AI Chatbot Example

AI Chatbot Example — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • DAVI

    DAVI

    The Dutch Automated Vehicle Initiative (DAVI) is a research and demonstration initiative developing automated vehicles for use on public roads. The project is unique in that, besides simply making driverless cars, it also focuses on having automated vehicles share information among each other. The aim is to have the cars help to avoid traffic congestion by reducing the safety distance between the cars (from 2 seconds to 0.5 seconds) and avoiding sudden traffic slow-downs due to maneuvers undertaken by drivers.

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  • Cover (telecommunications)

    Cover (telecommunications)

    In telecommunications and tradecraft, cover is the technique of concealing or altering the characteristics of communications patterns for the purpose of denying an unauthorized receiver information that would be of value. The purpose of cover is not to make the communication secure, but to make it look like noise, rendering it uninteresting and not worth analysis. Even if an attacker recognizes the communication as interesting, cover makes traffic analysis more difficult since he must crack the cover before he can find out to whom it is addressed. Usually, the covered communication is also encrypted. In this way, enemies have no idea you sent a message; friends know you sent a message, but don't know what you said; the intended recipient knows what you said. Technically, cover sometimes refers to the specific process of modulo two additions of a pseudorandom bit stream generated by a cryptographic device with bits from the control message. Source: from Federal Standard 1037C and from MIL-STD-188

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  • Social media therapy

    Social media therapy

    Social media therapy is a form of expressive therapy. It uses the act of creating and sharing user-generated content as a way of connecting with and understanding people. Social media therapy combines different expressive therapy aspects of talk therapy, art therapy, writing therapy, and drama therapy and applies them to the web domain. Within social media therapy, synchronous or asynchronous dialogue occurs through exchanges of audio, text or visual information. The digital content is published online to serve as a form of therapy. == Background == Time spent online via email, websites, instant messaging and social media has increased: since 1999, more than 2,554 million people have become internet users. This alters the way people communicate with each other, and alters the connotation of certain words. The concepts of "identity", "friend", "like" and "connected" have adapted alongside technology. People are influenced by data sharing, social marketing, and technological tools. There are multiple therapeutic services offered through the internet. E-therapy, online counseling, cyber therapy, and social media therapy are similar in that each utilizes the internet in order to provide therapy for patients. == Controversy == There are pros and cons when it comes to the subject of online therapy. Criticism of providing therapy through online methods comes from concerns over the lack of physical contact. There are important features of therapy created through face-to-face therapy such as transference and countertransference that can not be created through online therapy. Patricia R. Recupero and Samara E. Rainey stated in their article "Informed Consent to E-Therapy" of American Journal of Psychotherapy that the lack of face-to-face interaction increased the risk of misdiagnosis and misunderstanding between the E-therapist and patient, thereby increasing the risk of uncertainty for the clinician. There are also concerns over the internet creating a distraction from the therapy itself. Confidentiality and privacy concerns have been raised as well. However, several systematic reviews have found that online psychotherapy can produce clinical outcomes comparable to face-to-face treatment, suggesting that physical distance does not inherently reduce therapeutic effectiveness.

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  • Social media therapy

    Social media therapy

    Social media therapy is a form of expressive therapy. It uses the act of creating and sharing user-generated content as a way of connecting with and understanding people. Social media therapy combines different expressive therapy aspects of talk therapy, art therapy, writing therapy, and drama therapy and applies them to the web domain. Within social media therapy, synchronous or asynchronous dialogue occurs through exchanges of audio, text or visual information. The digital content is published online to serve as a form of therapy. == Background == Time spent online via email, websites, instant messaging and social media has increased: since 1999, more than 2,554 million people have become internet users. This alters the way people communicate with each other, and alters the connotation of certain words. The concepts of "identity", "friend", "like" and "connected" have adapted alongside technology. People are influenced by data sharing, social marketing, and technological tools. There are multiple therapeutic services offered through the internet. E-therapy, online counseling, cyber therapy, and social media therapy are similar in that each utilizes the internet in order to provide therapy for patients. == Controversy == There are pros and cons when it comes to the subject of online therapy. Criticism of providing therapy through online methods comes from concerns over the lack of physical contact. There are important features of therapy created through face-to-face therapy such as transference and countertransference that can not be created through online therapy. Patricia R. Recupero and Samara E. Rainey stated in their article "Informed Consent to E-Therapy" of American Journal of Psychotherapy that the lack of face-to-face interaction increased the risk of misdiagnosis and misunderstanding between the E-therapist and patient, thereby increasing the risk of uncertainty for the clinician. There are also concerns over the internet creating a distraction from the therapy itself. Confidentiality and privacy concerns have been raised as well. However, several systematic reviews have found that online psychotherapy can produce clinical outcomes comparable to face-to-face treatment, suggesting that physical distance does not inherently reduce therapeutic effectiveness.

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  • Sahara Net

    Sahara Net

    Sahara Net is an information and communications technology provider (ICT) serving the Saudi market, the company has rapidly grown since 1989 to offer various complementary services such as connectivity, internet, hosting, cloud, optimization, cyber security, and managed services. == History == Sahara Net is a Saudi Joint Stock Company (JSC) and its history goes back to 1989 when Sahara Net established the 1st Saudi Bulletin Board Service (BBS) in the Kingdom. During this period, it operated as a hub for email exchange in the FidoNet network. And in 1994 Sahara Net started offering Internet connectivity and other related services like internet email, web design, web hosting, and Domain name registry services. These services made the first ISP in Saudi Arabia before the official licensing in 1998, when the Saudi Internet market was regulated and Sahara Net received Internet Service Provider (ISP) license and was appointed as the official Local Internet Registry (LIR) in the Kingdom of Saudi Arabia. == Today == The company grew over these years to become one of the main ICTs in the Saudi Arabian market, extending network coverage to all major cities in Saudi Arabia, and offering various connectivity options to business as well as home users. In 2009, the company was partially acquired by Telindus (the ICT investment arm of Belgacom), the famous telecom operator in Belgium and Europe. Then, in 2014, the company was fully acquired by its original founders. Recently, Sahara Net was converted from an LLC to a JSC with over 1200 shareholders by a capital raise (original founders still control 70% of the shares).

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  • Caste census

    Caste census

    Caste census is a proposed census to be conducted in India by the Central Government of India. The proposed census was decided under the leadership of Prime Minister Narendra Modi by the cabinet committee of political affairs (CCPA) on 30 April 2025. It has been decided that a caste enumeration should be included with the forthcoming census. The exact time has not been declared yet. It is unclear that when the next census will be held. The decision of the cabinet was announced by the Central Railway Minister Ashwini Vaishnaw. It has been seen as a step that would help in drafting "equitable and targeted" policies by the present Central Government of India led by the Bhartiya Janta Party in India. The Central Home Minister Amit Shah has described the decision as a "historic decision". He has also described that the historic decision as “committed to social justice”. The leader of opposition Rahul Gandhi has welcomed the decision. He said "We have shown we can pressure govt" He has demanded a clear timeline for its completion. He has called it "The first step towards deep social reform". == Description == The caste census is a systematic recording of individuals’ caste identities during the nationwide census in the country. The Central minister Ashwini Vaishnaw expressed his view on the proposed census and said that it would "strengthen the social and economic structure of our society while the nation continues to progress”. The Caste census will happen for the first time in 100 years by the Central Government of India. It will be the part of the upcoming census in India. == History == According to Peabody, the first systematic caste-wise enumeration of households in the Indian subcontinent was conducted between 1658 and 1664 across seven districts of the then Marwar Kingdom, including Jodhpur city which was its capital. It was conducted by the then home minister Munhata Nainsi of the kingdom for the purpose of tax documentation. It was not to for classification of society or creation of social hierarchies but solving a tax related problem. During the period of the British rule in India, caste census was included in the decadal censuses to categorise the population by caste, religion and occupation. In 1871–72, the first detailed caste census was conducted by the government of British Raj in India. It was practiced between the period 1881 to 1931. The last caste census was conducted in the year 1931 in which 4,147 castes were recorded. The largest population in the whole of British India (including Pakistan and Bangladesh) was of Brahmins. The population of Brahmins was recorded more than 1.5 crores. After Brahmin community, the second place was of Jatav (Chamar)community. The population of Jatav was a little more than 1.23 crores. On the third place were Rajputs. The population of Rajputs was 81 lakhs. The Rajput caste was followed by the Kunbi caste of Maharashtra. The population of Kunbi caste was 64 lakhs and 34 thousands. The Kunbi caste was followed by Yadav (Ahir) caste. The population of Yadav (Ahir) community was 56 lakhs and 82 thousands. The Yadav (Ahir) caste was followed by Teli community. The population of Teli community was 42 lakhs and 58 thousands. The Teli community was followed by Gwala community. The population of the Gwala community was 40 lakhs. After the independence of India, the caste enumeration was stopped by the newly independent Government of India led by the prime minister Pandit Jawahar Lal Nehru in 1951. The caste enumeration was stopped to avoid reinforcing social divisions in the Indian society. But, there was an exception made for the enumeration of the Scheduled Castes (SCs) and Scheduled Tribes (STs) in the decadal censuses. Therefore, the enumeration of the Scheduled Castes and the Scheduled Tribes is being conducted in every census since 1951. In 1961, the Government of India permitted states for conducting their own surveys to compile OBC lists, but national caste census was not conducted.

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  • Viral marketing

    Viral marketing

    Viral marketing is a business strategy that uses existing social networks to promote a product or service on social media platforms. Its name refers to how consumers spread information about a product with other people, much in the same way that a virus spreads from one person to another. It can be delivered by word of mouth, or enhanced by the network effects of the Internet and mobile networks. The concept is often misused or misunderstood, as people apply it to any successful enough story without taking into account the word "viral". Viral advertising is personal and, while coming from an identified sponsor, it does not mean businesses pay for its distribution. Most of the well-known viral ads circulating online are ads paid by a sponsor company, launched either on their own platform (company web page or social media profile) or on social media websites such as YouTube. Consumers receive the page link from a social media network or copy the entire ad from a website and pass it along through e-mail or posting it on a blog, web page or social media profile. Viral marketing may take the form of video clips, advergames, ebooks, brandable software, images, text messages, email messages, or web pages. The most commonly utilized transmission vehicles for viral messages include pass-along based, incentive based, trendy based, and undercover based. However, the creative nature of viral marketing enables an "endless amount of potential forms and vehicles the messages can utilize for transmission", including mobile devices. The ultimate goal of marketers interested in creating successful viral marketing programs is to create viral messages that appeal to individuals with high social networking potential (SNP) and that have a high probability of being presented and spread by these individuals and their competitors in their communications with others in a short period. The term "viral marketing" has also been used pejoratively to refer to stealth marketing campaigns—marketing strategies that advertise a product to people without them knowing they are being marketed to. == History == The emergence of "viral marketing", as an approach to advertisement, has been tied to the popularization of the notion that ideas spread like viruses. The field that developed around this notion, memetics, peaked in popularity in the 1990s. As this then began to influence marketing gurus, it took on a life of its own in that new context. The brief career of Australian pop singer Marcus Montana is largely remembered as an early example of viral marketing. In early 1989, thousands of posters declaring "Marcus is Coming" were placed around Sydney, generating discussion and interest within the media and the community about the meaning of the mysterious advertisements. The campaign successfully made Montana's musical debut a talking point, but his subsequent music career was a failure. The term is found in PC User magazine in 1989 with a somewhat differing meaning. It was later used by Jeffrey Rayport in the 1996 Fast Company article "The Virus of Marketing", and Tim Draper and Steve Jurvetson of the venture capital firm Draper Fisher Jurvetson in 1997 to describe Hotmail's practice of appending advertising to outgoing mail from their users. Doug Rushkoff, a media critic, wrote about viral marketing on the Internet in 1996. Bob Gerstley wrote about algorithms designed to identify people with high "social networking potential." Gerstley employed SNP algorithms in quantitative marketing research. In 2004, the concept of the alpha user was coined to indicate that it had now become possible to identify the focal members of any viral campaign, the "hubs" who were most influential. Alpha users could be targeted for advertising purposes most accurately in mobile phone networks, due to their personal nature. In early 2013, the first ever Viral Summit was held in Las Vegas. == Factors == Marketer Jonah Berger defines six key factors that drive virality, organized in an acronym called STEPPS: Social currency – the better something makes people look, the more likely they will be to share it Triggers – things that are "top of mind" are more likely to be "tip of the tongue" Emotion – when people care, they share Public – the easier something is to see, the more likely people are to imitate it Practical value – people share useful information to help others Stories – like a Trojan Horse, stories carry messages and ideas along for the ride. Another important factor that drives virality is the propagativity of the content, referring to the ease with which consumers can redistribute it. == Psychology == To form deeper connections with viewers and increase the chances of virality, many marketers use psychological principles. They argue that this approach is scientific and can foster an environment where the odds of gaining traction are much higher. People find psychological safety and can develop a sense of trust when more people interact with online content. For this reason, marketers work to develop media that resonates with viewers on a deeper, emotional level as this approach frequently results in higher engagement. This level of interaction serves as a sign of approval, reducing the personal risk that is subconsciously linked to associating oneself with a company or brand’s content. Professor Jonah Berger at the University of Pennsylvania's Wharton School of Business affirms that marketing campaigns that trigger psychological responses linked to strong emotions tend to perform better. In particular, Berger found that positive emotions like happiness, joy, and excitement have more successful share rates than their negative counterparts. This outcome results from the human instinct to respond more positively to content with activating emotions, increasing the desire to share content, which contributes to its virality. Viral marketing utilizes the primitive feeling of frisson to increase their view and share counts. This feeling of excitement is considered powerful because of its ability to cause a physical response. From increased heart rates to full body chills, Professor Brent Coker at the University of Melbourne describes that this approach to marketing triggers a primitive response that immerses the viewer in the content on a deeper level. Researchers Juliana Fernandes from the University of Florida and Sigal Segev from the Florida International University also found that people are more inclined to share emotional campaigns over those that are heavily informational. They claim that consumers do not often care to learn about a product’s actual features and benefits. Instead, people prefer to be immersed in experience-based content that creates an emotional impact. Companies and brands can benefit from treating their content in this manner and go viral more frequently than those who do not. Social proof is another psychological phenomenon that impacts viral content. Experts in this field argue that it is a natural instinct to want to behave similarly to others because it results in positive validation. This phenomenon explains the human need to conform, so marketers focus on creating engaging content that encourages interactions and causes a snowball effect. This subconsciously influences people to like, comment, and share if they already see others doing the same. Social proof goes further by providing people with a form of social currency. When individuals interact with and share content, they become associated with the topics at hand. People naturally tend to perceive one another, and this pattern carries over to the digital world. As a result, many people tend to be vigilant about the viral marketing they engage with, since they want to be perceived positively. Companies and brands have the opportunity to develop social currency themselves by aligning with their target audiences and creating marketing campaigns that fit their interests or match their values. == Methods and metrics == According to marketing professors Andreas Kaplan and Michael Haenlein, to make viral marketing work, three basic criteria must be met, i.e., giving the right message to the right messengers in the right environment: Messenger: Three specific types of messengers are required to ensure the transformation of an ordinary message into a viral one: market mavens, social hubs, and salespeople. Market mavens are individuals who are continuously 'on the pulse' of things (information specialists); they are usually among the first to get exposed to the message and who transmit it to their immediate social network. Social hubs are people with an exceptionally large number of social connections; they often know hundreds of different people and have the ability to serve as connectors or bridges between different subcultures. Salespeople might be needed who receive the message from the market maven, amplify it by making it more relevant and persuasive, and then transmit it to the social hub for further distr

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  • Social employee

    Social employee

    A social employee is a worker operating within a social business model. Following an organization's social computing guidelines, social employees use social media tools both for internal workflow and collaboration purposes and for external engagement with customers, prospects and stakeholders through a combination of social media marketing, content marketing, social marketing, and social selling. Social employee programs are considered to be as much about culture and engagement as they are about business processes and best practices. In addition to increased leads and sales, social employee best practices are said to improve business outcomes important to social media marketing, such as increased connections and web traffic, improved brand identification and "chatter", and better customer advocacy. == Overview == The term "social employee" was first introduced to describe those exhibiting the emerging characteristics of workers operating under a social business model. The term is often used interchangeably with similar designations like "employee advocate" or "social employee advocate". Crucial to the perceived value of the social employee is the concept of the digital footprint. While organizations are able to generate large bases of followers through social media, research shows that brand marketing and engagement efforts through these networks are not as effective as those of individual employees. In fact, some research indicates that employee experts are more trusted than any other member of an organization. Because of this, social employee programs are designed to train, empower, and support employee engagement efforts in the hopes of authentically engaging larger communities, increasing the frequency of shares, reviews, and other forms of "earned media" and expanding the brand's presence on the web. == The personal or employee brand == A foundational concept of the social employee is the idea of the personal or employee brand. This concept first gained popular attention in a 1997 FastCompany article by business leader Tom Peters titled "The Brand Called You". In the article, Peters argued that the premium placed on branding impacted workers' lives to such an extent that creating and cultivating a distinct personal brand had become a professional necessity. According to Peters, doing so built trust, loyalty, visibility, influence, and employability. With increased adoption of social media tools by both businesses and consumers in the early 21st century, many business leaders became increasingly concerned with social engagement, both internally among employees and externally with customers and other stakeholders. While many in the business community acknowledged the potential social tools had for improved collaboration, productivity, and brand messaging, the concern that employees would misrepresent their brand, disclose proprietary information, or otherwise damage their company's reputation or ability to conduct business persisted. As a result, many began to advocate for employee branding as a solution to this problem. This helped give new meaning to the concept of brand ambassadorship, positioning everyday employees in public, and potentially high-profile, engagement roles. == Characteristics == === Engaged === Because social employee advocacy is dependent on the perceived authenticity of the employee, engagement is highly valued in social organizations. Further, data show the measurable impact of employee engagement on organizational productivity and profitability: Happy employees were found to be 12 percent more productive. In one study, engaged employees were found to be 38 percent more likely to produce at above-average rates. In another, organizations with engaged employees had a 19 percent higher than average shareholder return, while organizations with disengaged employees experienced shareholder return that was 44 percent below average. Engaged companies were found to outperform disengaged companies by up to 202 percent. Companies with strong focus on culture were found to have an average 13.9 percent turnover rate, while those with a low focus experience were found to have a 48.4 percent turnover rate. === Flexible job environment and work–life balance === The number of professionals working mobile or remote has risen considerably since 2010. While estimates vary, one study found that number of organizations with mobile or remote employees is expected to rise from 24 percent in 2012 to 89 percent by 2020. Other research has estimated that by 2020, 105.4 million professionals will work remotely in America, about 72.3 percent of the total workforce. This change has been linked to a rise in social technologies, including biometrics, wearables, near-field communications, and augmented reality. Social employees have also put a greater emphasis on work–life balance, with many believing that advances in technology can directly support efforts in this area. Purported benefits of this shift include a more flexible workforce, reduced business costs, and greater organizational leverage in attracting and retaining top talent. === Buys into the brand's story === In 2009, thought leader Simon Sinek presented a speech called "How Great Leaders Inspire Action" at a TEDxPugetSound event. Sinek's central argument in this speech was, "People don't buy what you do. They buy why you do it." This concept—that the story behind a business or product offering is a more compelling sales tool than the product itself—is frequently cited in social media marketing as a way to build authentic connections with stakeholders. However, others have argued that for employees to share a brand's story authentically, they must be engaged in that story themselves, and as a result, many companies have made storytelling part of their culture programs. === Collaborative === An implicit tenet in social business is that social technologies aren't a barrier to productivity, but rather a path to increased connectivity. The shift in enterprise software systems like IBM Connections to incorporate social communication models, such as mentions, wikis, and newsfeeds, reflects the changing communication dynamics within business. With an increase in diversity and sophistication in collaborative software platforms, social organizations have sought to find new creative ways to utilize these tools and secure employee buy-in around them. Crowdsourcing has also become popular in social businesses. Examples include AT&T's program The Innovation Pipeline (TIP), begun in 2009, which has generated over 28,000 ideas that have led to over 75 projects with funding exceeding $44 million. IBM has also put considerable resources into such processes, producing its social computing guidelines through employee crowdsourcing, as well as its Connections platform through the Technology Adoption Program (TAP), a more formalized crowdsourcing initiative. Another popular form of internal collaboration is the hack day, or hackathon. Organizations such as Netflix, Facebook, and IBM use hack days to pull employees out of their day-to-day work environments and encourage them to collaborate in nontraditional ways in an attempt to drive disruptive innovation. Social employees are often encouraged to seek external collaboration opportunities with customers and prospects. For example, Procter & Gamble introduced the Live Well Collaborative to connect with external stakeholders and develop products and services for the 50+ demographic. === Social listener === A social listener is someone who engages in social listening, or social media monitoring, for professional means. Social employees can use social media monitoring for a variety of reasons, including professional development, industry news and trends, and gauging market sentiment. Some have argued that social listening is one of the most important components of social business, as it enables organizations to collect rich market data, make more informed strategic decisions, and respond to customer needs more authentically. === Customer-centric === Advocates of customer-centricity in social business argue that social media has changed the dynamic from one-way brand messaging to shared interactions between brand and customer. Brand and customer engagement is seen as a means of creating more lasting connections with customers and prospects and empowering them to become brand promoters. Customer-centric interactions are seen to have distinct value to brands, as research shows that prospects are far more likely to trust brand-related messaging from a friend or family member than they are from a brand. As a means of building social employees, some social advocates have also called for a broader definition of customer to include the employees themselves. In the book The Pursuit of Social Business Excellence, authors Vala Afshar and Brad Martin made the following argument: A social business operates with the guiding principle that each employee's responsi

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  • Mooky (app)

    Mooky (app)

    Mooky was a location-based social and dating application, designed to help its users to find the perfect match by providing a large scale of filters. Mooky was free of charge. The app made use of mobile devices' geolocation, a feature of smart phones and other devices which allows users to locate other users who are nearby. == History == Mooky was published on Google Play on April 17, 2016, by Mooky BV. The latest version of this application was version 1.0.6. == Overview == === How it works === Mooky used Facebook to build a user profile with photos and basic information, like the user's surname and age. From there on the user had to fill in their Mooky profile, which contains information about the user's height, posture, hair color, eye color, ethnicity and religion. After this the user could select its preferences to find matches nearby. === User verification === Mooky asked their users to take a selfie holding a piece of paper saying 'Mooky'. Mooky would then manually accept or decline the user verification.

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  • Big memory

    Big memory

    Big-memory computers are machines with a large amount of random-access memory (RAM). The computers are required for databases, graph analytics, or more generally, high-performance computing, data science, and big data. Some database systems called in-memory databases are designed to run mostly in memory, rarely if ever retrieving data from disk or flash memory. See list of in-memory databases. == Details == The performance of big-memory systems depends on how the central processing units (CPUs) access the memory, via a conventional memory controller or via non-uniform memory access (NUMA). Performance also depends on the size and design of the CPU cache. Performance also depends on operating system (OS) design. The huge pages feature in Linux and other OSes can improve the efficiency of virtual memory. The transparent huge pages feature in Linux can offer better performance for some big-memory workloads. The "Large-Page Support" in Microsoft Windows enables server applications to establish large-page memory regions which are typically three orders of magnitude larger than the native page size.

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  • Undeniable signature

    Undeniable signature

    An undeniable signature is a digital signature scheme which allows the signer to be selective to whom they allow to verify signatures. The scheme adds explicit signature repudiation, preventing a signer later refusing to verify a signature by omission; a situation that would devalue the signature in the eyes of the verifier. It was invented by David Chaum and Hans van Antwerpen in 1989. == Overview == In this scheme, a signer possessing a private key can publish a signature of a message. However, the signature reveals nothing to a recipient/verifier of the message and signature without taking part in either of two interactive protocols: Confirmation protocol, which confirms that a candidate is a valid signature of the message issued by the signer, identified by the public key. Disavowal protocol, which confirms that a candidate is not a valid signature of the message issued by the signer. The motivation for the scheme is to allow the signer to choose to whom signatures are verified. However, that the signer might claim the signature is invalid at any later point, by refusing to take part in verification, would devalue signatures to verifiers. The disavowal protocol distinguishes these cases removing the signer's plausible deniability. It is important that the confirmation and disavowal exchanges are not transferable. They achieve this by having the property of zero-knowledge; both parties can create transcripts of both confirmation and disavowal that are indistinguishable, to a third-party, of correct exchanges. The designated verifier signature scheme improves upon deniable signatures by allowing, for each signature, the interactive portion of the scheme to be offloaded onto another party, a designated verifier, reducing the burden on the signer. == Zero-knowledge protocol == The following protocol was suggested by David Chaum. A group, G, is chosen in which the discrete logarithm problem is intractable, and all operation in the scheme take place in this group. Commonly, this will be the finite cyclic group of order p contained in Z/nZ, with p being a large prime number; this group is equipped with the group operation of integer multiplication modulo n. An arbitrary primitive element (or generator), g, of G is chosen; computed powers of g then combine obeying fixed axioms. Alice generates a key pair, randomly chooses a private key, x, and then derives and publishes the public key, y = gx. === Message signing === Alice signs the message, m, by computing and publishing the signature, z = mx. === Confirmation (i.e., avowal) protocol === Bob wishes to verify the signature, z, of m by Alice under the key, y. Bob picks two random numbers: a and b, and uses them to blind the message, sending to Alice: c = magb. Alice picks a random number, q, uses it to blind, c, and then signing this using her private key, x, sending to Bob: s1 = cgq ands2 = s1x. Note that s1x = (cgq)x = (magb)xgqx = (mx)a(gx)b+q = zayb+q. Bob reveals a and b. Alice verifies that a and b are the correct blind values, then, if so, reveals q. Revealing these blinds makes the exchange zero knowledge. Bob verifies s1 = cgq, proving q has not been chosen dishonestly, and s2 = zayb+q, proving z is valid signature issued by Alice's key. Note that zayb+q = (mx)a(gx)b+q. Alice can cheat at step 2 by attempting to randomly guess s2. === Disavowal protocol === Alice wishes to convince Bob that z is not a valid signature of m under the key, gx; i.e., z ≠ mx. Alice and Bob have agreed an integer, k, which sets the computational burden on Alice and the likelihood that she should succeed by chance. Bob picks random values, s ∈ {0, 1, ..., k} and a, and sends: v1 = msga and v2 = zsya, where exponentiating by a is used to blind the sent values. Note that v2 = zsya = (mx)s(gx)a = v1x. Alice, using her private key, computes v1x and then the quotient, v1xv2−1 = (msga)x(zsgxa)−1 = msxz−s = (mxz−1)s. Thus, v1xv2−1 = 1, unless z ≠ mx. Alice then tests v1xv2−1 for equality against the values: (mxz−1)i for i ∈ {0, 1, …, k}; which are calculated by repeated multiplication of mxz−1 (rather than exponentiating for each i). If the test succeeds, Alice conjectures the relevant i to be s; otherwise, she conjectures random value. Where z = mx, (mxz−1)i = v1xv2−1 = 1 for all i, s is unrecoverable. Alice commits to i: she picks a random r and sends hash(r, i) to Bob. Bob reveals a. Alice confirms that a is the correct blind (i.e., v1 and v2 can be generated using it), then, if so, reveals r. Revealing these blinds makes the exchange zero knowledge. Bob checks hash(r, i) = hash(r, s), proving Alice knows s, hence z ≠ mx. If Alice attempts to cheat at step 3 by guessing s at random, the probability of succeeding is 1/(k + 1). So, if k = 1023 and the protocol is conducted ten times, her chances are 1 to 2100.

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  • Dashboard (computing)

    Dashboard (computing)

    In computer information systems, a dashboard is a type of graphical user interface which often provides at-a-glance views of data relevant to a particular objective or process through a combination of visualizations and summary information. In other usage, "dashboard" is another name for "progress report" or "report" and is considered a form of data visualization. The dashboard is often accessible by a web browser and is typically linked to regularly updating data sources. Dashboards are often interactive and facilitate users to explore the data themselves, usually by clicking into elements to view more detailed information. The term dashboard originates from the automobile dashboard where drivers monitor the major functions at a glance via the instrument panel. == History == The idea of digital dashboards followed the study of decision support systems in the 1970s. Early predecessors of the modern business dashboard were first developed in the 1980s in the form of Executive Information Systems (EISs). Due to problems primarily with data refreshing and handling, it was soon realized that the approach wasn't practical as information was often incomplete, unreliable, and spread across too many disparate sources. Thus, EISs hibernated until the 1990s when the information age quickened pace and data warehousing, and online analytical processing (OLAP) allowed dashboards to function adequately. Despite the availability of enabling technologies, the dashboard use didn't become popular until later in that decade, with the rise of key performance indicators (KPIs), and the introduction of Robert S. Kaplan and David P. Norton's balanced scorecard. In the late 1990s, Microsoft promoted a concept known as the Digital Nervous System and "digital dashboards" were described as being one leg of that concept. Today, the use of dashboards forms an important part of Business Performance Management (BPM). Initially dashboards were used for monitoring purposes, now with the advancement of technology, dashboards are being used for more analytical purposes. The use of dashboards has now been incorporating; scenario analysis, drill down capabilities, and presentation format flexibility. == Benefits == Digital dashboards allow managers to monitor the contribution of the various departments in their organization. In addition, they enable “rolling up” of information to present a consolidated view across an organization. To gauge exactly how well an organization is performing overall, digital dashboards allow you to capture and report specific data points from each department within the organization, thus providing a "snapshot" of performance. Benefits of using digital dashboards include: Visual presentation of performance measures Ability to identify and correct negative trends Measure efficiencies/inefficiencies Ability to generate detailed reports showing new trends Ability to make more informed decisions based on collected business intelligence Dashboards offers a holistic view of the entire business as it gives the manager a bird's eye view into the performance of sales, data inventory, web traffic, social media analytics and other associated data that is visually presented on a single dashboard. Dashboards lead to better management of marketing/financial strategies as a dashboard for the display of marketing data makes the process of marketing easier and more reliable as compared to doing it manually. Web analytics play a crucial role in shaping the marketing strategy of many businesses. Dashboards also facilitate for better tracking of sales and financial reporting as the data is more precise and in one area. Lastly, dashboards offer for better customer service through monitoring because they keep both the managers and the clients updated on the project progress through automated emails and notifications. == Align strategies and organizational goals == Gain total visibility of all systems instantly Quick identification of data outliers and correlations Consolidated reporting into one location Available on mobile devices to quickly access metrics == Classification == Dashboards can be broken down according to role and are either strategic, analytical, operational, or informational. Dashboards are the 3rd step on the information ladder, demonstrating the conversion of data to increasingly valuable insights. Strategic dashboards support managers at any level in an organization and provide the quick overview that decision-makers need to monitor the health and opportunities of the business. Dashboards of this type focus on high-level measures of performance and forecasts. Strategic dashboards benefit from static snapshots of data (daily, weekly, monthly, and quarterly) that are not constantly changing from one moment to the next. Dashboards for analytical purposes often include more context, comparisons, and history, along with subtler performance evaluators. In addition, analytical dashboards typically support interactions with the data, such as drilling down into the underlying details. Dashboards for monitoring operations are often designed differently from those that support strategic decision making or data analysis and often require monitoring of activities and events that are constantly changing and might require attention and response at a moment's notice. == Types of dashboards == Digital dashboards may be laid out to track the flows inherent in the business processes that they monitor. Graphically, users may see the high-level processes and then drill down into low-level data. This level of detail is often buried deep within the corporate enterprise and otherwise unavailable to the senior executives. Three main types of digital dashboards dominate the market today: desktop software applications, web-browser-based applications, and desktop applications are also known as desktop widgets. The last are driven by a widget engine. Both Desktop and Browser-based providers enable the distribution of dashboards via a web browser. An example of the latter is web-based-browser Asana, which helps teams orchestrate their work, from daily tasks to strategic cross-functional initiatives. With it, teams can manage everything from company objectives to digital transformation to product launches and marketing campaigns. Specialized dashboards may track all corporate functions. Examples include human resources, recruiting, sales, operations, security, information technology, project management, customer relationship management, digital marketing and many more departmental dashboards. For a smaller organization like a startup a compact startup scorecard dashboard tracks important activities across lot of domains ranging from social media to sales. Digital dashboard projects involve business units as the driver and the information technology department as the enabler. Therefore, the success of dashboard projects depends on the relevancy/importance of information provided within the dashboard. This includes the metrics chosen to monitor and the timeliness of the data forming those metrics; data must be up to date and accurate. Key performance indicators, balanced scorecards, and sales performance figures are some of the content appropriate on business dashboards. === Performance Dashboards === Dashboards involve the combination of visual and functional features. This combination of features helps improve cognition and interpretation. A performance dashboard sits at the intersection of two powerful disciplines: business intelligence and performance management. Therefore, there are different users who could use these dashboards for different reasons. For example, a level of workers could look at monitoring inventory while those in more managerial roles can look at lagging measure. Then executives could utilize the dashboard to evaluate strategic performance against objectives. == Dashboards and scorecards == Balanced scorecards and dashboards have been linked together as if they were interchangeable. However, although both visually display critical information, the difference is in the format: Scorecards can open the quality of an operation while dashboards provide calculated direction. A balanced scorecard has what they called a "prescriptive" format. It should always contain these components: Perspectives – group Objectives – verb-noun phrases pulled from a strategy plan Measures – also called metric or key performance indicators (KPIs) Spotlight indicators – red, yellow, or green symbols that provide an at-a-glance view of a measure's performance. Each of these sections ensures that a Balanced Scorecard is essentially connected to the businesses critical strategic needs. The design of a dashboard is more loosely defined. Dashboards are usually a series of graphics, charts, gauges and other visual indicators that can be monitored and interpreted. Even when there is a strategic link, on a dashboard, it may not be noticed as such since objectives are not normally pre

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  • Autonomous logistics

    Autonomous logistics

    Autonomous logistics describes systems that provide unmanned, autonomous transfer of equipment, baggage, people, information or resources from point-to-point with minimal human intervention. Autonomous logistics is a new area being researched and currently there are few papers on the topic, with even fewer systems developed or deployed. With web enabled cloud software there are companies focused on developing and deploying such systems which will begin coming online in 2018. == Autonomous logistics vehicles == There are several subclasses of autonomous logistics vehicles: Ground autonomous logistics Based on Unmanned ground vehicle technology, a large autonomous logistics tracked carrier, which can be deployed in a tropical forest for day and night, has been developed. Another example is the TerraMax autonomous truck based on Oshkosh's Medium Tactical Vehicle Replacement (MTVR) military truck platform. Most recently, TerraMax competed in the 2007 Darpa Urban Challenge. The MTVR was designed for the U.S. Marine Corps with a 70% off-road mission profile. TerraMax's unmanned ground vehicle kit does not interfere with the conventional operation of the vehicle. A robust sensor suite allows for 360-degree situational awareness around TerraMax. Elements of the autonomous navigation kit could be used to enhance driver awareness. The complete kit could be used in applications such as snow removal on airport runways. Aerial autonomous logistics Based on unmanned aerial vehicle technology, aerial autonomous logistics (or logistics UAVs) provides transfer of resources and equipment in disaster relief situations, replenishment operations, reconnaissance operations where information is gathered, and general parcel or package delivery. Space autonomous logistics Describes the ability to provide logistics to and from space, be that orbital, lunar or beyond. Current space logistics vehicle examples are the Progress spacecraft, Russian expendable freighter uncrewed resupply spacecraft and the Automated Transfer Vehicle, expendable uncrewed resupply spacecraft developed by the European Space Agency. Above Water autonomous logistics Based on unmanned surface vehicle technology, this class of vehicles provides a range of surface fleet replenishment and equipment transfer capabilities. Subsea autonomous logistics Using autonomous underwater vehicle technology, these vehicles provide re-supply to underwater facilities, reconnaissance of underwater structures, emergency recovery capability, and so on. == Agent-based logistics == Shipping containers handle most of today's intercontinental transport of packaged goods. Managing them in terms of planning and scheduling is a challenging task due to the complexity and dynamics of the involved processes. Hence, recent developments show an increasing trend towards autonomous control with software agents acting on behalf of the logistic objects. Despite the high degree of autonomy it is still necessary to cooperate in order to achieve certain goals. The current trends and recent changes in logistics lead to new, complex and partially conflicting requirements for logistic planning and control systems. Due to the distributed nature of logistics, the usage of agent technology is promising. Due to the mobile nature of logistics, the usage of mobile agent technology is promising as well. Scenarios of usage of mobile agents in logistics has been envisioned.

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  • Verifiable secret sharing

    Verifiable secret sharing

    In cryptography, a secret sharing scheme is verifiable if auxiliary information is included that allows players to verify their shares as consistent. More formally, verifiable secret sharing ensures that even if the dealer is malicious there is a well-defined secret that the players can later reconstruct. (In standard secret sharing, the dealer is assumed to be honest.) The concept of verifiable secret sharing (VSS) was first introduced in 1985 by Benny Chor, Shafi Goldwasser, Silvio Micali and Baruch Awerbuch. In a VSS protocol a distinguished player who wants to share the secret is referred to as the dealer. The protocol consists of two phases: a sharing phase and a reconstruction phase. Sharing: Initially the dealer holds secret as input and each player holds an independent random input. The sharing phase may consist of several rounds. At each round each player can privately send messages to other players and can also broadcast a message. Each message sent or broadcast by a player is determined by its input, its random input and messages received from other players in previous rounds. Reconstruction: In this phase each player provides its entire view from the sharing phase and a reconstruction function is applied and is taken as the protocol's output. An alternative definition given by Oded Goldreich defines VSS as a secure multi-party protocol for computing the randomized functionality corresponding to some (non-verifiable) secret sharing scheme. This definition is stronger than that of the other definitions and is very convenient to use in the context of general secure multi-party computation. Verifiable secret sharing is important for secure multiparty computation. Multiparty computation is typically accomplished by making secret shares of the inputs, and manipulating the shares to compute some function. To handle "active" adversaries (that is, adversaries that corrupt nodes and then make them deviate from the protocol), the secret sharing scheme needs to be verifiable to prevent the deviating nodes from throwing off the protocol. == Feldman's scheme == A commonly used example of a simple VSS scheme is the protocol by Paul Feldman, which is based on Shamir's secret sharing scheme combined with any encryption scheme which satisfies a specific homomorphic property (that is not necessarily satisfied by all homomorphic encryption schemes). The following description gives the general idea, but is not secure as written. (Note, in particular, that the published value gs leaks information about the dealer's secret s.) First, a cyclic group G of prime order q, along with a generator g of G, is chosen publicly as a system parameter. The group G must be chosen such that computing discrete logarithms is hard in this group. (Typically, one takes an order-q subgroup of (Z/pZ)×, where q is a prime dividing p − 1.) The dealer then computes (and keeps secret) a random polynomial P of degree t with coefficients in Zq, such that P(0) = s, where s is the secret. Each of the n share holders will receive a value P(1), ..., P(n) modulo q. Any t + 1 share holders can recover the secret s by using polynomial interpolation modulo q, but any set of at most t share holders cannot. (In fact, at this point any set of at most t share holders has no information about s.) So far, this is exactly Shamir's scheme. To make these shares verifiable, the dealer distributes commitments to the coefficients of P modulo q. If P(x) = s + a1x + ... + atxt, then the commitments that must be given are: c0 = gs, c1 = ga1, ... ct = gat. Once these are given, any party can verify their share. For instance, to verify that v = P(i) modulo q, party i can check that g v = c 0 c 1 i c 2 i 2 ⋯ c t i t = ∏ j = 0 t c j i j = ∏ j = 0 t g a j i j = g ∑ j = 0 t a j i j = g P ( i ) {\displaystyle g^{v}=c_{0}c_{1}^{i}c_{2}^{i^{2}}\cdots c_{t}^{i^{t}}=\prod _{j=0}^{t}c_{j}^{i^{j}}=\prod _{j=0}^{t}g^{a_{j}i^{j}}=g^{\sum _{j=0}^{t}a_{j}i^{j}}=g^{P(i)}} . This scheme is, at best, secure against computationally bounded adversaries, namely the intractability of computing discrete logarithms. Pedersen proposed later a scheme where no information about the secret is revealed even with a dealer with unlimited computing power. == Baghery's hash-based scheme == A recent line of research has proposed a unified framework, for building practical VSS schemes that do not necessarily require homomorphic commitments —a key requirement in traditional constructions such as Feldman's and Pedersen's schemes. The framework allows instantiations with different commitment schemes, including post-quantum secure options such as hash-based commitments. This offers a flexible and efficient approach to build VSS schemes, in which the verifiability of shares is decoupled from the need for homomorphic commitments, which are often tied to assumptions like the Discrete Logarithm (DL) problem, known to be insecure against quantum adversaries. One instantiation of the new framework uses hash-based commitments and a random oracle to construct a hash-based VSS scheme based on Shamir's secret sharing. === Protocol Overview === Sharing Phase: Given a secure hash-based commitment scheme C {\displaystyle {\mathcal {C}}} and a hash function H {\displaystyle {\mathcal {H}}} (modeled as a random oracle), to share a secret value s {\displaystyle s} among n {\displaystyle n} parties with threshold t {\displaystyle t} , the dealer acts as follows: Following Shamir sharing, the dealer samples a random degree- t {\displaystyle t} polynomial P ( X ) {\displaystyle P(X)} over a filed or ring, with P ( 0 ) = s {\displaystyle P(0)=s} . Each of the n {\displaystyle n} parties will receive a value v i = P ( i ) {\displaystyle v_{i}=P(i)} modulo q {\displaystyle q} as a share. To prove the validity of the shares, the dealer acts as follows: Samples another random degree- t {\displaystyle t} polynomial R ( X ) {\displaystyle R(X)} and n {\displaystyle n} random values γ 1 , … , γ n {\displaystyle \gamma _{1},\dots ,\gamma _{n}} from the same filed or ring. Computes a set of commitments c i = C ( P ( i ) , R ( i ) , γ i ) {\displaystyle c_{i}={\mathcal {C}}(P(i),R(i),\gamma _{i})} for i = 1 , 2 , … , n {\displaystyle i=1,2,\dots ,n} . Note that, the additional randomness γ i {\displaystyle \gamma _{i}} is used when the secret s {\displaystyle s} does not have sufficient entropy, but it can be omitted when sharing a uniformly random secret. Each of the n {\displaystyle n} parties will also receive a value γ i {\displaystyle \gamma _{i}} modulo q {\displaystyle q} as a share. Calculates a challenge value d {\displaystyle d} via a hash function d = H ( c 1 , … , c n ) {\displaystyle d={\mathcal {H}}(c_{1},\dots ,c_{n})} and then computes a polynomial Z ( X ) = R ( X ) + d ⋅ P ( X ) {\displaystyle Z(X)=R(X)+d\cdot P(X)} . Broadcasts the commitments c 1 , … , c n {\displaystyle c_{1},\dots ,c_{n}} along with Z ( X ) {\displaystyle Z(X)} as the proof and privately sends ( v i , γ i ) {\displaystyle (v_{i},\gamma _{i})} as the individual share to party i {\displaystyle i} . Verification Phase: Given an individual share ( v i , γ i ) {\displaystyle (v_{i},\gamma _{i})} and a proof ( c 1 , … , c n , Z ( X ) ) {\displaystyle (c_{1},\dots ,c_{n},Z(X))} , party i {\displaystyle i} verifies the correctness of it as below: Checks that Z ( X ) {\displaystyle Z(X)} is a valid (up to) degree- t {\displaystyle t} polynomial. Recomputes the challenge value d = H ( c 1 , … , c n ) {\displaystyle d={\mathcal {H}}(c_{1},\dots ,c_{n})} , and verifies the commitment equation c i = C ( v i , Z ( i ) − d v i , γ i ) {\displaystyle c_{i}={\mathcal {C}}(v_{i},Z(i)-dv_{i},\gamma _{i})} . If the verification fails, similar to Feldman’s and Pedersen’s schemes, the party raises a complaint. If too many complaints (more than t {\displaystyle t} ) are raised, the dealer is disqualified. In case of a complaint, the dealer can publicly reveal the disputed share to allow global verification. Honest parties can then collectively agree to either continue or disqualify the dealer. This scheme supports the sharing of both low-entropy and high-entropy secrets. Moreover, since it relies solely on secure hash functions for commitments and on a (quantum) random oracle, it plausibly achieves security even against quantum adversaries. Additionally, by using only lightweight cryptographic primitives, the scheme is considerably more efficient in practice compared to traditional VSS constructions based on number-theoretic assumptions. == Benaloh's scheme == Once n shares are distributed to their holders, each holder should be able to verify that all shares are collectively t-consistent (i.e., any subset t of n shares will yield the same, correct, polynomial without exposing the secret). In Shamir's secret sharing scheme the shares s 1 , s 2 , . . . , s n {\displaystyle s_{1},s_{2},...,s_{n}} are t-consistent if and only if the interpolation of the points ( 1 , s 1 ) , ( 2 , s 2 ) , . . . , (

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  • BREACH

    BREACH

    BREACH (a backronym: Browser Reconnaissance and Exfiltration via Adaptive Compression of Hypertext) is a security vulnerability against HTTPS when using HTTP compression. BREACH is built based on the CRIME security exploit. BREACH was announced at the August 2013 Black Hat USA conference by security researchers Angelo Prado, Neal Harris and Yoel Gluck. == Details == While the CRIME attack was presented as a general attack that could work effectively against a large number of protocols, only exploits against SPDY request compression and TLS compression were demonstrated and largely mitigated in browsers and servers. The CRIME exploits against HTTP compression has not been mitigated at all, even though the authors of CRIME have warned that this vulnerability might be even more widespread than SPDY and TLS compression combined. BREACH is an instance of the CRIME attack against HTTP compression—the use of gzip or DEFLATE data compression algorithms via the content-encoding option within HTTP by many web browsers and servers. Given this compression oracle, the rest of the BREACH attack follows the same general lines as the CRIME exploit, by performing an initial blind brute-force search to guess a few bytes, followed by divide-and-conquer search to expand a correct guess to an arbitrarily large amount of content. == Mitigation == BREACH exploits the compression in the underlying HTTP protocol. Therefore, turning off TLS compression makes no difference to BREACH, which can still perform a chosen-plaintext attack against the HTTP payload. As a result, clients and servers are either forced to disable HTTP compression completely (thus reducing performance), or to adopt workarounds to try to foil BREACH in individual attack scenarios, such as using cross-site request forgery (CSRF) protection. Another suggested approach is to disable HTTP compression whenever the referrer header indicates a cross-site request, or when the header is not present. This approach allows effective mitigation of the attack without losing functionality, only incurring a performance penalty on affected requests. Another approach is to add padding at the TLS, HTTP header, or payload level. Around 2013–2014, there was an IETF draft proposal for a TLS extension for length-hiding padding that, in theory, could be used as a mitigation against this attack. It allows the actual length of the TLS payload to be disguised by the insertion of padding to round it up to a fixed set of lengths, or to randomize the external length, thereby decreasing the likelihood of detecting small changes in compression ratio that is the basis for the BREACH attack. However, this draft has since expired without further action. A very effective mitigation is HTB (Heal-the-BREACH) that adds random-sized padding to compressed data, providing some variance in the size of the output contents. This randomness delays BREACH from guessing the correct characters in the secret token by a factor of 500 (10-byte max) to 500,000 (100-byte max). HTB protects all websites and pages in the server with minimal CPU usage and minimal bandwidth increase.

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