A Review of Voice-Base Person Identification: State-of-the-Art

Automated person identification and authentication systems are useful for national security, integrity of electoral processes, prevention of cybercrimes and many access control applications. This is a critical component of information and communication technology which is central to national development. The use of biometrics systems in identification is fast replacing traditional methods such as use of names, personal identification numbers codes, password, etc., since nature bestow individuals with distinct personal imprints and signatures. Different measures have been put in place for person identification, ranging from face, to fingerprint and so on. This paper highlights the key approaches and schemes developed in the last five decades for voice-based person identification systems. Voice-base recognition system has gained interest due to its non-intrusive technique of data acquisition and its increasing method of continually studying and adapting to the person’s changes. Information on the benefits and challenges of various biometric systems are also presented in this paper. The present and prominent voice-based recognition methods are discussed. It was observed that these systems application areas have covered intelligent monitoring, surveillance, population management, election forensics, immigration and border control

A context‐aware approach to defend against unauthorized reading and relay attacks in RFID systems

Radio frequency identification (RFID) systems are becoming increasingly ubiquitous in both public and private domains. However, because of the inherent weaknesses of underlying wireless radio communications, RFID systems are plagued with a wide variety of security and privacy threats. A large number of these threats arise because of the tag's promiscuous response to any reader requests. This renders sensitive tag information easily subject to unauthorized reading . Promiscuous tag response also incites different forms of relay attacks whereby a malicious colluding pair, relaying messages between a tag and a reader, can successfully impersonate the tag without actually possessing it. Because of the increasing ubiquity of RFID devices, there is a pressing need for the development of security primitives and protocols to defeat unauthorized reading and relay attacks. However, currently deployed or proposed solutions often fail to satisfy the constraints and requirements of the underlying RFID applications in terms of (one or more of) efficiency, security, and usability. This paper proposes a novel research direction, one that utilizes sensing technologies, to tackle the problems of unauthorized reading and relay attacks with a goal of reconciling the requirements of efficiency, security, and usability. The premise of the proposed work is based on a current technological advancement that enables many RFID tags with low‐cost sensing capabilities. The on‐board tag sensors will be used to acquire useful contextual information about the tag's environment (or its owner, or the tag itself). For defense against unauthorized reading and relay attacks, such context information can be leveraged in two ways. First, contextual information can be used to design context‐aware selective unlocking mechanisms so that tags can selectively respond to reader interrogations and thus minimize the likelihood of unauthorized reading and “ghost‐and‐leech” relay attacks. Second, contextual information can be used as a basis for context‐aware secure transaction verification to defend against special types of relay attacks involving malicious readers. Copyright © 2011 John Wiley & Sons, Ltd. This paper proposes a novel research direction, one that utilizes sensing technologies to tackle the challenging problems of unauthorized reading and relay attacks in radio frequency identification systems. First, contextual information is used to design context‐aware selective unlocking mechanisms, so that tags can selectively respond to reader interrogations and, thus, minimize the likelihood of unauthorized reading and “ghost‐and‐leech” relay attacks. Second, contextual information is used as a basis for context‐aware secure transaction verification to defend against special types of relay attacks involving malicious readers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109577/1/sec404.pd

Biometric identification

Image recognition is an information process implemented by some information converter (intelligent information channel, recognition system) having input and output. The input of the system is fed with information about the characteristics of the objects being presented. The output of the system displays information about which classes (generalized images) the recognized objects are assigned to. When creating and operating an automated system for pattern recognition, a number of problems are solved, while for different authors the formulations of these tasks, and the set itself, do not coincide, since it depends to a certain extent on the specific mathematical model on which this or that recognition system is based. This is the task of formalizing the domain, forming a training sample, learning the recognition system, reducing the dimensionality of space

Survey of Data Confidentiality and Privacy in the Cloud Computing Environment

The objective of this research is to develop a scheme for improving cloud data confidentiality. A considerable number of people are sharing data through third-party applications in the cloud computing environment. According to reviewed literature, it has been realized that data security and privacy were the key challenges to the wider adoption of cloud services with insider threats being the most prevalent. Similarly, our online survey indicated that 53.3% of the respondents citing insider breaches as the main threat to their organizational data. The survey also confirmed that data security and privacy is one of the greatest barriers to the adoption of cloud services in their organization. Noting the flaws of Attribute-Based Encryption (ABE) and Identity-based encryption (IBE), and with the growth of computing power, applications are constantly being developed which makes them vulnerable to attacks. Since data confidentiality is essential in the provision of information security in the cloud, this paper suggested the development and the deployment of a hybrid attribute-based re-encryption scheme, which is a scheme that bridges the ABE and IBE, to secure data in the cloud computing environment. Keywords: Encryption, Cloud Computing, Data, confidentiality, Privacy DOI: 10.7176/CEIS/11-5-03 Publication date:September 30th 2020

Cognitive Checkpoint: Emerging Technologies for Biometric-Enabled Watchlist Screening

This paper revisits the problem of individual risk assessment in the layered security model. It contributes to the concept of balancing security and privacy via cognitive-centric machine called an ’e-interviewer’. Cognitive checkpoint is a cyber-physical security frontier in mass-transit hubs that provides an automated screening using all types of identity (attributed, biometric, and biographical) from both physical and virtual worlds. We investigate how the development of the next generation of watchlist for rapid screening impacts a sensitive balancing mechanism between security and privacy. We identify directions of such an impact, trends in watchlist technologies, and propose ways to mitigate the potential risks

Decentralized nation, solving the web identity crisis

The web of today whether you prefer to call it web 2.0, web 3.0, web 5.0 or even the metaverse is at a critical stage of evolution and challenge, largely centered around its crisis of identity. Like teenagers who cannot assess properly their reason for being and do not seem ready to take responsibility for their actions, we are constantly blaming the very system we are trying to get away from. To truly realize the benefits from innovation and technology, this crisis has to be resolved, not just through tactical solutions but through developments that enhance the sustainability of the web and its benefits. Significant strides are being made in the evolution of digital services enabled by technology, regulation, and the sheer pace of societal change. The journey to the decentralized web is mirroring the convergence of the physical and digital worlds across all economies and is increasingly embracing the digital native world. Technology has provided the foundational platform for individuals and entities to create and manage wealth, potentially without the need for big institutions. Ironically, despite all of the advancements, we are still facing an unprecedented and increasing wealth gap. Clearly, the system is broken, not just around the edges but at the very core of the democratic underpinning of our society. In this whitepaper, we propose how artificial intelligence on blockchain can be used to generate a new class of identity through direct human computer interaction. We demonstrate how this, combined with new perspectives for sustaining community and governance embedded within the use of blockchain technology, will underpin a sustainable solution to protect identity, authorship and privacy at the same time while contributing to restore trust amongst members of a future decentralized nation and hence contribute to solving the web most significant identity crisis.Comment: 11 pages, 1 figur

Going beyond your personal learning network, using recommendations and trust through a multimedia question-answering service for decision-support: A case study in the healthcare.

Social learning networks enable the sharing, transfer and enhancement of knowledge in the workplace that builds the ground to exchange informal learning practices. In this work, three healthcare networks are studied in order to understand how to enable the building, maintaining and activation of new contacts at work and the exchange of knowledge between them. By paying close attention to the needs of the practitioners, we aimed to understand how personal and social learning could be supported by technological services exploiting social networks and the respective traces reflected in the semantics. This paper presents a case study reporting on the results of two co-design sessions and elicits requirements showing the importance of scaffolding strategies in personal and shared learning networks. Besides, the significance of these strategies to aggregate trust among peers when sharing resources and decision-support when exchanging questions and answers. The outcome is a set of design criteria to be used for further technical development for a social semantic question and answer tool. We conclude with the lessons learned and future work

Green strength optimization of injection molding proces for novel recycle binder system using Taguchi method

Metal injection molding is a worldwide technology that world use as a predominant method in manufacturing. Optimizing the injection molding process is critical in obtaining a good shape retention of green components and improving manufacturing processes itself. This research focuses on the injection molding optimization which correlated to a single response of green strength which implementing orthogonal array of Taguchi L9 (34). It involved the effect of four molding factors: injection temperature, mold temperature, injection pressure and injection speed, towards green strength. The significant levels and contribution to the variables of green strength are determined using the analysis of variance. Manual screening test is conducted in regards of identifying the appropriate level of each factors. The study demonstrated that injection temperature was the most influential factor contributes to the best green strength, followed by mold temperature, injection speed and injection pressure. The optimum condition for attaining optimal green strength was definitely by conducting injection molding at; 160 ºC of injection temperature, 40 ºC of mold temperature, 50 % of injection pressure and 50 % of injection speed. The confirmation experiment result is 15.5127 dB and it was exceeding minimum requirement of the optimum performance. This research reveals that the proposed approach can excellently solve the problem with minimal number of trials, without sacrificing the ability of evaluating the appropriate condition to achieve related response, which is green strength

Privacy in Biometric Systems

Biometrics are physiological and/or behavioral characteristics of a person that have been used to provide an automatic proof of identity in a growing list of applications including crime/terrorism fighting, forensics, access and border control, securing e-/m-commerce transactions and service entitlements. In recent years, a great deal of research into a variety of new and traditional biometrics has widened the scope of investigations beyond improving accuracy into mechanisms that deal with serious concerns raised about the potential misuse of collected biometric data. Despite the long list of biometrics’ benefits, privacy concerns have become widely shared due to the fact that every time the biometric of a person is checked, a trace is left that could reveal personal and confidential information. In fact, biometric-based recognition has an inherent privacy problem as it relies on capturing, analyzing, and storing personal data about us as individuals. For example, biometric systems deal with data related to the way we look (face, iris), the way we walk (gait), the way we talk (speaker recognition), the way we write (handwriting), the way we type on a keyboard (keystroke), the way we read (eye movement), and many more. Privacy has become a serious concern for the public as biometric systems are increasingly deployed in many applications ranging from accessing our account on a Smartphone or computer to border control and national biometric cards on a very large scale. For example, the Unique Identification Authority of India (UIDAI) has issued 56 million biometric cards as of January 2014 [1], where each biometric card holds templates of the 10 fingers, the two irises and the face. An essential factor behind the growing popularity of biometrics in recent years is the fact that biometric sensors have become a lot cheaper as well as easier to install and handle. CCTV cameras are installed nearly everywhere and almost all Smartphones are equipped with a camera, microphone, fingerprint scanner, and probably very soon, an iris scanner