Privacy-Preserving Biometric Authentication

Biometric-based authentication provides a highly accurate means of authentication without requiring the user to memorize or possess anything. However, there are three disadvantages to the use of biometrics in authentication; any compromise is permanent as it is impossible to revoke biometrics; there are significant privacy concerns with the loss of biometric data; and humans possess only a limited number of biometrics, which limits how many services can use or reuse the same form of authentication. As such, enhancing biometric template security is of significant research interest. One of the methodologies is called cancellable biometric template which applies an irreversible transformation on the features of the biometric sample and performs the matching in the transformed domain. Yet, this is itself susceptible to specific classes of attacks, including hill-climb, pre-image, and attacks via records multiplicity. This work has several outcomes and contributions to the knowledge of privacy-preserving biometric authentication. The first of these is a taxonomy structuring the current state-of-the-art and provisions for future research. The next of these is a multi-filter framework for developing a robust and secure cancellable biometric template, designed specifically for fingerprint biometrics. This framework is comprised of two modules, each of which is a separate cancellable fingerprint template that has its own matching and measures. The matching for this is based on multiple thresholds. Importantly, these methods show strong resistance to the above-mentioned attacks. Another of these outcomes is a method that achieves a stable performance and can be used to be embedded into a Zero-Knowledge-Proof protocol. In this novel method, a new strategy was proposed to improve the recognition error rates which is privacy-preserving in the untrusted environment. The results show promising performance when evaluated on current datasets

A Case of Sesame Seeds: Growing and Nurturing Credentials in the Face of Mimicry

The purpose of this paper is to put the study of mimicry on the information security research map. Mimicry in humans has received little scholarly attention. Sociologist Diego Gambetta has constructed a framework that enables reasoning about episodes of mimicry based on trust in signs. By looking at the problem of phishing the applicability of this framework to problems of mimicry in information security system was tested. It was found that while the framework offers valuable insights, it needs to be updated since the assumptions that it makes do not hold in practice. A new framework is proposed, built on the core ideas of Gambetta’s framework, and extended with results from a literature study of phishing and other sources. This framework has been used for finding possible solutions to problems in web browser interface design. Because the nature of authentication was found to be the observation of discriminatory signals the paper also discusses the ethical issues surrounding the use of credentials. We hope that this paper will help system designers in finding and choosing appropriate credentials for authentication. By using the proposed framework a system can be analysed for the presence of credentials that enable the discrimination between genuine users and impostors. The framework can also serve as a method for identifying the dynamics behind user verification of credentials. The two problems that the framework can help address are the impersonation of providers and the impersonation of users. Like much other security research the results of this paper can be misused by attackers. It is expected that the framework will be more useful for defenders than attackers, as it is of an analytical nature, and cannot be used directly in any attacks. Since this study is of an exploratory nature the findings of the study need to be verified through research with greater validity. The paper contains directions for further research

Context-aware multi-factor authentication

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia InformáticaAuthentication systems, as available today, are inappropriate for the requirements of ubiquitous, heterogeneous and large scale distributed systems. Some important limitations are: (i) the use of weak or rigid authentication factors as principal’s identity proofs, (ii) non flexibility to combine different authentication modes for dynamic and context-aware interaction criteria, (iii) not being extensible models to integrate new or emergent pervasive authentication factors and (iv) difficulty to manage the coexistence of multi-factor authentication proofs in a unified single sign-on solution. The objective of this dissertation is the design, implementation and experimental evaluation of a platform supporting multi-factor authentication services, as a contribution to overcome the above limitations. The devised platform will provide a uniform and flexible authentication base for multi-factor authentication requirements and context-aware authentication modes for ubiquitous applications and services. The main contribution is focused on the design and implementation of an extensible authentication framework model, integrating classic as well as new pervasive authentication factors that can be composed for different context-aware dynamic requirements. Flexibility criteria are addressed by the establishment of a unified authentication back-end, supporting authentication modes as defined processes and rules expressed in a SAML based declarative markup language. The authentication base supports an extended single sign-on system that can be dynamically tailored for multi-factor authentication policies, considering large scale distributed applications and according with ubiquitous interaction needs

Social, Private, and Trusted Wearable Technology under Cloud-Aided Intermittent Wireless Connectivity

There has been an unprecedented increase in the use of smart devices globally, together with novel forms of communication, computing, and control technologies that have paved the way for a new category of devices, known as high-end wearables. While massive deployments of these objects may improve the lives of people, unauthorized access to the said private equipment and its connectivity is potentially dangerous. Hence, communication enablers together with highly-secure human authentication mechanisms have to be designed.In addition, it is important to understand how human beings, as the primary users, interact with wearable devices on a day-to-day basis; usage should be comfortable, seamless, user-friendly, and mindful of urban dynamics. Usually the connectivity between wearables and the cloud is executed through the user’s more power independent gateway: this will usually be a smartphone, which may have potentially unreliable infrastructure connectivity. In response to these unique challenges, this thesis advocates for the adoption of direct, secure, proximity-based communication enablers enhanced with multi-factor authentication (hereafter refereed to MFA) that can integrate/interact with wearable technology. Their intelligent combination together with the connection establishment automation relying on the device/user social relations would allow to reliably grant or deny access in cases of both stable and intermittent connectivity to the trusted authority running in the cloud.The introduction will list the main communication paradigms, applications, conventional network architectures, and any relevant wearable-specific challenges. Next, the work examines the improved architecture and security enablers for clusterization between wearable gateways with a proximity-based communication as a baseline. Relying on this architecture, the author then elaborates on the social ties potentially overlaying the direct connectivity management in cases of both reliable and unreliable connection to the trusted cloud. The author discusses that social-aware cooperation and trust relations between users and/or the devices themselves are beneficial for the architecture under proposal. Next, the author introduces a protocol suite that enables temporary delegation of personal device use dependent on different connectivity conditions to the cloud.After these discussions, the wearable technology is analyzed as a biometric and behavior data provider for enabling MFA. The conventional approaches of the authentication factor combination strategies are compared with the ‘intelligent’ method proposed further. The assessment finds significant advantages to the developed solution over existing ones.On the practical side, the performance evaluation of existing cryptographic primitives, as part of the experimental work, shows the possibility of developing the experimental methods further on modern wearable devices.In summary, the set of enablers developed here for wearable technology connectivity is aimed at enriching people’s everyday lives in a secure and usable way, in cases when communication to the cloud is not consistently available

Implementation of Captcha as Graphical Passwords For Multi Security

To validate human users, passwords play a vital role in computer security. Graphical passwords offer more security than text-based passwords, this is due to the reason that the user replies on graphical passwords. Normal users choose regular or unforgettable passwords which can be easy to guess and are prone to Artificial Intelligence problems. Many harder to guess passwords involve more mathematical or computational complications. To counter these hard AI problems a new Captcha technology known as, Captcha as Graphical Password (CaRP), from a novel family of graphical password systems has been developed. CaRP is both a Captcha and graphical password scheme in one. CaRP mainly helps in hard AI problems and security issues like online guess attacks, relay attacks, and shoulder-surfing attacks if combined with dual view technologies. Pass-points, a new methodology from CaRP, addresses the image hotspot problem in graphical password systems which lead to weak passwords. CaRP also implements a combination of images or colors with text which generates session passwords, that helps in authentication because with session passwords every time a new password is generated and is used only once. To counter shoulder surfing, CaRP provides cheap security and usability and thus improves online security. CaRP is not a panacea; however, it gives protection and usability to some online applications for improving online security

Towards internet voting in the state of Qatar

Qatar is a small country in the Middle East which has used its oil wealth to invest in the country's infrastructure and education. The technology for Internet voting now exists or can be developed, but are the people of Qatar willing to take part in Internet voting for national elections?. This research identifies the willingness of government and citizens to introduce and participate in Internet voting (I-voting) in Qatar and the barriers that may be encountered when doing so. A secure I voting model for the Qatar government is then proposed that address issues of I-voting which might arise due to the introduction of such new technology. Recommendations are made for the Qatar government to assist in the introduction of I-voting. The research identifies the feasibility of I-voting and the government s readiness and willingness to introduce it. Multiple factors are examined: the voting experience, educational development, telecommunication development, the large number of Internet users, Qatar law which does not bar the use of I-voting and Qatar culture which supports I-voting introduction. It is shown that there is a willingness amongst both the people and the government to introduce I-voting, and there is appropriate accessibility, availability of IT infrastructure, availability of Internet law to protect online consumers and the existence of the e government project. However, many Qataris have concerns of security, privacy, usability, transparency and other issues that would need to be addressed before any voting system could be considered to be a quality system in the eyes of the voters. Also, the need to consider the security threat associated on client-side machines is identified where a lack of user awareness on information security is an important factor. The proposed model attempts to satisfy voting principles, introducing a secure platform for I-voting using best practices and solutions such as the smart card, Public Key Infrastructure (PKI) and digital certificates. The model was reviewed by a number of experts on Information Technology, and the Qatari culture and law who found that the system would, generally, satisfy voting principles, but pointed out the need to consider the scalability of the model, the possible cyber-attacks and the risks associated with voters computers. which could be reduced by enhancing user awareness on security and using secure operating systems or Internet browsers. From these findings, a set of recommendations were proposed to encourage the government to introduce I-voting which consider different aspects of I-voting, including the digital divide, e-literacy, I voting infrastructure, legal aspects, transparency, security and privacy. These recommendations were also reviewed by experts who found them to be both valuable and effective. Since literature on Internet voting in Qatar is sparse, empirical and non-empirical studies were carried out in a variety of surveys, interviews and experiments. The research successfully achieved its aim and objectives and is now being considered by the Qatari Government

Security and Privacy Attacks with and against Machine Learning

Both researchers and industry have increased their employ of machine learning in new applications with the unfaltering march of the Digital Revolution. However, without complete consideration of these rapid changes, undiscovered attack surfaces may remain open that allow bad actors to breach the security of the system, or leak sensitive information. In this work we shall investigate attacks with and against Machine Learning, starting in the application space of authentication which has observed the adoption of ML, before generalizing to any ML model application. We shall explore a multitude of attacks from ML-assisted behavioral side-channel Attacks against novel authentication systems, Random Input Attacks against the ML models of biometrics, to Membership and Attribute inference attacks against ML models which find employ in Authentication among a host of other sensitive applications. With any proposed attack, there is an obligation to define mitigation strategies. This advancement of knowledge in both attacks and defenses will make the ever-evolving landscape that is our digital world more hardy to external threats. However, in the constant arms race of security and privacy threats, the problem is far from complete, with iterative improvements to be sought on both attacks and defenses. Having not yet attained the perfect defense, they are currently flawed, paired with a tangible cost in either the usability or utility of the application. The necessity of these defenses cannot be understated with a looming threat of an attack, we also need to better understand the trade-offs required, if they are to be implemented. Specifically, we shall describe our successful efforts to rapidly recover a user's secret from observation resilient authentication schemes (ORAS), through behavioral side-channels. Explore the surprising effectiveness of uniform random inputs in breaching the security of behavioral biometric models. Dive deep into membership and attribute inference attacks to highlight the infeasibility of attribute inference due to the inability to perform strong membership inference, paired with a realigned definition of approximate attribute inference to better reflect the privacy risks of an attribute inference attacker. Finally evaluating the privacy-utility tradeoffs offered by differential privacy as a means to mitigate the prior membership and attribute inference attacks