The Horcrux Protocol: A Method for Decentralized Biometric-based Self-sovereign Identity

Most user authentication methods and identity proving systems rely on a centralized database. Such information storage presents a single point of compromise from a security perspective. If this system is compromised it poses a direct threat to users' digital identities. This paper proposes a decentralized authentication method, called the Horcrux protocol, in which there is no such single point of compromise. The protocol relies on decentralized identifiers (DIDs) under development by the W3C Verifiable Claims Community Group and the concept of self-sovereign identity. To accomplish this, we propose specification and implementation of a decentralized biometric credential storage option via blockchains using DIDs and DID documents within the IEEE 2410-2017 Biometric Open Protocol Standard (BOPS)

Increasing resilience in privileged access management

This Master of Science in Technology thesis, developed in collaboration with a target company, focuses on increasing resilience and disaster recovery planning for a privileged access management tool. The research was conducted using online sources and supplemented by available frameworks and best practices while working for the target organization. The thesis explorers several critical questions regarding privileged access rights: their nature, necessity to secure them, appropriate protection mechanisms, and ensuring the resilience of the protection mechanisms during potential disaster recovery scenarios. The research adopts design science research methodology, commencing with a literature review of identity and access management. The thesis progresses by identifying and assessing possible threat, incident and disaster scenarios for privileged access. The research then presents the most relevant scenarios and solution to enable resilience through high availability. The solutions is then evaluated. The research culminates in a conclusion that answers the set research questions

The Android Platform Security Model

Android is the most widely deployed end-user focused operating system. With its growing set of use cases encompassing communication, navigation, media consumption, entertainment, finance, health, and access to sensors, actuators, cameras, or microphones, its underlying security model needs to address a host of practical threats in a wide variety of scenarios while being useful to non-security experts. The model needs to strike a difficult balance between security, privacy, and usability for end users, assurances for app developers, and system performance under tight hardware constraints. While many of the underlying design principles have implicitly informed the overall system architecture, access control mechanisms, and mitigation techniques, the Android security model has previously not been formally published. This paper aims to both document the abstract model and discuss its implications. Based on a definition of the threat model and Android ecosystem context in which it operates, we analyze how the different security measures in past and current Android implementations work together to mitigate these threats. There are some special cases in applying the security model, and we discuss such deliberate deviations from the abstract model

A Survey of PPG's Application in Authentication

Biometric authentication prospered because of its convenient use and security. Early generations of biometric mechanisms suffer from spoofing attacks. Recently, unobservable physiological signals (e.g., Electroencephalogram, Photoplethysmogram, Electrocardiogram) as biometrics offer a potential remedy to this problem. In particular, Photoplethysmogram (PPG) measures the change in blood flow of the human body by an optical method. Clinically, researchers commonly use PPG signals to obtain patients' blood oxygen saturation, heart rate, and other information to assist in diagnosing heart-related diseases. Since PPG signals contain a wealth of individual cardiac information, researchers have begun to explore their potential in cyber security applications. The unique advantages (simple acquisition, difficult to steal, and live detection) of the PPG signal allow it to improve the security and usability of the authentication in various aspects. However, the research on PPG-based authentication is still in its infancy. The lack of systematization hinders new research in this field. We conduct a comprehensive study of PPG-based authentication and discuss these applications' limitations before pointing out future research directions.Comment: Accepted by Computer & Security (COSE

A review of multi-factor authentication in the internet of healthcare things

Objective: This review paper aims to evaluate existing solutions in healthcare authentication and provides an insight into the technologies incorporated in Internet of Healthcare Things (IoHT) and multi-factor authentication (MFA) applications for next-generation authentication practices. Our review has two objectives: (a) Review MFA based on the challenges, impact and solutions discussed in the literature; and (b) define the security requirements of the IoHT as an approach to adapting MFA solutions in a healthcare context. Methods: To review the existing literature, we indexed articles from the IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink databases. The search was refined to combinations of ‘authentication’, ‘multi-factor authentication’, ‘Internet of Things authentication’, and ‘medical authentication’ to ensure that the retrieved journal articles and conference papers were relevant to healthcare and Internet of Things-oriented authentication research. Results: The concepts of MFA can be applied to healthcare where security can often be overlooked. The security requirements identified result in stronger methodologies of authentication such as hardware solutions in combination with biometric data to enhance MFA approaches. We identify the key vulnerabilities of weaker approaches to security such as password use against various cyber threats. Cyber threats and MFA solutions are categorised in this paper to facilitate readers’ understanding of them in healthcare domains. Conclusions: We contribute to an understanding of up-to-date MFA approaches and how they can be improved for use in the IoHT. This is achieved by discussing the challenges, benefits, and limitations of current methodologies and recommendations to improve access to eHealth resources through additional layers of security

Activity-Aware Electrocardiogram-based Passive Ongoing Biometric Verification

Identity fraud due to lost, stolen or shared information or tokens that represent an individual\u27s identity is becoming a growing security concern. Biometric recognition - the identification or verification of claimed identity, shows great potential in bridging some of the existing security gaps. It has been shown that the human Electrocardiogram (ECG) exhibits sufficiently unique patterns for use in biometric recognition. But it also exhibits significant variability due to stress or activity, and signal artifacts due to movement. In this thesis, we develop a novel activity-aware ECG-based biometric recognition scheme that can verify/identify under different activity conditions. From a pattern recognition standpoint, we develop algorithms for preprocessing, feature extraction and probabilistic classification. We pay particular attention to the applicability of the proposed scheme in ongoing biometric verification of claimed identity. Finally we propose a wearable prototype architecture of our scheme

Continuous touchscreen biometrics: authentication and privacy concerns

In the age of instant communication, smartphones have become an integral part of our daily lives, with a significant portion of the population using them for a variety of tasks such as messaging, banking, and even recording sensitive health information. However, the increasing reliance on smartphones has also made them a prime target for cybercriminals, who can use various tactics to gain access to our sensitive data. In light of this, it is crucial that individuals and organisations prioritise the security of their smartphones to protect against the abundance of threats around us. While there are dozens of methods to verify the identity of users before granting them access to a device, many of them lack effectiveness in terms of usability and potential vulnerabilities. In this thesis, we aim to advance the field of touchscreen biometrics which promises to alleviate some of the recurring issues. This area of research deals with the use of touch interactions, such as gestures and finger movements, as a means of identifying or authenticating individuals. First, we provide a detailed explanation of the common procedure for evaluating touch-based authentication systems and examine the potential pitfalls and concerns that can arise during this process. The impact of the pitfalls is evaluated and quantified on a newly collected large-scale dataset. We also discuss the prevalence of these issues in the related literature and provide recommendations for best practices when developing continuous touch-based authentication systems. Then we provide a comprehensive overview of the techniques that are commonly used for modelling touch-based authentication, including the various features, classifiers, and aggregation methods that are employed in this field. We compare the approaches under controlled, fair conditions in order to determine the top-performing techniques. Based on our findings, we introduce methods that outperform the current state-of-the-art. Finally, as a conclusion to our advancements in the development of touchscreen authentication technology, we explore any negative effects our work may cause to an ordinary user of mobile websites and applications. In particular, we look into any threats that can affect the privacy of the user, such as tracking them and revealing their personal information based on their behaviour on smartphones

A user-centric privacy-preserving authentication protocol for IoT-AmI environments

Ambient Intelligence (AmI) in Internet of Things (IoT) has empowered healthcare professionals to monitor, diagnose, and treat patients remotely. Besides, the AmI-IoT has improved patient engagement and gratification as doctors’ interactions have become more comfortable and efficient. However, the benefits of the AmI-IoT-based healthcare applications are not availed entirely due to the adversarial threats. IoT networks are prone to cyber attacks due to vulnerable wireless mediums and the absentia of lightweight and robust security protocols. This paper introduces computationally-inexpensive privacy-assuring authentication protocol for AmI-IoT healthcare applications. The use of blockchain & fog computing in the protocol guarantees unforgeability, non-repudiation, transparency, low latency, and efficient bandwidth utilization. The protocol uses physically unclonable functions (PUF), biometrics, and Ethereum powered smart contracts to prevent replay, impersonation, and cloning attacks. Results prove the resource efficiency of the protocol as the smart contract incurs very minimal gas and transaction fees. The Scyther results validate the robustness of the proposed protocol against cyber-attacks. The protocol applies lightweight cryptography primitives (Hash, PUF) instead of conventional public-key cryptography and scalar multiplications. Consequently, the proposed protocol is better than centralized infrastructure-based authentication approaches