Online at Will: A Novel Protocol for Mutual Authentication in Peer-to-Peer Networks for Patient-Centered Health Care Information Systems

Patient-centered health care information systems (PHSs) on peer-to-peer (P2P) networks promise decentralization benefits. P2P PHSs, such as decentralized personal health records or interoperable Covid-19 proximity trackers, can enhance data sovereignty and resilience to single points of failure, but the openness of P2P networks introduces new security issues. We propose a novel, simple, and secure mutual authentication protocol that supports offline access, leverages independent and stateless encryption services, and enables patients and medical professionals to establish secure connections when using P2P PHSs. Our protocol includes a virtual smart card (software-based) feature to ease integration of authentication features of emerging national health-IT infrastructures. The security evaluation shows that our protocol resists most online and offline threats while exhibiting performance comparable to traditional, albeit less secure, password-based authentication methods. Our protocol serves as foundation for the design and implementation of P2P PHSs that will make use of P2P PHSs more secure and trustworthy

INFINITY PAY

The present disclosure relates to the field of contactless payment systems and biometric authentication. More specifically, it relates to a novel system and method for enabling secure contactless payments using biometric identification, even in situations where the user\u27s primary device is unavailable. This innovative solution incorporates a combination of machine learning, neural networks, blockchain technology, and interconnected IoT devices to facilitate seamless and secure transactions

An enhanced secure delegation-based anonymous authentication protocol for PCSs

Rapid development of wireless networks brings about many security problems in portable communication systems (PCSs), which can provide mobile users with an opportunity to enjoy global roaming services. In this regard, designing a secure user authentication scheme, especially for recognizing legal roaming users, is indeed a challenging task. It is noticed that there is no delegation-based protocol for PCSs, which can guarantee anonymity, untraceability, perfect forward secrecy, and resistance of denial-of-service (DoS) attack. Therefore, in this article, we put forward a novel delegation-based anonymous and untraceable authentication protocol, which can guarantee to resolve all the abovementioned security issues and hence offer a solution for secure communications for PCSs

Hardware accelerated authentication system for dynamic time-critical networks

The secure and efficient operation of time-critical networks, such as vehicular networks, smart-grid and other smart-infrastructures, is of primary importance in today’s society. It is crucial to minimize the impact of security mechanisms over such networks so that the safe and reliable operations of time-critical systems are not being interfered. Even though there are several security mechanisms, their application to smart-infrastructure and Internet of Things (IoT) deployments may not meet the ubiquitous and time-sensitive needs of these systems. That is, existing security mechanisms either introduce a significant computation and communication overhead, or they are not scalable for a large number of IoT components. In particular, as a primary authentication mechanism, existing digital signatures cannot meet the real-time processing requirements of time-critical networks, and also do not fully benefit from advancements in the underlying hardware/software of IoTs. As a part of this thesis, we create a reliable and scalable authentication system to ensure secure and reliable operation of dynamic time-critical networks like vehicular networks through hardware acceleration. The system is implemented on System-On-Chips (SoC) leveraging the parallel processing capabilities of the embedded Graphical Processing Units (GPUs) along with the CPUs (Central Processing Units). We identify a set of cryptographic authentication mechanisms, which consist of operations that are highly parallelizable while still maintain high standards of security and are also secure against various malicious adversaries. We also focus on creating a fully functional prototype of the system which we call a “Dynamic Scheduler” which will take care of scheduling the messages for signing or verification on the basis of their priority level and the number of messages currently in the system, so as to derive maximum throughput or minimum latency from the system, whatever the requirement may be

Novel Physical Layer Authentication Techniques for Secure Wireless Communications

Due to the open nature of radio propagation, information security in wireless communications has been facing more challenges compared to its counterpart in wired networks. Authentication, defined as an important aspect of information security, is the process of verifying the identity of transmitters to prevent against spoofing attacks. Traditionally, secure wireless communications is achieved by relying solely upon higher layer cryptographic mechanisms. However, cryptographic approaches based on complex mathematical calculations are inefficient and vulnerable to various types of attacks. Recently, researchers have shown that the unique properties of wireless channels can be exploited for authentication enhancement by providing additional security protection against spoofing attacks. Motivated by the vulnerability of existing higher-layer security techniques and the security advantages provided by exploring the physical link properties, five novel physical layer authentication techniques to enhance the security performance of wireless systems are proposed. The first technique exploits the inherent properties of CIR to achieve robust channel-based authentication. The second and third techniques utilize a long-range channel predictor and additional multipath delay characteristics, respectively, to enhance the CIR-based authentication. The fourth technique exploits the advantages of AF cooperative relaying to improve traditional channel-based authentication. The last technique employs an embedded confidential signaling link to secure the legitimate transmissions in OFDM systems

SMS-based One-Time Passwords: Attacks and Defense

SMS-based One-Time Passwords (SMS OTP) were introduced to counter phishing and other attacks against Internet services such as online banking. Today, SMS OTPs are commonly used for authentication and authorization for many different applications. Recently, SMS OTPs have come under heavy attack, especially by smartphone trojans. In this paper, we analyze the security architecture of SMS OTP systems and study attacks that pose a threat to Internet-based authentication and authorization services. We determined that the two foundations SMS OTP is built on, cellular networks and mobile handsets, were completely different at the time when SMS OTP was designed and introduced. Throughout this work, we show why SMS OTP systems cannot be considered secure anymore. Based on our findings, we propose mechanisms to secure SMS OTPs against common attacks and specifically against smartphone trojans

ML-Based User Authentication Through Mouse Dynamics

Increasing reliance on digital services and the limitations of traditional authentication methods have necessitated the development of more advanced and secure user authentication methods. For user authentication and intrusion detection, mouse dynamics, a form of behavioral biometrics, offers a promising and non-invasive method. This paper presents a comprehensive study on ML-Based User Authentication Through Mouse Dynamics. This project proposes a novel framework integrating sophisticated techniques such as embeddings extraction using Transformer models with cutting-edge machine learning algorithms such as Recurrent Neural Networks (RNN). The project aims to accurately identify users based on their distinct mouse behavior and detect unauthorized access by utilizing the hybrid models. Using a mouse dynamics dataset, the proposed framework’s performance is evaluated, demonstrating its efficacy in accurately identifying users and detecting intrusions. In addition, a comparative analysis with existing methodologies is provided, highlighting the enhancements made by the proposed framework. This paper contributes to the development of more secure, reliable, and user-friendly authentication systems that leverage the power of machine learning and behavioral biometrics, ultimately augmenting the privacy and security of digital services and resources