Biometric data are extensively used in modern healthcare systems and is often transmitted over networks for various purposes, raising inherent privacy and security concerns. Wearable devices, smartphones, and Internet of Things (IoT) technologies are common sources of such data, which are susceptible to interception during transmission. To mitigate these risks, cancelable biometrics offer a promising solution by enabling secure and privacy-preserving identification. In this study, we propose a cancelable identification model based on contactless heart signals acquired via continuous-wave radar. The recorded signal, which reflects cardiac motion, is first transformed into a scalogram. Feature extraction is then performed using Convolutional Neural Networks (CNNs), comparing models trained via transfer learning with those trained solely on the dataset. Before classification, the extracted features are converted into cancelable templates using Gaussian Random Projection (GRP), and classification is performed using a Multilayer Perceptron (MLP). The proposed method demonstrates feasibility, achieving 91.20% accuracy across all scenarios in the dataset, which increases to 95.40% when focusing solely on the resting scenario. Additionally, CNNs trained exclusively on the dataset outperform pre-trained models using transfer learning in feature extraction performance.

The present work aims to address key security vulnerabilities in Vehicular Ad Hoc Networks (VANETs) through an enhanced authentication scheme. This study evaluates the effectiveness of utilizing Elliptic Curve Cryptography (ECC) for improving security efficiency and compares it with conventional techniques used in state-of-the-art authentication protocols. The results demonstrate improvements in both computational and communication efficiency. A rigorous formal analysis using the Tamarin Prover confirms the robustness of the proposed security processes. Real-world implementation of the proposed protocol using Raspberry Pi devices is conducted and empirical performance tests using NS-3 (Network Simulator 3) show a 30% improvement in computational efficiency and a 25% reduction in authentication delay compared to conventional techniques, along with a 98% success rate in evading impersonation attacks and a 95% success rate in preventing replay attacks while maintaining similar efficiency levels.

This groundbreaking study investigates the detection of atrial fibrillation (AF) using short photoplethysmography (PPG) traces. Drawing inspiration from both cardiologists’ methods of listening to cardiac activity and the characterization of musical recordings (timbre, pitch, and scalograms), we extract musical features from the cardiac PPG recordings. By employing this innovative approach and validating the results using the MIMIC-PERform dataset, a hand-crafted approach achieves up to 89% accuracy, while a convolutional neural network with an attention module (CBAM) achieves up to 95% accuracy. These results are comparable to solutions with FDA clearance approval, but with the added advantage of using shortened traces. The findings demonstrate the feasibility of using short PPG signal recordings for AF detection and highlight the universal nature of this solution compared to more expensive alternatives that rely on ECG signals.

Random numbers play a key role in applications such as industrial simulations, laboratory experimentation, computer games, and engineering problem solving. The design of new true random generators (TRNGs) has attracted the attention of the research community for many years. Designs with little hardware requirements and high throughput are demanded by new and powerful applications. In this paper, we introduce the design of a novel TRNG based on the coherent sampling (CS) phenomenon. Contrary to most designs based on this phenomenon, ours uses self-timed rings (STRs) instead of the commonly employed ring oscillators (ROs). Our design has two key advantages over existing proposals based on CS. It does not depend on the FPGA vendor used and does not need manual placement and routing in the manufacturing process, resulting in a highly portable generator. Our experiments show that the TRNG offers a very high throughput with a moderate cost in hardware. The results obtained with ENT, DIEHARD, and National Institute of Standards and Technology (NIST) statistical test suites evidence that the output bitstream behaves as a truly random variable.

Abstract The Internet of Things is an emerging paradigm, which is used to link physical objects with Internet. One of the most common ways of communicating and identifying objects on Internet of Things is using Radio Frequency IDentification (RFID) systems between different objects. Researchers have focused on developing improvements of RFID authentication protocols that stave off privacy threats and well‐known security problems. Recently, Khor et al. have proposed a new authentication protocol that conforms to the Electronic Product Code Class‐1 Generation‐2 standard (ISO/IEC 18000‐6C for RFID systems). In this paper, we show the vulnerabilities of this authentication protocol concerning to full disclosure, impersonation, traceability, de‐synchronization, and Denial‐of‐Service attacks. These attacks make the protocol unfeasible to introduce it with an adequate security and sufficient privacy protection level. Finally, we present a new protocol, called Fingerprint+ protocol, which is based on ISO/IEC 9798‐2 and ISO/IEC 18000‐6C and whose security is formally verified using BAN logic. Copyright © 2014 John Wiley & Sons, Ltd.

Abstract Radio frequency identification (RFID) is a powerful technology that enables wireless information storage and control in an economical way. These properties have generated a wide range of applications in different areas. Due to economic and technological constrains, RFID devices are seriously limited, having small or even tiny computational capabilities. This issue is particularly challenging from the security point of view. Security protocols in RFID environments have to deal with strong computational limitations, and classical protocols cannot be used in this context. There have been several attempts to overcome these limitations in the form of new lightweight security protocols designed to be used in very constrained (sometimes called ultra‐lightweight) RFID environments. One of these proposals is the David–Prasad ultra‐lightweight authentication protocol. This protocol was successfully attacked using a cryptanalysis technique named Tango attack. The capacity of the attack depends on a set of boolean approximations. In this paper, we present an enhanced version of the Tango attack, named Genetic Tango attack, that uses Genetic Programming to design those approximations, easing the generation of automatic cryptanalysis and improving its power compared to a manually designed attack. Experimental results are given to illustrate the effectiveness of this new attack.

ABSTRACT Tian et al. proposed a novel ultralightweight RFID mutual authentication protocol [1] that has recently been analyzed in several articles. In this letter, we first propose a desynchronization attack that succeeds with probability almost 1, which improves upon the 0.25 given in a previous analysis by Ahmadian et al. We also show that the bad properties of the proposed permutation function can be exploited to disclose several bits of the tag's secret (rather than just 1 bit as previously shown by Avoine et al.), which increases the power of a traceability attack. Finally, we show how to extend the aforementioned attack to run a full disclosure attack, which requires to eavesdrop less protocol runs than the proposed attack by Wang et al. (i.e., 192 < < 2 30). Copyright © 2013 John Wiley & Sons, Ltd.

In resource-constrained devices such as RFID tags or implantable medical devices, algorithm designers need to make careful choices to ensure that their proposals are sufficiently efficient for the target platform. A common way of expressing such restrictions is in terms of an upper bound for the maximum available footprint area in gate equivalents (GE). For example, RFID tags conforming to standards EPC Class-1 Generation-2 and ISO/IEC 18000-6C can devote up to 4K GE to security functions. However, in most cases, algorithm designers are not hardware experts, nor they have any quantitative means to find out how much area their designs would occupy in a given technology. In this paper, we attempt to fill this gap by providing an estimate of the upper bound for the footprint area of any algorithm. Our approach takes into account the main components of such algorithms, namely, basic arithmetic/logic operations and additional hardware such as registers and multiplexers. We believe that our proposal can help designers in making informed decisions about what kind of algorithmic structures can be afforded for a target environment.

Distance-bounding protocols form a family of challenge–response authentication protocols that have been introduced to thwart relay attacks. They enable a verifier to authenticate and to establish an upper bound on the physical distance to an untrusted prover. We provide a detailed security analysis of a family of such protocols. More precisely, we show that the secret key shared between the verifier and the prover can be leaked after a number of nonce repetitions. The leakage probability, while exponentially decreasing with the nonce length, is only weakly dependent on the key length. Our main contribution is a high probability bound on the number of sessions required for the attacker to discover the secret, and an experimental analysis of the attack under noisy conditions. Both of these show that the attack's success probability mainly depends on the length of the used nonces rather than the length of the shared secret key. The theoretical bound could be used by practitioners to appropriately select their security parameters. While longer nonces can guard against this type of attack, we provide a possible countermeasure which successfully combats these attacks even when short nonces are used.

Secure and energy-efficient communication between Implantable Medical Devices (IMDs) and authorized external users is attracting increasing attention these days. However, there currently exists no systematic approach to the problem, while solutions from neighboring fields, such as wireless sensor networks, are not directly transferable due to the peculiarities of the IMD domain. This work describes an original, efficient solution for secure IMD communication. A new implant system architecture is proposed, where security and main-implant functionality are made completely decoupled by running the tasks onto two separate cores. Wireless communication goes through a custom security ASIP, called SISC (Smart-Implant Security Core), which runs an energy-efficient security protocol. The security core is powered by RF-harvested energy until it performs external-reader authentication, providing an elegant defense mechanism against battery Denial-of-Service (DoS) and other, more common attacks. The system has been evaluated based on a realistic case study involving an artificial pancreas implant. When synthesized for a UMC 90nm CMOS ASIC technology, our system architecture achieves defense against unauthorized accesses having zero energy cost , running entity authentication through harvesting only 7.45μ J of RF energy from the requesting entity. In all other successfully authenticated accesses, our architecture achieves secure data exchange without affecting the performance of the main IMD functionality, adding less than 1‰ (1.3 mJ ) to the daily energy consumption of a typical implant. Compared to a singe-core, secure reference IMD, which would still be more vulnerable to some types of attacks, our secure system on chip (SoC) achieves high security levels at 56% energy savings and at an area overhead of less than 15%.

The design of a secure RFID identification scheme is a thought-provoking challenge, and this paper deals with this problem adopting a groundbreaking approach. The proposed protocol, called Noent, is based on cryptographic puzzles to avoid the indiscriminate disclose of the confidential information stored on tags and on an innovative role reversal distance-bounding protocol to distinguish between honest and rogue readers. The protocol provides moderate privacy protection (data and location) to single tags but its effectiveness increases hugely when it is used to protect a large population of tags (e.g., protection against inventory disclosure). Moreover, in comparison with classical approaches, Noent does not require an on-line database, which facilitates key updating and mitigates desynchronization attacks.

In order to obtain more secure and reliable systems, the vast majority of RFID protocols include a Pseudorandom Number Generator (PRNG) in its design. However, the authors often do not specify the PRNG to use and standard solutions exceed the capabilities of low-cost RFID tags. In this paper, we propose two lightweight PRNGs (AKARI-1 and AKARI-2) that meet the requirements of these systems while improving their reliability and security. They may be supported on commercial tags of low price.

We present a metaheuristic-based attack against the traceability of an ultra-lightweight authentication protocol for RFID environments called SLMAP, and analyse its implications. The main interest of our approach is that it is a complete black-box technique that doesn't make any assumptions on the components of the underlying protocol and can thus be easily generalised to analyse many other proposals.