In this paper we consider authentication at the physical layer, in which the authenticator aims at distinguishing a legitimate supplicant from an attacker on the basis of the characteristics of a set of parallel wireless channels, which are affected by time-varying fading. Moreover, the attacker's channel has a spatial correlation with the supplicant's one. In this setting, we assess and compare the performance achieved by different approaches under different channel conditions. We first consider the use of two different statistical decision methods, and we prove that using a large number of references (in the form of channel estimates) affected by different levels of time-varying fading is not beneficial from a security point of view. We then consider classification methods based on machine learning. In order to face the worst case scenario of an authenticator provided with no forged messages during training, we consider one-class classifiers. When instead the training set includes some forged messages, we resort to more conventional binary classifiers, considering the cases in which such messages are either labelled or not. For the latter case, we exploit clustering algorithms to label the training set. The performance of both nearest neighbor (NN) and support vector machine (SVM) classification techniques is evaluated. Through numerical examples, we show that under the same probability of false alarm, one-class classification (OCC) algorithms achieve the lowest probability of missed detection when a small spatial correlation exists between the main channel and the adversary one, while statistical methods are advantageous when the spatial correlation between the two channels is large.
In this paper we assess the security performance of key-less physical layer authentication schemes in the case of time-varying fading channels, considering both partial and no channel state information (CSI) on the receiver's side. We first present a generalization of a well-known protocol previously proposed for flat fading channels and we study different statistical decision methods and the corresponding optimal attack strategies in order to improve the authentication performance in the considered scenario. We then consider the application of machine learning techniques in the same setting, …
In this paper, facts existing in different domains are explored, which are comparable by their end result. Properties of various domains and the facts that are part of such a unit are also presented, examples of comparison and methods of usage as means of zero-knowledge protocols are given, finally a zero-knowledge protocol based on afore-mentioned concept is given.
Conventional block-based multicast authentication schemes overlook the heterogeneity of receivers by letting the sender choose the block size, divide a multicast stream into blocks, associate each block with a signature, and spread the effect of the signature across all the packets in the block through hash graphs or coding algorithms. The correlation among packets makes them vulnerable to packet loss, which is inherent in the Internet and wireless networks. Moreover, the lack of Denial of Service (DoS) resilience renders most of them vulnerable to packet injection in hostile environments. In …
Wireless Sensor Networks (WSN) are becoming popular day by day, however one of the main issue in WSN is its limited resources. We have to look to the resources to create Message Authentication Code (MAC) keeping in mind the feasibility of technique used for the sensor network at hand. This research work investigates different cryptographic techniques such as symmetric key cryptography and asymmetric key cryptography. Furthermore, it compares different encryption techniques such as stream cipher (RC4), block cipher (RC2, RC5, RC6 etc) and hashing techniques (MD2, MD4, MD5, SHA, SHA1 etc). The r…
Many different approaches for neural network based hash functions have been proposed. Statistical analysis must correlate security of them. This paper proposes novel neural hashing approach for gray scale image authentication. The suggested system is rapid, robust, useful and secure. Proposed hash function generates hash values using neural network one-way property and non-linear techniques. As a result security and performance analysis are performed and satisfying results are achieved. These features are dominant reasons for preferring against traditional ones.
In this paper, we present a comprehensive survey of authentication protocols for Internet of Things (IoT). Specifically, we select and in-detail examine more than forty authentication protocols developed for or applied in the context of the IoT under four environments, including: (1) Machine to machine communications (M2M), (2) Internet of Vehicles (IoV), (3) Internet of Energy (IoE), and (4) Internet of Sensors (IoS). We start by reviewing all survey articles published in the recent years that focusing on different aspects of the IoT idea. Then, we review threat models, countermeasures, and f…
Performance of the existing physical layer authentication schemes could be severely affected by the imperfect estimates and variations of the communication link attributes used. The commonly adopted static hypothesis testing for physical layer authentication faces significant challenges in time-varying communication channels due to the changing propagation and interference conditions, which are typically unknown at the design stage. To circumvent this impediment, we propose an adaptive physical layer authentication scheme based on machine-learning as an intelligent process to learn and utilize…
For a physical layer message authentication procedure based on the comparison of channel estimates obtained from the received messages, we focus on an outer bound on the type I/II error probability region. Channel estimates are modelled as multivariate Gaussian vectors, and we assume that the attacker has only some side information on the channel estimate, which he does not know directly. We derive the attacking strategy that provides the tightest bound on the error region, given the statistics of the side information. This turns out to be a zero mean, circularly symmetric Gaussian density who…
Lightweight and low latency security schemes at the physical layer that have recently attracted a lot of attention include: (i) physical unclonable functions (PUFs), (ii) localization based authentication, and, (iii) secret key generation (SKG) from wireless fading coefficients. In this paper, we focus on short blocklengths and propose a fast, privacy preserving, multi-factor authentication protocol that uniquely combines PUFs, proximity estimation and SKG. We focus on delay constrained applications and demonstrate the performance of the SKG scheme in the short blocklength by providing a numer…
Android's graphical password unlock remains one of the most widely used schemes for phone unlock authentication, and it is has been studied extensively in the last decade since its launch. We have learned that users' choice of patterns mimics the poor password choices in other systems, such as PIN or text-based passwords. A wide variety of analysis and data collections methods was used to reach these conclusions, but what is missing from the literature is a systemized comparison of the related work in this space that compares both the methodology and the results. In this paper, we take a detai…
In vehicular communications, in-vehicle devices' mobile and multihoming characteristics bring new requirements for devicevsecurity authentication. On the one hand, the existing network layer authentication methods rely on the PKI system; on the other hand, key negotiation needs interaction. These two points determine that the traditional security authentication method requires bandwidth consumption and additional delay. It is unsuitable for heterogeneous wireless scenarios with a high packet loss rate and limited bandwidth resources. In addition, the establishment of a security association sta…
This paper proposes to exploit the so-called {\it reciprocity parameters} (modelling non-reciprocal communication hardware) to use them as decision metric for binary hypothesis testing based authentication framework at a receiver node Bob. Specifically, Bob first learns the reciprocity parameters of the legitimate sender Alice via initial training. Then, during the test phase, Bob first obtains a measurement of reciprocity parameters of channel occupier (Alice, or, the intruder Eve). Then, with ground truth and current measurement both in hand, Bob carries out the hypothesis testing to automat…
While the literature on RF fingerprinting-based authentication and key distillation is vast, the two topics have customarily been studied separately. In this paper, starting from the observation that the wireless channel is a composite, deterministic / stochastic process, we propose a power domain decomposition that allows performing the two tasks simultaneously. We devise intelligent pre-processing schemes to decompose channel state information (CSI) observation vectors into "predictable" and "unpredictable" components. The former, primarily due to large-scale fading, can be used for node aut…
In this paper, a new approach to Spread Spectrum (SS) watermarking technique is introduced. This problem is particularly interesting in the field of modern multimedia applications like internet when copyright protection of digital image is required. The approach exploits two-predecessor single attractor (TPSA) cellular automata (CA) suitability to work as efficient authentication function in wavelet based SS watermarking domain. The scheme is designed from the analytical study of state transition behaviour of non-group CA and the basic cryptography/encryption scheme is significantly different …
The Internet of Things (IoT) is giving a boost to a plethora of new opportunities for the robust and sustainable deployment of cyber physical systems. The cornerstone of any IoT system is the sensing devices. These sensing devices have considerable resource constraints, including insufficient battery capacity, CPU capability, and physical security. Because of such resource constraints, designing lightweight cryptographic protocols is an opportunity. Remote User Authentication ensures that two parties establish a secure and durable session key. This study presents a lightweight and safe authent…
This paper focuses on how touch interactions on smartphones can provide a continuous user authentication service through behaviour captured by a touchscreen. While efforts are made to advance touch-based behavioural authentication, researchers often focus on gathering data, tuning classifiers, and enhancing performance by evaluating touch interactions in a sequence rather than independently. However, such systems only work by providing data representing distinct behavioural traits. The typical approach separates behaviour into touch directions and creates multiple user profiles. This work pres…
The field of touch-based authentication has been rapidly developing over the last decade, creating a fragmented and difficult-to-navigate area for researchers and application developers alike due to the variety of methods investigated. In this study, we perform a systematic literature analysis of 30 studies on the techniques used for feature extraction, classification, and aggregation in touch-based authentication systems as well as the performance metrics reported by each study. Based on our findings, we design a set of experiments to compare the performance of the most frequently used techni…
Nowadays, there is an increasing interest in the development of Autonomous Vehicles (AV). However, there are two types of attack challenges that can affect AVs and are yet to be resolved, i.e., sensor attacks and vehicle access attacks. This paper, to the best of our knowledge, is the first work that proposes a novel authentication scheme involving DRAM power-up unique features using deep Convolutional Neural Network (CNN), which can be used to implement secure access control of autonomous vehicles. Our approach consists of two parts. First, we convert raw power-up sequence data from DRAM cell…
Physical unclonable function (PUF) has been proposed as a promising and trustworthy solution to a variety of cryptographic applications. Here we propose a non-imaging based authentication scheme for optical PUFs materialized by random scattering media, in which the characteristic fingerprints of optical PUFs are extracted from stochastical fluctuations of the scattered light intensity with respect to laser challenges which are detected by a single-pixel detector. The randomness, uniqueness, unpredictability, and robustness of the extracted fingerprints are validated to be qualified for real au…
Digital authentication is a mature field, offering a range of solutions with rigorous mathematical guarantees. Nevertheless, paper documents, where cryptographic techniques are not directly applicable, are still widely utilized due to usability and legal reasons. We propose a novel approach to authenticating paper documents using smartphones by taking short videos of them. Our solution combines cryptographic and image comparison techniques to detect and highlight subtle semantic-changing attacks on rich documents, containing text and graphics, that could go unnoticed by humans. We rigorously a…
Information security is of great importance for modern society with all things connected. Physical unclonable function (PUF) as a promising hardware primitive has been intensively studied for information security. However, the widely investigated silicon PUF with low entropy is vulnerable to various attacks. Herein, we introduce a concept of bionic optical PUFs inspired from unique biological architectures, and fabricate four types of bionic PUFs by molding the surface micro-nano structures of natural plant tissues with a simple, low-cost, green and environmentally friendly manufacturing proce…
Hash chains provide a secure and light way of security to data authentication including two aspects: Data Integrity and Data Origin Authentication. The real challenge of using the hash chains is how it could recover the synchronization state and continue keeping the hash link in case of packet loss? Based on the packet loss tolerance and some accepted delay of video delivery which are representing the permitted tolerance for heavy loaded applications, we propose different mechanisms for such synchronization recovery. Each mechanism is suitable to use according to the video use case and the low…
In this paper a DWT based steganography in frequency domain, termed as ATFDWT has been proposed. Here, the cover image is transformed into the time domain signal through DWT, resulting four sub-image components as 'Low resolution', 'Horizontal orientation', 'Vertical orientation' and 'Diagonal orientation'. The secret message/image bits stream in varying positions are embedded in 'Vertical orientation sub-image' followed by reverse transformation to generate embedded/encrypted image. The decoding is done through the reverse procedure. The experimental results against statistical and visual att…
We propose an extension to the so-called PD detector. The PD detector jointly monitors received power and correlation profile distortion to detect the presence of GNSS carry-off-type spoofing, jamming, or multipath. We show that classification performance can be significantly improved by replacing the PD detector's symmetric-difference-based distortion measurement with one based on the post-fit residuals of the maximum-likelihood estimate of a single-signal correlation function model. We call the improved technique the PD-ML detector. In direct comparison with the PD detector, the PD-ML detect…
Optimizing Mouse Dynamics for User Authentication by Machine Learning: Addressing Data Sufficiency, Accuracy-Practicality Trade-off, and Model Performance Challenges
The University of Tokyo（东京大学）；Wuhan, China（中国武汉）；Xi’an Jiaotong Univeristy（西安交通大学）；Beijing, China（中国北京）
提出基于 KDE 与 KL 散度的数据量估计、MAU 片段优化及 LT-AMouse 框架，在 Balabit 和 DFL 上以更少数据实现优于 sota 的鼠标动力学认证。
Due to the diverse and mobile nature of the deployment environment, smart commodity devices are vulnerable to various attacks which can grant unauthorized access to a rogue device in a large, connected network. Traditional digital signature-based authentication methods are vulnerable to key recovery attacks, CSRF, etc. To circumvent this, RF-PUF had been proposed as a promising alternative that utilizes the inherent nonidealities of the devices as physical signatures. RF-PUF offers a robust authentication method that is resilient to key-hacking methods due to the absence of secret key requirem…
As the demand for highly secure and dependable lightweight systems increases in the modern world, Physically Unclonable Functions (PUFs) continue to promise a lightweight alternative to high-cost encryption techniques and secure key storage. While the security features promised by PUFs are highly attractive for secure system designers, they have been shown to be vulnerable to various sophisticated attacks - most notably Machine Learning (ML) based modelling attacks (ML-MA) which attempt to digitally clone the PUF behaviour and thus undermine their security. More recent ML-MA have even exploite…
Observation Resilient Authentication Schemes (ORAS) are a class of shared secret challenge-response identification schemes where a user mentally computes the response via a cognitive function to authenticate herself such that eavesdroppers cannot readily extract the secret. Security evaluation of ORAS generally involves quantifying information leaked via observed challenge-response pairs. However, little work has evaluated information leaked via human behavior while interacting with these schemes. A common way to achieve observation resilience is by including a modulus operation in the cogniti…
With the rapid advancement of technology, different biometric user authentication, and identification systems are emerging. Traditional biometric systems like face, fingerprint, and iris recognition, keystroke dynamics, etc. are prone to cyber-attacks and suffer from different disadvantages. Electroencephalography (EEG) based authentication has shown promise in overcoming these limitations. However, EEG-based authentication is less accurate due to signal variability at different psychological and physiological conditions. On the other hand, keystroke dynamics-based identification offers high a…
We propose the formal study of governed blockchains that are owned and controlled by organizations and that neither create cryptocurrencies nor provide any incentives to solvers of cryptographic puzzles. We view such approaches as frameworks in which system parts, such as the cryptographic puzzle, may be instantiated with different technology. Owners of such a blockchain procure puzzle solvers as resources they control, and use a mathematical model to compute optimal parameters for the cryptographic puzzle mechanism or other parts of the blockchain. We illustrate this approach with a use case …
Shoulder surfing is an attack vector widely recognized as a real threat - enough to warrant researchers dedicating a considerable effort toward designing novel authentication methods to be shoulder surfing resistant. Despite a multitude of proposed solutions over the years, few have employed empirical evaluations and comparisons between different methods, and our understanding of the shoulder surfing phenomenon remains limited. Barring the challenges in experimental design, the reason for that can be primarily attributed to the lack of objective and comparable vulnerability measures. In this p…
A novel digital watermarking for ownership verification and image authentication applications using discrete wavelet transform (DWT) is proposed in this paper. Most previous proposed watermarking algorithms embed sequences of random numbers as watermarks. Here binary images are taken as watermark for embedding. In the proposed approach, the host image is converted into the YCbCr color space and then its Y channel decomposed into wavelet coefficients. The selected approximation coefficients are quantized and then their four least significant bits of the quantized coefficients are replaced by th…
