Biblio

Supply chain management systems (SCM) are the most intensive and statistical RFID application for object tracking. A lot of research has been carried out to overcome security issues in the field of online/offline object tracking as well as authentication protocols involving RFID technology. Due to advancements with the Internet of Things (IoT) and embedded systems in object tracking schemes the latest research manages to deliver information about the object’s location as well as provide particulars about the state of an object. Recent research presented a proposal for an authentication and online object tracking protocol focusing on solutions for privacy issues for device identification, end-to-end authentication, and secure online object tracking. However, recent schemes have been found to be vulnerable to traceability attacks. This paper presents an enhanced end-to-end authentication scheme where the identity of the user is kept anonymous so that its actions can not be tracked, eliminating attacks related to traceability. The security of the proposed protocol is formally analyzed using the attack model of the automated security testing tool, ProVerif. The proposed scheme outperforms competing schemes based on security.

Major manufacturers and retailers are increasingly using RFID systems in supply-chain scenarios, where theft of goods during transport typically causes significant economic losses for the consumer. Recent sample-based authentication methods attempt to use a small set of random sample tags to authenticate the integrity of the entire tag population, which significantly reduces the authentication time at the expense of slightly reduced reliability. The problem is that it still incurs extensive initialization overhead when writing the authentication information to all of the tags. This paper presents KTAuth, a lightweight integrity authentication approach to efficiently and reliably detect missing tags and counterfeit tags caused by stolen attacks. The competitive advantage of KTAuth is that it only requires writing the authentication information to a small set of deterministic key tags, offering a significant reduction in initialization costs. In addition, KTAuth strictly follows the C1G2 specifications and thus can be deployed on Commercial-Off-The-Shelf RFID systems. Furthermore, KTAuth proposes a novel authentication chain mechanism to verify the integrity of tags exclusively based on data stored on them. To evaluate the feasibility and deployability of KTAuth, we implemented a small-scale prototype system using mainstream RFID devices. Using the parameters achieved from the real experiments, we also conducted extensive simulations to evaluate the performance of KTAuth in large-scale RFID systems.

Return-oriented programming(ROP) is a prevalent technique that targets return addresses to hijack control flow. To prevent such attack, researchers mainly focus on either Shadow Stack or MAC-based mechanisms(message code authentication). But Shadow Stack suffers from additional memory overhead and information leakage, while MAC-based mechanisms(e.g. Zipper Stack) impose high runtime overhead for MAC calculations.In this paper, we propose Twine Stack, a hybrid and efficient return address protection mechanism with lightweight hardware extension. It utilizes a tiny hardware shadow stack to realize a new multi-chain Zipper Stack. Specifically, each entry in the shadow stack stores a return address and its MAC in each chain, allowing queueing calculation with just one hash module. At meantime, some return address verifications could be done by comparison with the hardware shadow stack, instead of calculation again. We implemented Twine Stack on RISC-V architecture, and evaluated it on FPGA board. Our experiments show that Twine Stack reduces over 95% hash verifications, and imposes merely 1.38% performance overhead with an area overhead of 974 LUTs and 726 flip flops. The result demonstrates that our hybrid scheme mitigates the drawbacks of each separate scheme.

Code-reuse attacks pose a threat to embedded devices since they are able to defeat common security defenses such as non-executable stacks. To succeed in his code-reuse attack, the attacker has to gain knowledge of some or all of the instructions of the target firmware/software. In case of a bare-metal firmware that is protected from being dumped out of a device, it is hard to know the running instructions of the target firmware. This consequently makes code-reuse attacks more difficult to achieve. This paper shows how an attacker can gain knowledge of some of these instructions by sniffing the unencrypted incremental updates. These updates exist to reduce the radio reception power for resource-constrained devices. Based on the literature, these updates are checked against authentication and integrity, but they are sometimes sent unencrypted. Therefore, it will be demonstrated how a Return-Oriented Programming (ROP) attack can be accomplished using only the passively sniffed incremental updates. The generated updates of the R3diff and Delta Generator (DG) differencing algorithms will be under assessment. The evaluation reveals that both of them can be exploited by the attacker. It also shows that the DG generated updates leak more information than the R3diff generated updates. To defend against this attack, different countermeasures that consider different power consumption scenarios are proposed, but yet to be evaluated.

Rapid multiplication of electric vehicles requires the implementation of a new infrastructure to sustain their operations. For instance, charging these vehicles batteries necessitates a connection that allows information exchanges between vehicle and infrastructure. These exchanges are managed by a network called V2G (Vehicle to Grid), which is governed by the ISO 15118 standard. This last recommends the use of X.509 hierarchical PKI to protect the network communications against attacks. Although several authors have identified and criticized the shortcomings of this proposal, but no one provides a robust and effective remedial solution to alleviate them. This paper proposes an efficient protocol that addresses these shortcomings while respecting the concepts of the ISO 15118 standard. It fulfills the most important security requirements i.e. confidentiality, anonymity, integrity and non-repudiation. The validity and effectiveness of the proposed protocol were confirmed using the formal modeling tool Tamarin Prover and the RISE- V2G simulator.

Signatures are used on documents as written proof that the document was verified by the person indicated. Signature also indicated that the document originated from the signer if the document is transferred to another party. A document maybe in physical print form but may also be a digital print. A digital print requires additional security since a digital document may easily be altered by anyone although the said document is signed using a photographed or scanned signature. One of the means of security is by using the RSA Digital Signature method which is a combination of the RSA algorithm with Digital Signature. RSA algorithm is one of the public key cryptography algorithms, while Digital Signature is a security scheme which may guarantee the authenticity, non-repudiation, and integrity of a file by means of a hash function. This research implemented a web-based combination of RSA Digital Signature with SHA-3 hash function to secure the integrity of PDF files using PHP programming language. The result is a web-based system which could guarantee the authenticity, non repudiation and integrity of PDF files. Testing were carried out on six different sizes of PDF files ranging from 6 KB, up to 23285 KB on three different web browsers: Google Chrome, Microsoft Edge, and Mozilla Firefox. Average processing times of signing and verifying on each browsers were 1.3309 seconds, 1.2565 seconds, and 1.2667 seconds.

Web pages aggressively track users for a variety of purposes from targeted advertisements to enhanced authentication. As browsers move to restrict traditional cookie-based tracking, web pages increasingly move to tracking based on browser fingerprinting. Unfortunately, the state-of-the-art to detect fingerprinting in browsers is often error-prone, resorting to imprecise heuristics and crowd-sourced filter lists. This paper presents EssentialFP, a principled approach to detecting fingerprinting on the web. We argue that the pattern of (i) gathering information from a wide browser API surface (multiple browser-specific sources) and (ii) communicating the information to the network (network sink) captures the essence of fingerprinting. This pattern enables us to clearly distinguish fingerprinting from similar types of scripts like analytics and polyfills. We demonstrate that information flow tracking is an excellent fit for exposing this pattern. To implement EssentialFP we leverage, extend, and deploy JSFlow, a state-of-the-art information flow tracker for JavaScript, in a browser. We illustrate the effectiveness of EssentialFP to spot fingerprinting on the web by evaluating it on two categories of web pages: one where the web pages perform analytics, use polyfills, and show ads, and one where the web pages perform authentication, bot detection, and fingerprinting-enhanced Alexa top pages.

The use of wearable devices (e.g., smartwatches) in two factor authentication (2FA) is fast emerging, as wearables promise better usability compared to smartphones. Still, the current deployments of wearable 2FA have significant usability and security issues. Specifically, one-time PIN-based wearable 2FA (PIN-2FA) requires noticeable user effort to open the app and copy random PINs from the wearable to the login terminal's (desktop/laptop) browser. An alternative approach, based on one-tap approvals via push notifications (Tap-2FA), relies upon user decision making to thwart attacks and is prone to skip-through. Both approaches are also vulnerable to traditional phishing attacks. To address this security-usability tension, we introduce a fundamentally different design of wearable 2FA, called SG-2FA, involving wrist-movement “seamless gestures” captured near transparently by the second factor wearable device while the user types a very short special sequence on the browser during the login process. The typing of the special sequence creates a wrist gesture that when identified correctly uniquely associates the login attempt with the device's owner. The special sequence can be fixed (e.g., “\$@\$@\$\$”), does not need to be a secret, and does not need to be memorized (could be simply displayed on the browser). This design improves usability over PIN-2FA since only this short sequence has to be typed as part of the login process (no interaction with or diversion of attention to the wearable and copying of random PINs is needed). It also greatly improves security compared to Tap-2FA since the attacker can not succeed in login unless the user's wrist is undergoing the exact same gesture at the exact same time. Moreover, the approach is phishing-resistant and privacy-preserving (unlike behavioral biometrics). Our results show that SG-2FA incurs only minimal errors in both benign and adversarial settings based on appropriate parameterizations.

Recent years have seen an increase in medical big data, which can be attributed to a paradigm shift experienced in medical data sharing induced by the growth of medical technology and the Internet of Things. The evidence of this potential has been proved during the recent covid-19 pandemic, which was characterised by the use of medical wearable devices to help with the medical data exchange between the healthcare providers and patients in a bid to contain the pandemic. However, the use of these technologies has also raised questions and concerns about security and privacy risks. To assist in resolving this issue, this paper proposes a blockchain-based access control framework for managing access to users’ medical data. This is facilitated by using a smart contract on the blockchain, which allows for delegated access control and secure user authentication. This solution leverages blockchain technology’s inherent autonomy and immutability to solve the existing access control challenges. We have presented the solution in the form of a medical wearable sensor prototype and a mobile app that uses the Ethereum blockchain in a real data sharing control scenario. Based on the empirical results, the proposed solution has proven effective. It has the potential to facilitate reliable data exchange while also protecting sensitive health information against potential threats. When subjected to security analysis and evaluation, the system exhibits performance improvements in data privacy levels, high security and lightweight access control design compared to the current centralised access control models.

Recently, the frequent security incidents of the Internet of things make the wearable IOT health monitoring systems (WIHMS) face serious security threats. Aiming at the security requirements of WIHMS identity authentication, Q. Jiang proposed a lightweight device mutual identity authentication solution in 2019. The scheme has good security performance. However, we find that in Jiang’s scheme, in the authentication phase, the server CS needs at least 3 queries and 1 update of the database operation, which affects the overall performance of the system. For this reason, we propose a new device mutual authentication and key agreement protocol. In our protocol, the authentication server only needs to query the server database twice.

Adaptive authentication systems identify and enforce suitable methods to verify that someone (user) or something (device) is eligible to access a service or a resource. An authentication method is usually adapted in response to changes in the security risk or the user's behaviour. Previous work on adaptive authentication systems provides limited guidance about i) what and how contextual factors can affect the selection of an authentication method; ii) which requirements are relevant to an adaptive authentication system and iii) how authentication methods can affect the satisfaction of the relevant requirements. In this paper, we provide a holistic framework informed by previous research to characterize the adaptive authentication problem and support the development of an adaptive authentication system. Our framework explicitly considers the contextual factors that can trigger an adaptation, the requirements that are relevant during decision making and their trade-offs, as well as the authentication methods that can change as a result of an adaptation. From the gaps identified in the literature, we elicit a set of challenges that can be addressed in future research on adaptive authentication.

Assuring Cybersecurity for the Internet of things (IoT) remains a significant challenge. Most IoT devices have minimal computational power and should be secured with lightweight security techniques (optimized computation and energy tradeoff). Furthermore, IoT devices are mainly designed to have long lifetimes (e.g., 10–15 years), forcing the designers to open the system for possible future updates. Here, we developed a lightweight and reconfigurable security architecture for IoT devices. Our research goal is to create a simple authentication protocol based on physical unclonable function (PUF) for FPGA-based IoT devices. The main challenge toward realization of this protocol is to make it make it resilient against machine learning attacks and it shall not use cryptography primitives.

The traditional data storage method often adopts centralized architecture, which is prone to trust and security problems. This paper proposes a trusted data storage and access control scheme combining blockchain and attribute-based encryption, which allow cyber-physical system (CPS) nodes to realize the fine-grained access control strategy. At the same time, this paper combines the blockchain technology with distributed storage, and only store the access control policy and the data access address on the blockchain, which solves the storage bottleneck of blockchain system. Furthermore, this paper proposes a novel multi-authority attributed-based identification method, which realizes distributed attribute key generation and simplifies the pairwise authentication process of multi-authority. It can not only address the key escrow problem of one single authority, but also reduce the problem of high communication overhead and heavy burden of multi-authority. The analyzed results show that the proposed scheme has better comprehensive performance in trusted data storage and access control for power cyber-physical system.

Smart grid has improved the security, efficiency of the power system and balanced the supply and demand by intelligent management, which enhanced stability and reliability of power grid. The key point to achieve them is real-time data and consumption data sharing by using fine-grained policies. But it will bring the leakage of the privacy of the users and the loss of data control rights of the data owner. The reported solutions can not give the best trade-off among the privacy protection, control over the data shared and confidentiality. In addition, they can not solve the problems of large computation overhead and dynamic management such as users' revocation. This paper aims at these problems and proposes a decentralized attribute-based data sharing scheme. The proposed scheme ensures the secure sharing of data while removing the central authority and hiding user's identity information. It uses attribute-based signcryption (ABSC) to achieve data confidentiality and authentication. Under this model, attribute-based encryption gives the access policies for users and keeps the data confidentiality, and the attribute-based signature is used for authentication of the primary ciphertext-integrity. It is more efficient than "encrypt and then sign" or "sign and then encrypt". In addition, the proposed scheme enables user's revocation and public verifiability. Under the random oracle model, the security and the unforgeability against adaptive chosen message attack are demonstrated.

Attestation of audio signals for recognition of forgery in voice is challenging task. In this research work, a deep convolutional neural network (CNN) is utilized to detect audio operations i.e. pitch shifted and amplitude varied signals. Short-time Fourier transform (STFT) and Modified Discrete Cosine Transform (MDCT) features are chosen for audio processing and their plotted patterns are fed to CNN. Experimental results show that our model can successfully distinguish tampered signals to facilitate the audio authentication on TIMIT dataset. Proposed CNN architecture can distinguish spoofed voices of shifting pitch with accuracy of 97.55% and of varying amplitude with accuracy of 98.85%.

Controller Area Network is the bus standard that works as a central system inside the vehicles for communicating in-vehicle messages. Despite having many advantages, attackers may hack into a car system through CAN bus, take control of it and cause serious damage. For, CAN bus lacks security services like authentication, encryption etc. Therefore, an anomaly detection system must be integrated with CAN bus in vehicles. In this paper, we proposed an Artificial Neural Network based anomaly detection method to identify illicit messages in CAN bus. We trained our model with two types of attacks so that it can efficiently identify the attacks. When tested, the proposed algorithm showed high performance in detecting Denial of Service attacks (with accuracy 100%) and Fuzzy attacks (with accuracy 99.98%).

This paper proposes a real time implementation of a smart key which is a Wi-Fi based device that helps to lock/unlock all kinds of doors. Internet access allows to control doors all over the world by a simple mobile application. The app developed can be used in two modes ADMIN and GUEST mode. The ADMIN mode is protected by pin/password and is encrypted by the Advanced Encryption Standard (AES) algorithm. The password can be stored in the Key store and it can be changed whenever required. The ADMIN mode has the privilege to authenticate the GUEST mode to access all doors. For GUEST mode authentication, guests have to request the admin by using the app. Firebase is used as a server where the device and the mobile app are connected to it. Firebase is fast and accurate and hence can be accessed quickly. The main advantage of this proposed method is that it is fully operated through Internet so it can locked/unlocked wherever from the world. Comparative analysis is taken for three algorithms i.e., AES, DES and 3-DES and AES algorithm has given the best results in terms of execution time and memory usage and is implemented in the hardware lock. The experimental results give the screen shots of the app in guest and admin mode, firebase data and hardware real time implementation of the smart lock on a door.

The construction of the power Internet of Things has led various terminals to access the corporate network on a large scale. The internal and external business interaction and data exchange are more extensive. The current security protection system is based on border isolation protection. This is difficult to meet the needs of the power Internet of Things connection and open shared services. This paper studies the application scheme of the ``zero trust'' typical business scenario of the power Internet of Things with ``Continuous Identity Authentication and Dynamic Access Control'' as the core, and designs the power internet security protection architecture based on zero trust.

In order to guarantee the normal operation of the power Internet of things devices, the zero-trust idea was used for studying the security protection strategies of devices from four aspects: user authentication, equipment trust, application integrity and flow baselines. Firstly, device trust is constructed based on device portrait; then, verification of device application integrity based on MD5 message digest algorithm to achieve device application trustworthiness. Next, the terminal network traffic baselines are mined from OpenFlow, a southbound protocol in SDN. Finally, according to the dynamic user trust degree attribute access control model, the comprehensive user trust degree was obtained by weighting the direct trust degree. It obtained from user authentication and the trust degree of user access to terminal communication traffic. And according to the comprehensive trust degree, users are assigned the minimum authority to access the terminal to realize the security protection of the terminal. According to the comprehensive trust degree, the minimum permissions for users to access the terminal were assigned to achieve the security protection of the terminal. The research shows that the zero-trust mechanism is applied to the terminal security protection of power Internet of Things, which can improve the reliability of the safe operation of terminal equipment.

We consider the anonymous mutual authentication problem, which consists of a certificate authority, single or multiple verifiers, many legitimate users (provers) and any arbitrary number of illegitimate users. The legal verifier and a legitimate user must be mutually authenticated to each other using the user's key, while the identity of the user must stay unrevealed. An attacker (illegitimate prover) as well as an illegal verifier must fail in authentication. A general interactive information theoretic framework in a finite field is proposed, where the normalized total key rate as a metric for reliability is defined. Maximizing this rate has a trade-off with establishing anonymity. The problem is studied in two different scenarios: centralized scenario (one single verifier performs the authentication process) and distributed scenario (authentication is done by N verifiers, distributively). For both scenarios, achievable schemes, which satisfy the completeness, soundness (at both verifier and prover) and anonymity properties, are proposed. Increasing the size of the field, results in the key rate approaching its upper bound.

This paper proposes an anonymity based mechanism for providing privacy in IoT environment. Proposed scheme allows IoT entities to anonymously interacting and authenticating with each other, or even proving that they have trustworthy relationship without disclosing their identities. Authentication is based on an anonymous certificates mechanism where interacting IoT entities could unlinkably prove possession of a valid certificate without revealing any incorporated identity-related information, thereby preserving their privacy and thwarting tracking and profiling attacks. Through a security analysis, we demonstrate the reliability of our solution.

In recent years, biometric authentication, such as fingerprint and face recognition, has become widespread in smartphones. However, fingerprint and face authentication have the problem that they cannot be used depending on the condition of the user's fingers or face. Therefore, we have been investigating a new biometric authentication system using pinna as a personal authentication system for smart phones. We have studied a personal authentication system using the Pinna Related Transfer Function (PRTF), which is an acoustic transfer function measured from the pinna. However, since the position of the smartphone changes every time it is placed on the ear, there is a problem that the authentication rate decreases. In this paper, we propose a multimodal personal authentication system using PRTF, pinna images, and smartphone location information, and verify its effectiveness. The results show that the proposed authentication system can improve the robustness against the fluctuation of the smartphone location.

The two-factor authentication (2FA) has drawn increasingly attention as the mobile devices become more prevalent. For example, the user's possession of the enrolled phone could be used by the 2FA system as the second proof to protect his/her online accounts. Existing 2FA solutions mainly require some form of user-device interaction, which may severely affect user experience and creates extra burdens to users. In this work, we propose Proximity-Echo, a secure 2FA system utilizing the proximity of a user's enrolled phone and the login device as the second proof without requiring the user's interactions or pre-constructed device fingerprints. The basic idea of Proximity-Echo is to derive location signatures based on acoustic beep signals emitted alternately by both devices and sensing the echoes with microphones, and compare the extracted signatures for proximity detection. Given the received beep signal, our system designs a period selection scheme to identify two sound segments accurately: the chirp period is the sound segment propagating directly from the speaker to the microphone whereas the echo period is the sound segment reflected back by surrounding objects. To achieve an accurate proximity detection, we develop a new energy loss compensation extraction scheme by utilizing the extracted chirp periods to estimate the intrinsic differences of energy loss between microphones of the enrolled phone and the login device. Our proximity detection component then conducts the similarity comparison between the identified two echo periods after the energy loss compensation to effectively determine whether the enrolled phone and the login device are in proximity for 2FA. Our experimental results show that our Proximity-Echo is accurate in providing 2FA and robust to both man-in-the-middle (MiM) and co-located attacks across different scenarios and device models.

Authentication and access control techniques are fundamental security elements to restrict access to critical resources in IoT environment. In the current state-of-the-art approaches in the literature, the architectures do not address the security features of authentication and access control together. Besides, they don't completely fulfill the key Internet-of-Things (IoT) features such as usability, scalability, interoperability and security. In this paper, we introduce a novel blockchain-based architecture for authentication and capability-based access control for IoT environment. A capability is a token which contains the access rights authorized to the device holding it. The architecture uses blockchain technology to carry out all the operations in the scheme. It does not embed blockchain technology into the resource-constrained IoT devices for the purpose of authentication and access control of the devices. However, the IoT devices and blockchain are connected by means of interfaces through which the essential communications are established. The authenticity of such interfaces are verified before any communication is made. Consequently, the architecture satisfies usability, scalability, interoperability and security features. We carried out security evaluation for the scheme. It exhibits strong resistance to threats like spoofing, tampering, repudiation, information disclosure, and Denial-of-Service (DoS). We also developed a proof of concept implementation where cost and storage overhead of blockchain transactions are studied.

Neural Network Physical Unclonable Function (NN-PUF) has been proposed for the secure implementation of Edge AI. This study evaluates the tamper resistance of NN-PUF against machine learning attacks. The machine learning attack in this study learns CPRs using deep learning. As a result of the evaluation experiment, the machine learning attack predicted about 82% for CRPs. Therefore, this study revealed that NN-PUF is vulnerable to machine learning attacks.