Addressing Vulnerabilities in CAN-FD: An Exploration and Security Enhancement Approach

Smart grid (SG) achieves more convenient and efficient power transmission through the rapid development of the information and communication technology. In addition to the transmission of electrical energy, the SG system also involves privacy and control information of service providers, which is closely related to people's livelihood. However, at present, the data in the SG system are transmitted in the form of plaintext, which does not have complete protection measures for entity privacy and communication data security. Focusing on preserving entity privacy and data security, this article proposes an anonymous secure authentication protocol (ASAP-SG) for the SG environment. Based on elliptic curve cryptography and physical unclonable function, ASAP-SG can realize authentication and key agreement between smart meters and service providers. The security of ASAP-SG has been verified with proverif tool and proven strictly under the real-or-random model. Furthermore, heuristic analysis manifests that ASAP-SG can successfully resist known security attacks. Finally, a fully comparison with the other five most advanced schemes reveals that ASAP-SG consumes the optimal computation cost on both smart meters and service providers and reduces the communication overhead by 33.3%–45.8%, on the basis of satisfying ten security objectives. These features make ASAP-SG more suitable for resource-constrained SG environment.

With the enhanced data amount being created, it is significant to various organizations and their processing, and managing big data becomes a significant challenge for the managers of the data. The development of inexpensive and new computing systems and cloud computing sectors gave qualified industries to gather and retrieve the data very precisely however securely delivering data across the network with fewer overheads is a demanding work. In the decentralized framework, the big data sharing puts a burden on the internal nodes among the receiver and sender and also creates the congestion in network. The internal nodes that exist to redirect information may have inadequate buffer ability to momentarily take the information and again deliver it to the upcoming nodes that may create the occasional fault in the transmission of data and defeat frequently. Hence, the next node selection to deliver the data is tiresome work, thereby resulting in an enhancement in the total receiving period to allocate the information. Blockchain is the primary distributed device with its own approach to trust. It constructs a reliable framework for decentralized control via multi-node data repetition. Blockchain is involved in offering a transparency to the application of transmission. A simultaneous multi-threading framework confirms quick data channeling to various network receivers in a very short time. Therefore, an advanced method to securely store and transfer the big data in a timely manner is developed in this work. A deep learning-based smart contract is initially designed. The dilated weighted recurrent neural network (DW-RNN) is used to design the smart contract for the Ethereum blockchain. With the aid of the DW-RNN model, the authentication of the user is verified before accessing the data in the Ethereum blockchain. If the authentication of the user is verified, then the smart contracts are assigned to the authorized user. The model uses elliptic Curve ElGamal cryptography (EC-EC), which is a combination of elliptic curve cryptography (ECC) and ElGamal encryption for better security, to make sure that big data transfers on the Ethereum blockchain are safe. The modified Al-Biruni earth radius search optimization (MBERSO) algorithm is used to make the best keys for this EC-EC encryption scheme. This algorithm manages keys efficiently and securely, which improves data security during blockchain operations. The processes of encryption facilitate the secure transmission of big data over the Ethereum blockchain. Experimental analysis is carried out to prove the efficacy and security offered by the suggested model in transferring big data over blockchain via smart contracts.

The metaverse is a new virtual world that has the potential to significantly impact our interactions with digital content and with each other. It is a shared virtual environment where users can seamlessly and with immersive experiences create, interact, and enjoy digital assets. Nevertheless, the metaverse also poses fundamental challenges, particularly about security and privacy concerns, that require careful consideration. One of the most daunting aspects of securing the metaverse is authentication. Several solutions have been proposed, including deployment of blockchain technology and smart contracts, to address these authentication challenges. While these methods provide a secure and tamper-proof authentication mechanism, they fail to meet certain critical security and privacy requirements like interoperability and decentralization. This research proposes an enhanced privacy-preserving authentication scheme based on blockchain, elliptic curve cryptography, biohashing, and a physical unclonable function that guards against various attacks. The proposed scheme does not rely on a single central authority and consists of various phases, including user and avatar authentication, password change, and avatar generation phases. The proposed scheme underwent security assessment using the Burrows Abadi Needham (BAN) logic, ProVerif tool, and Scyther tool. The results demonstrate that it provides a better level of security against a wide range of attack vectors. The proposed scheme offers a swift and efficient authentication mechanism that adheres to the requirements of the metaverse environment, such as interoperability, decentralization, and privacy protection, and requires less computation cost as compared to state-of-the-art schemes.

Physically unclonable functions (PUFs) have been explored as lightweight hardware primitives for the purpose of realizing robust security via strong authentication or secure key/ID generation. PUF harness manufacturing process variations for the purpose of generating binary keys or binary functions. An ideal strong PUF is a binary function that maps an m-bit input challenge to an uniquen-bit output response, making it attractive for authentication applications. Unfortunately, real strong PUF implementations suffer from reliability issues where the same challenge may produce different responses in the presence of noise. To overcome this problem, strong PUF leverages the availability of exponential number of challenge-response pairs (CRPs). A successful authentication event requires acquiring multiple CRPs and applying a threshold. In contrast, weak PUFs produce limited keys and are required to be highly reliable. Multiple techniques have been developed to achieve the necessary reliability. An additional prerequisite for strong PUFs is resilience against model-building attacks (cloning) by an adversary, who has observed a few CRPs, to prevent successful prediction of future CRPs. In this work, we first illustrate a strong PUF design that re-purposes a weightless neural network (WNN). Second, we showcase the robustness of WNN-based strong PUFs with respect to machine learning attacks, while providing desirable uniqueness and reliability metrics. Finally, we employ an initial entropy source of highly reliable weak PUF bits mapped to weightless neural networks (WNNs) for the purpose of creating a near-ideal strong PUF in terms of reliability. Our results show that it is possible to create highly reliable WNN–based strong PUFs with < 65 % ML accuracy by using as few as 32 initial reliable weak PUF bits.

Several publications presented tamper-evident Physical Unclonable Functions (PUFs) for secure storage of cryptographic keys and tamper-detection. Unfortunately, previously published PUF-based key derivation schemes do not sufficiently take into account the specifics of the underlying application, i.e., an attacker that tampers with the physical parameters of the PUF outside of an idealized noise error model. This is a notable extension of existing schemes for PUF key derivation, as they are typically concerned about helper data leakage, i.e., by how much the PUF’s entropy is diminished when gaining access to its helper data. To address the specifics of tamper-evident PUFs, we formalize the aspect of tamper-sensitivity, thereby providing a new tool to rate by how much an attacker is allowed to tamper with the PUF. This complements existing criteria such as effective number of secret bits for entropy and failure rate for reliability. As a result, it provides a fair comparison among different schemes and independent of the PUF implementation, as its unit is based on the noise standard deviation of the underlying PUF measurement. To overcome the limitations of previous schemes, we then propose an Error-Correcting Code (ECC) based on the Lee metric, i.e., a distance metric well-suited to describe the distance between q-ary symbols as output from an equidistant quantization, i.e., a higher-order alphabet PUF. This novel approach is required, as the underlying symbols’ bits are not i.i.d. which hinders applying previous state-of-the-art approaches. We present the concept for our scheme and demonstrate its feasibility based on an empirical PUF distribution. The benefits of our approach are an increase by over 21% in effective secret bit compared to previous approaches based on equidistant quantization. At the same time, we improve tamper-sensitivity compared to an equiprobable quantization while ensuring similar reliability and entropy. Hence, this work opens up a new direction of how to interpret the PUF output and details a practically relevant scheme outperforming all previous constructions.

The lack of stability is one of the limitations that constrain physical unclonable function (PUF) from being put in widespread practical use. In this paper, we propose a weak PUF and a strong PUF that are both completely stable. These PUFs are called locally enhanced defectivity physical unclonable function (LEDPUF). An LEDPUF is a pure functional PUF that does not require any kinds of correction schemes as conventional parametric PUFs do. The source of randomness of an LEDPUF is extracted from locally enhance defectivity without affecting other parts of the chip. In this paper, we construct a weak LEDPUF by forming arrays of directed self-assembly random connections, and the strong LEDPUF is implemented by using the weak LEDPUF as the key of a keyed-hash message authentication code. Our simulation and statistical results show that the entropy of the weak LEDPUF bits is close to ideal, and the inter-chip Hamming distances of both weak and strong LEDPUFs are about 50%, which means that these LEDPUFs are not only stable but also unique. We develop a new unified framework for evaluating the security of PUFs, based on password security, by using information theoretic tools of guesswork. The guesswork model allows us to quantitatively compare, with a single unified metric, PUFs with varying levels of stability, bias, and available side information. In addition, it generalizes other measures to evaluate the security level, such as min-entropy and mutual information. We evaluate the guesswork-based security of some measured static random access memory and ring oscillator PUFs as an example and compare them with an LEDPUF to show that the stability has a more severe impact on the PUF security than biased responses. Furthermore, we find the guesswork of two new problems: guesswork under the probability of attack failure and the guesswork of strong PUFs that are used for authentication.

Recent fourth industrial revolution, industry4.0 results in lot of automation of industrial processes and brings intelligence in many home appliances in the form of IoT, enhances M2M / D2D communication where electronic devices play a prominent role. It is very much necessary to ensure security of those devices. To provide reliable authentication and identification of each device and to abort the counterfeiting from the unauthorized foundries Physical Unclonable Functions (PUFs) emerged as a one of the promising cryptographic hardware security solution. PUF is function, mathematically modeled by using uncontrollable/ unavoidable random variances of the fabrication process of the ICs. These variances can generate unpredictable, random responses can be used to overcome the difficulties such as storing the keys in non-volatile memories (NVMs) in the classical cryptography. A wide variety of PUF architectures such as Arbiter PUFs, Ring oscillator PUFs, SRAM PUFs proposed by authors. But due to its design complexity and low cost, Delay based Arbiter PUFs (D-PUFs) are considering to be a one of the security primitives in authentication applications such as low-cost IoT devices for secure key generation. This paper presents a review on the different types of Delay based PUF architectures proposed by the various authors, sources to exhibit the physical disorders in ICs, methods to estimate the Performance metrics and applications of PUF in different domains.

Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained network nodes. The XOR Arbiter PUF (XOR PUF or XPUF) is an intensively studied PUF invented to improve the security of the Arbiter PUF, probably the most lightweight delay-based PUF. Recently, highly powerful machine learning attack methods were discovered and were able to easily break large-sized XPUFs, which were highly secure against earlier machine learning attack methods. Component-differentially-challenged XPUFs (CDC-XPUFs) are XPUFs with different component PUFs receiving different challenges. Studies showed they were much more secure against machine learning attacks than the conventional XPUFs, whose component PUFs receive the same challenge. But these studies were all based on earlier machine learning attack methods, and hence it is not clear if CDC-XPUFs can remain secure under the recently discovered powerful attack methods. In this paper, the two current most powerful two machine learning methods for attacking XPUFs are adapted by fine-tuning the parameters of the two methods for CDCXPUFs. Attack experiments using both simulated PUF data and silicon data generated from PUFs implemented on field-programmable gate array (FPGA) were carried out, and the experimental results showed that some previously secure CDC-XPUFs of certain circuit parameter values are no longer secure under the adapted new attack methods, while many more CDC-XPUFs of other circuit parameter values remain secure. Thus, our experimental attack study has re-defined the boundary between the secure region and the insecure region of the PUF circuit parameter space, providing PUF manufacturers and IoT security application developers with valuable information in choosing PUFs with secure parameter values.

Communication security is essential for the proper functioning of the Internet of Things. Traditional approaches that rely on cryptographic keys are vulnerable to side-channel attacks. Physical Unclonable Functions (PUFs), leveraging unavoidable and irreproducible variations of integrated circuits to produce responses unique for individual PUF devices, are emerging as promising candidates as security primitives to provide keyless solutions. Before a PUF can be adopted for real applications, the PUF must be thoroughly examined to understand its various properties for its application feasibility. In this paper, we study XOR PUFs for broad ranges of values for circuit architecture parameters. XOR PUFs have been extensively studied, and have been shown to be unable to withstand machine learning attacks for 64-bit XOR PUFs with less than ten component PUFs. Attack methods employed in existing studies need a large number of challenge-response pairs (CRPs), which are obtainable only if the PUF has an open access interface. When PUF-embedded devices equipped with mutual authentication or response obfuscating techniques, it is difficult for attackers to accumulate large numbers of CRPs. With only a small number of accumulated CRPs available to attackers, small size PUFs, like XOR PUFs with a small number of component PUFs and stages, may become resistant to machine learning attacks. Since smaller sizes mean less resource-demanding, it is worthwhile to examine such PUFs which have usually been considered unsafe against attacks. Such are thoughts that have been motivating us in this paper to explore the PUF performances for a wide range of values of the PUF architecture parameters.

Physical unclonable functions (PUFs) are devices which are easily probed but difficult to predict. Optical PUFs have been discussed within the literature, with traditional optical PUFs typically using spatial light modulators, coherent illumination, and scattering volumes; however, these systems can be large, expensive, and difficult to maintain alignment in practical conditions. We propose and demonstrate a new kind of optical PUF based on computational imaging and compressive sensing to address these challenges with traditional optical PUFs. This work describes the design, simulation, and prototyping of this computational optical PUF (COPUF) that utilizes incoherent polychromatic illumination passing through an additively manufactured refracting optical polymer element. We demonstrate the ability to pass information through a COPUF using a variety of sampling methods, including the use of compressive sensing. The sensitivity of the COPUF system is also explored. We explore non-traditional PUF configurations enabled by the COPUF architecture. The double COPUF system, which employees two serially connected COPUFs, is proposed and analyzed as a means to authenticate and communicate between two entities that have previously agreed to communicate. This configuration enables estimation of a message inversion key without the calculation of individual COPUF inversion keys at any point in the PUF life cycle. Our results show that it is possible to construct inexpensive optical PUFs using computational imaging. This could lead to new uses of PUFs in places where electrical PUFs cannot be utilized effectively, as low cost tags and seals, and potentially as authenticating and communicating devices.

Embedded systems carry and process more and more sensitive information in untrusted environments, where an attacker can wiretap the external communication and also has unlimited physical access to the device. Cryptography protects systems against many of the threats and relies on the security of the cryptographic keys inside the system. Physical Unclonable Functions (PUFs) measure manufacturing variations inside integrated circuits, for example FPGAs, to generate a unique secret PUF response inside each device. Similar to deriving a biometric pattern from human features, the individual pattern inside an FPGA differs slightly from measurement to measurement. From these measurements, the PUF response is generated to derive a secure and reliable cryptographic key. The Ring-Oscillator (RO) PUF is a popular PUF type because of its high randomness and reliability. Frequencies of ROs are compared pairwise to derive one secret bit. So far, the reliability of RO PUFs was evaluated by counting bit flips in measured PUF responses. This work analyzes the distribution of frequency measurements to derive the behavior of the PUF. Analyzing the frequency distributions gives a more precise estimation of the PUF bit error rates than measuring the bit errors after the comparison of two oscillator frequencies. The evaluation of publicly available real world empirical FPGA data has shown that most error probabilities of RO PUF responses are so low that they cannot be measured in feasible time. For almost 200 evaluated FPGAs, more than 70% of the PUF outputs on every FPGA have bit error probabilities under 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-20</sup> . We can even ensure this error probability for over 60% of the PUF outputs after a practicable number of frequency measurements with a confidence of 99.9%. Index Terms-Physical Unclonable Functions (PUFs), Ring Oscillator PUF, FPGA, Statistics.

In Vehicular Ad-hoc Networks (VANETs), the ability of emergency vehicles (EVs) to reach their destinations quickly can maximize the protection of people’s lives and property safety, and minimize the losses and impacts caused by various emergencies. In this endeavor, the emergency vehicle avoidance protocol is of paramount importance. However, the existing authentication protocol is vulnerable to side-channel attacks, Roadside Units (RSUs) captured attacks, as well as untraceability, etc. Therefore, for wider and more practical realizability, we propose an efficient and secure authentication scheme based on Elliptic Curves Cryptography (ECC), fuzzy extraction algorithm and Physical Unclonable Function (PUF) for EVs avoidance. In the protocols, PUF and biometric key are used for protecting RSUs’ and EVs’ privacy information respectively. Additionally, a conditional privacy-preserving and traceable message authentication strategy is designed for emergency messages propagation, the avoidance messages can be forwarded to ordinary vehicles before the EVs arriving. Compared with related EVs avoidance protocols, our protocol can resist side-channel attacks and other various known attacks. In our scheme, the first authentication efficiencies have increased by 11.72% and the subsequent authentication increased by 25.99% than the previous protocols in the same scenario. Security and performance analysis demonstrate that the proposed scheme is secure, efficient, and practical.

Physical Unclonable Functions (PUF) are an emerging hardware security primitives proposed by various researchers in last one decade. PUFs are useful security architectures used for identification, authentication and cryptographic key generation. Many PUF topologies are proposed in the past targeting both ASIC and FPGA. It is nearly impossible to get two PUF circuits with same characteristics for the same design. PUFs make use of random process variation occurring during manufacturing of IC which is uncontrollable. The most versatile PUF is ring oscillator (RO) PUF, in which the frequencies of ring oscillators are compared to produce the PUF response. The conventional approach consumes large number of ring oscillators and requires all RO's to be mutually symmetric. In this paper, we have proposed a RO-PUF for FPGA devices, which is capable of generating multiple output bits from each ring oscillator with better security metrics in comparison with PUF designed with similar technique. The PUF is implemented on Xilinx Spartan 3E FPGA boards and the challenge-response pairs (CRP) are verified for statistical properties.

A Physical Unclonable Function (PUF) is a die specific random function that can be used in a number of secure IC applications including die identification/authentication and key generation. At the core of a silicon PUF is a circuit (the PUF core) that generates random bits. These bits are like a silicon biometric, unique across dies, but can be reliably reproduced multiple times on a die across voltage and temperature variations and aging. In this thesis, we discuss various aspects of a PUF design, with a strong focus on circuit details. We describe the properties and the figures of merit of a PUF and then compare various PUF core implementations. We identify the biggest design challenges and provide several solutions. Results in this work are supported by measurement data from testchips designed in 65nm bulk CMOS. We provide an apples-to-apples comparison of various PUF implementations. We demonstrate that while adequate randomness and uniqueness is achievable for most PUF implementations, achieving high reliability is a challenge. The conventional method to achieve high reliability is to use error correcting codes (ECC). Unfortunately, the overheads associated with these techniques grows very quickly with error correction capability. Alternately, researchers have proposed several error reduction techniques to minimize the use of error correction. In this work, we evaluate four orthogonal and complementary error reduction techniques. Two of these techniques, categorized as extrinsic techniques, are multiple evaluation (ME) and activation control (AC) and are able to reduce errors in PUF response by ~70-80%. The other two techniques, categorized as intrinsic, are post-silicon selection (PSS) and directed accelerated aging (DAA) and show ~100% correction of errors. As a proof of concept prototype, we describe a self-contained, BIST-controlled key-generator that implements the PSS technique to autonomously generate bits with a bit error rate &lt; 5 * 10^-9, equivalent to a 128-bit key error rate &lt; 10^-6. We also describe a realization of a strong-PUF that uses these highly reliable bits in conjunction with an Advanced Encryption Standard (AES) primitive.

A fundamental property of physical unclonable functions (PUFs) is that they generate unique outputs that cannot be reproduced by another chip, even with an identical circuit and layout design. Several configurations of feed-forward PUFs (FF PUFs) are evaluated in terms of their interchip variation, a measure of uniqueness. In general, PUFs are considered to be unique due to symmetry in their path delay distributions, which are typically Gaussian. In this paper, we prove that certain FF PUFs can result in skewed path delay distributions leading to poor uniqueness. In these PUFs, the total delay difference is sum of a symmetric Gaussian distribution and an asymmetric half-Gaussian distribution. We also compute empirical estimates and verify our observations by simulating 200 PUFs in each FF configuration. It is observed that (1) FF PUFs with one intermediate arbiter and odd number of feed-forward loops and (2) FF PUFs in cascade or separate configurations have degraded interchip variation. This is the first study to observe and prove the non-uniqueness property of such PUFs.