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Recently, there has been a lot of success in using the deterministic approach to provide approximate characterization of Gaussian network capacity. In this paper, we take a deterministic view and revisit the problem of wiretap channel with side information. A precise characterization of the secrecy capacity is obtained for a linear deterministic model, which naturally suggests a coding scheme which we show to achieve the secrecy capacity of the degraded Gaussian model (dubbed as “secret writing on dirty paper”) to within half a bit. [ABSTRACT FROM PUBLISHER]

Wet paper codes are used to design steganographic schemes, in which the sender can embed messages into a cover with arbitrarily selected changeable bits that are not shared by the recipient. In this letter, we propose a novel approach to wet paper codes by folding the cover into several layers and applying basic wet paper coding methods with low computational complexity to each layer. This method uses the changes introduced in the first layer to embed messages into every layer and therefore achieves high embedding efficiency (average number of bits embedded by per change). [ABSTRACT FROM AUTHOR]

In this paper, we show that the communication channel known as writing in memory with defective cells is a relevant information-theoretical model for a specific case of passive warden steganography when the sender embeds a secret message into a subset C of the cover object X without sharing C with the recipient. The set C, which is also called the selection channel, could be arbitrary, determined by the sender from the cover object using a deterministic, pseudo-random, or a truly random process. We call this steganography "writing on wet paper" and realize it using a simple variable-rate random linear code that gives the sender a convenient flexibility and control over the embedding process and is thus suitable for practical implementation. The importance of the wet paper scenario for covert communication is discussed within the context of adaptive steganography and perturbed quantization steganography. Heuristic arguments supported by tests using blind steganalysis indicate that the wet paper steganography provides improved steganographic security and is less vulnerable to steganalytic attacks compared with existing methods with shared selection channels. [ABSTRACT FROM PUBLISHER]

Security of linear ramp secret sharing schemes can be characterized by the relative generalized Hamming weights of the involved codes. In this paper, we elaborate on the implication of these parameters and devise a method to estimate their value for general one-point algebraic geometric codes. As it is demonstrated, for Hermitian codes, our bound is often tight. Furthermore, for these codes, the relative generalized Hamming weights are often much larger than the corresponding generalized Hamming weights. [ABSTRACT FROM AUTHOR]

Wet paper codes were previously proposed as a tool for construction of steganographic schemes with arbitrary (nonshared) selection channels. In this paper, we propose a new approach to wet paper codes using random linear codes of small codimension that at the same time improves the embedding efficiency (number of random message bits embedded per embedding change). Practical algorithms are given and their performance is evaluated experimentally and compared to theoretically achievable bounds. An approximate formula for the embedding efficiency of the proposed scheme is derived. The proposed coding method can be modularly combined with most steganographic schemes to improve their security. [ABSTRACT FROM PUBLISHER]

In image steganography, a pixel can carry secret bits by choosing adding/subtracting one to/from the gray value. This kind of"±1 steganography" can hide a longer message than simple LSB embedding. We propose a double-layered embedding method for implementing "±1 steganography," in which binary covering codes and wet paper codes are used to hide messages in the LSB plane and the second LSB plane, respectively. We show that this method can achieve the upper bound on the embedding efficiency of"±1 steganography" when the employed binary covering codes reach the upper bound on that of LSB steganography. Applications using random and structured covering codes show that the new method outperforms previous ones and can approach the upper bound. [ABSTRACT FROM AUTHOR]

Three-dimensional (3-D) meshes are commonly used to represent virtual surfaces and volumes. Over the past decade, 3-D meshes have emerged in industrial, medical, and entertainment applications, being of large practical significance for 3-D mesh steganography and steganalysis. In this article, we provide a systematic survey of the literature on 3-D mesh steganography and steganalysis. Compared with an earlier survey (Girdhar et al., 2017), we propose a new taxonomy of steganographic algorithms with four categories: 1) two-state domain, 2) LSB domain, 3) permutation domain, and 4) transform domain. Regarding steganalysis algorithms, we divide them into two categories: 1) universal steganalysis and 2) specific steganalysis. For each category, the history of technical developments and the current technological level are introduced and discussed. Finally, we highlight some promising future research directions and challenges in improving the performance of 3-D mesh steganography and steganalysis. [ABSTRACT FROM AUTHOR]

ZigBee is one of the communication protocols used in the Internet of Things (IoT) applications. In typical deployment scenarios involving low-cost and low-power IoT devices, many communication features are disabled, consequently affecting the security offered by ZigBee. The ZigBee specification assumes that deployment of frame counters is sufficient to mitigate replay attacks in secure ZigBee networks. However, we demonstrate that it is insufficient in this paper (i.e., the network is no longer secure after the coordinator restarts). As a countermeasure, we present a timestamp-based scheme to mitigate replay attacks. Our mitigation strategy does not consume power significantly, and fully powered devices will be responsible for providing power-constrained devices with the current timestamp. The proposed scheme is designed for all ZigBee topologies and different states of ZigBee End Devices (ZEDs). Findings from our evaluation show that the proposed scheme can successfully mitigate replay attacks, with no significant network performance degradation even assuming a worst-case scenario (i.e., many devices are sending data simultaneously). [ABSTRACT FROM AUTHOR]

Mobile crowdsensing (MCS) systems typically struggle to address the challenge of data aggregation, incentive design, and privacy protection, simultaneously. However, existing solutions usually focus on one or, at most, two of these issues. To this end, this paper presents CROWD FA, a novel paradigm for privacy-preserving MCS through federated analytics (FA), which aims to achieve a well-rounded solution encompassing data aggregation, incentive design, and privacy protection. Specifically, inspired by FA, CROWD FA initiates an MCS computing paradigm that enables data aggregation and incentive design. Participants can perform aggregation operations on their local data, facilitated by CROWD FA, which supports various common data aggregation operations and bidding incentives. To address privacy concerns, CROWD FA relies solely on an efficient cryptographic primitive known as additive secret sharing to simultaneously achieve privacy-preserving data aggregation and privacy-preserving incentive. To instantiate CROWD FA, this paper presents a privacy-preserving data aggregation scheme (PRADA) based on CROWD FA, capable of supporting a range of data aggregation operations. Additionally, a CROWD FA-based privacy-preserving incentive mechanism (PRAED) is designed to ensure truthful and fair incentives for each participant, while maximizing their individual rewards. Theoretical analysis and experimental evaluations demonstrate that CROWD FA protects participants’ data and bid privacy while effectively aggregating sensing data. Notably, CROWD FA outperforms state-of-the-art approaches by achieving up to 22 times faster computation time. [ABSTRACT FROM AUTHOR]

The unprecedented growth in the number of mobile data and connected machines ever-fast approaches limits of fourth generation technologies to address this enormous data demand. Therefore, the development of the fifth generation (5G) wireless communication technologies is a priority issue currently. The evolution towards 5G wireless communications will be a cornerstone for realizing the future human-centric and connected machine-centric networks, which achieve near-instantaneous, zero distance connectivity for people and connected machines. On the other hand, wireless networks have been widely used in civilian and military applications and become an indispensable part of our daily life. People rely heavily on wireless networks for transmission of important/private information, such as credit card information, energy pricing, e-health data, command, and control messages. Therefore, security is a critical issue for future 5G wireless networks. Physical layer security techniques can be used to either perform secure data transmission directly or generate the distribution of cryptography keys for conventional cryptography techniques in the 5G networks. With careful management and implementation, physical layer security can be used as an additional level of protection on top of the existing security schemes. As such, they will formulate a well-integrated security solution together that efficiently safeguards the confidential and privacy communication data in 5G wireless networks. The main goal of this IEEE JSAC Special Issue on “Physical Layer Security for 5G Wireless Networks” is to bring together leading researchers in both academia and industry from diversified backgrounds to advance the theory and practice of physical layer security for 5G wireless networks. [ABSTRACT FROM AUTHOR]

This paper provides upper and lower bounds on the optimal guessing moments of a random variable taking values on a finite set when side information may be available. These moments quantify the number of guesses required for correctly identifying the unknown object and, similarly to Arikan’s bounds, they are expressed in terms of the Arimoto-Rényi conditional entropy. Although Arikan’s bounds are asymptotically tight, the improvement of the bounds in this paper is significant in the non-asymptotic regime. Relationships between moments of the optimal guessing function and the MAP error probability are also established, characterizing the exact locus of their attainable values. The bounds on optimal guessing moments serve to improve non-asymptotic bounds on the cumulant generating function of the codeword lengths for fixed-to-variable optimal lossless source coding without prefix constraints. Non-asymptotic bounds on the reliability function of discrete memoryless sources are derived as well. Relying on these techniques, lower bounds on the cumulant generating function of the codeword lengths are derived, by means of the smooth Rényi entropy, for source codes that allow decoding errors. [ABSTRACT FROM PUBLISHER]

E-healthcare as a significant facet of the Internet of Things (IoT) relies on wearable devices to continuously monitor users’ vital signals for health-related purposes. The sensitive and vast nature of the collected data necessitate secure encryption and storage on the cloud. Simultaneously, there is a need to share these data for healthcare purposes. How to balance the privacy and usability of these data is a challenging problem in the e-healthcare applications. A central problem arose from the continuous data collection is how to effectively share the data collected in one specific time period when users are unwell. We formalize it as the sequential data sharing problem. This problem appears in various IoT applications apart from e-healthcare, such as video surveillance. In this paper, we explain why all existing solutions cannot address the above problem. Then, we propose a novel sequential data sharing system (SDSS), where the data encrypted at any specific time period can be efficiently shared. We first present a practical construction of SDSS that supports securely sharing data within one specific time period in a symmetric manner. The decryption key are retrieved sequentially by utilizing the shared key and hash function. All involved calculations in the system are lightweight. Data pertaining to other non-selected time periods remain unknown. We then extend the SDSS to a multiple-range version, enabling simultaneous sharing data for multiple specific time periods, and show an example. We formalize the definition of security models and analyze the security of our systems. Finally, we evaluate the performance of our systems using SHA-256 and AES-256. Experimental results demonstrate that our systems are highly efficient. It takes less than 1 millisecond to encrypt 100KB data and less than 0.4 milliseconds to decrypt the corresponding cipher data. Our proposed systems provide a solution to balance the privacy and usability in the context of sequentially collected data. We believe that this work will enhance the adoption and practicality of IoT applications. [ABSTRACT FROM AUTHOR]

With the growing use of mobile devices, location-based services (LBS) are becoming increasingly popular. BLS deliver accurate services to individuals according to their geographical locations, but privacy issues have been the primary concerns of users. Privacy-preserving LBS (PPLBS) were proposed to protect location privacy, but there are still some problems: 1) a semi-trusted third party (STTP) is required to blur users’ locations; 2) both the computation and communication costs of generating a query are linear with the size of queried areas; 3) the schemes were not formally treated, in terms of definition, security model, security proof, etc. In this paper, to protect location privacy and improve query efficiency, an oblivious location-based services (OLBS) scheme is proposed. Our scheme captures the following features: 1) an STTP is not required; 2) users can query services without revealing their exact location information; 3) the service provider only knows the size of queried areas and nothing else; and 4) both the computation and communication costs of generating a query is constant, instead of linear with the size of queried areas. We formalise both the definition and security model of our OLBS scheme, and propose a concrete construction. Furthermore, the implementation is conducted to show its efficiency. The security of our scheme is reduced to well-known complexity assumptions. The novelty is to reduce the computation and communication costs of generating a query and enable the service provider to obliviously generate decrypt keys for queried services. This contributes to the growing work of formalising PPLBS schemes and improving query efficiency. [ABSTRACT FROM AUTHOR]

Constacyclic codes are well-known generalizations of cyclic and negacyclic codes. Due to their rich algebraic structure, constacyclic codes are used to construct quantum codes and symbol-pair codes. Let ${\mathbb {F}}_{q}$ be a finite field with order $q$ , where $q$ is a positive power of a prime $p$. Suppose that $n$ is a positive integer and the product of distinct prime factors of $n$ divides $q-1$ , i.e., $rad(n)\mid (q-1)$. In this paper, we explicitly factorize the polynomial $x^{n}-\lambda $ for each $\lambda \in {\mathbb {F}}_{q}^{*}$. As applications, first, we obtain all repeated-root $\lambda $ -constacyclic codes and their dual codes of length $np^{s}$ over ${\mathbb {F}}_{q}$ ; second, we determine all simple-root LCD cyclic codes and LCD negacyclic codes of length $n$ over ${\mathbb {F}}_{q}$ ; third, we list all self-dual repeated-root negacyclic codes of length $np^{s}$ over ${\mathbb {F}}_{q}$. In contrast to known results, the lengths of constacyclic codes in this paper have more flexible parameters. [ABSTRACT FROM AUTHOR]

An improved and extended version of a quaternion-based lossless encryption technique for digital image and communication on medicine (DICOM) images is proposed. We highlight and address several security flaws present in the previous version of the algorithm originally proposed by Dzwonkowski et al. (2015). The newly proposed secure quaternion Feistel cipher (S-QFC) algorithm retains the concept of a modified Feistel network with modular arithmetic and the use of special properties of quaternions to perform rotations of data sequences in 3D space for each of the cipher rounds. A new and more secure key generation scheme based on quaternion Julia sets is utilized. We also introduce both-sided modular matrix multiplications for the encryption and decryption processes. The proposed S-QFC algorithm eliminates the major security flaws of its predecessor while maintaining high computation speed in comparison to other algorithms originally embedded in DICOM (i.e., advanced encryption standard and triple data encryption standard). A computer-based analysis has been carried out. Simulation results and cryptanalysis are shown at the end of this paper. [ABSTRACT FROM AUTHOR]

We revisit and take a closer look at a (not so well known) result of a 2017 paper, showing that the differential uniformity of any vectorial function is bounded from below by an expression depending on the size of its image set. We make explicit the resulting tight lower bound on the image set size of differentially $\delta $ -uniform functions (which is the only currently known non-trivial lower bound on the image set size of such functions). We also significantly improve an upper bound on the nonlinearity of vectorial functions obtained in the same reference and involving their image set size. We study when the resulting bound is sharper than the covering radius bound. We obtain as a by-product a lower bound on the Hamming distance between differentially $\delta $ -uniform functions and affine functions, which we improve significantly with a second bound. This leads us to study what can be the maximum Hamming distance between vectorial functions and affine functions. We provide an upper bound which is slightly sharper than a bound by Liu, Mesnager and Chen when $m < n$ , and a second upper bound, which is much stronger in the case (happening in practice) where $m$ is near $n$ ; we study the tightness of this latter bound; this leads to an interesting question on APN functions, which we address (negatively). We finally derive an upper bound on the nonlinearity of vectorial functions by means of their Hamming distance to affine functions and make more precise the bound on the differential uniformity which was the starting point of the paper. [ABSTRACT FROM AUTHOR]

A classical method of constructing a linear code over \mathrm GF(q) with a $t$ -design is to use the incidence matrix of the $t$ -design as a generator matrix over \mathrm GF(q) of the code. This approach has been extensively investigated in the literature. In this paper, a different method of constructing linear codes using specific classes of 2-designs is studied, and linear codes with a few weights are obtained from almost difference sets, difference sets, and a type of 2-designs associated to semibent functions. Two families of the codes obtained in this paper are optimal. The linear codes presented in this paper have applications in secret sharing and authentication schemes, in addition to their applications in consumer electronics, communication and data storage systems. A coding-theory approach to the characterization of highly nonlinear Boolean functions is presented. [ABSTRACT FROM AUTHOR]

This article presents the results of a systematic review of the literature pertaining to the use of blockchain technology in the engineering and manufacturing activities. The uses of blockchain have been growing quickly in the literature, and this fast pace can make it difficult for researchers to keep abreast of the state of the art. Using a systematic approach to search the primary electronic indices, the compiled list of papers is then analyzed and a number of themes are identified. The results of this article suggest that the literature surrounding blockchain and the engineering/manufacturing industry can be categorized into three primary groups: blockchain to protect data validity, blockchain to enhance inter and intraorganizational communications, and blockchain to increase the efficiency of the manufacturing process. Within each top-level theme, there exist some subthemes that provide a more finely defined categorization of the papers contained in that theme. These subthemes include specific areas of blockchain application such as additive manufacturing, cloud manufacturing, and building information models (BIMs). For each group of papers identified, each study is discussed briefly. This article concludes with a set of conclusions about the current state of the literature and suggestions for further research directions. The primary contribution of this article is to provide a foundation upon which additional research can be accomplished as well as to provide a resource for practitioners to help them understand the current state of the industry and help them determine how blockchain might be beneficial to their organization. [ABSTRACT FROM AUTHOR]

Reliably and power efficiently securing integrated systems against advanced power analysis attacks (PAAs) is a significant design challenge in modern integrated circuits. Power masking and hiding are typical countermeasures for increasing system resilience for power attacks at the expense of the overall system performance and power efficiency. These method are, however, not able to alert the user or trigger additional protective actions in case of the attack. In this paper, a method for detecting power attacks in real-time is proposed. The proposed approach exploits statistical methods to analyze the on-chip voltage variations across an on-chip power grid and detect the attacker probe connected to the system. The problem of the full security coverage of the power grid is formulated and solved in this paper. Adjusting the density of the on-chip sensors and exploiting sparse analysis techniques is considered to simultaneously enhance the accuracy and power efficiency of the proposed solution. The proposed attack detection system is designed, simulated, and evaluated in Simulink based on IBM microprocessor benchmark data. Machine learning (ML) models are trained in Python and with scikit-learn ML library. The proposed system has been demonstrated to efficiently detect PAA within a period of time that is orders of magnitude shorter than a typical attack duration length. The system is expected to exhibit high detection accuracy and power efficiency across a wide spectrum of integrated systems. [ABSTRACT FROM AUTHOR]

The energy blockchain is a distributed Internet protocol for energy transactions between nodes of a power system. Recent applications of the energy blockchain in microgrids only consider the energy transactions between peers without considering the technical issues that can arise, especially when the system is islanded. One contribution of the paper is, thus, to depict a comprehensive framework of the technical and economic management of microgrids in the blockchain era, considering, for the first time, the provision of ancillary services and, in particular, of the voltage regulation service. When more PV nodes are operating in the grid, large reactive power flows may appear in the branches. In order to limit such flows, a reactive optimal power flow (R-OPF) is solved, setting the voltage at the PV buses as variables within prescribed limits. Each PV generator will thus contribute to voltage regulation, receiving a remuneration included in the transaction and certified by the blockchain technology. For showing how this system can work, a test microgrid, where some energy transactions take place, has been considered. For each transaction, the R-OPF assigns the reactive power to the PV buses. The R-OPF is solved by a glow-worm swarm optimizer. Finally, the paper proposes a method for remuneration of reactive power provision; this method, integrated into the blockchain, allows evaluating the contribution to voltage regulation and increases the transparency and cost traceability in the transactions. The application section shows the implementation of a Tendermint-based energy transaction platform integrating R-OPF and the earlier cited technical assessments. [ABSTRACT FROM AUTHOR]

This paper studies the low-SNR regime performance of a scalar complex $K$ -user interference channel with the Gaussian noise. The finite bandwidth case is considered, where the low-SNR regime is approached by letting the input power go to zero, while the bandwidth is small and fixed. We show that for all $\delta >0$ , there exists a set of channel coefficients with non-zero measure (probability), in which the wideband slope per user satisfies $ \mathcal {S}_{0}< {\scriptstyle {}^{\scriptstyle 2}}\hspace{-0.224em}/\hspace{-0.112em}{\scriptstyle K}+\delta $. This is quite contrary to the large bandwidth case, where a slope of 1 per user is achievable with probability 1. We also develop an interference alignment scheme for the finite bandwidth case that shows some gain in wideband slope. [ABSTRACT FROM AUTHOR]

Complexity of sequences plays an important role in pseudorandom sequences and cryptography. In this paper, we present a construction of sequences with high nonlinear complexity from function fields. The main idea is to make use of function fields with many rational places as well as an automorphism of large order. We illustrate our construction through rational function fields and cyclotomic function fields in which there exist some automorphisms of large order. It turns out that we are able to: 1) slightly increase the length of the inversive sequence without losing nonlinear complexity and 2) obtain sequences with much larger nonlinear complexity than random sequences. [ABSTRACT FROM AUTHOR]

In this paper, we apply two-to-one functions over F2n in two generic constructions of binary linear codes. We consider two-to-one functions in two forms: (1) generalized quadratic functions; and (2) (x2t + x)e with gcd (t, n) = gcd(e, 2n−1) = 1. Based on the study of the Walsh transforms of those functions or their variants, we present many classes of linear codes with few nonzero weights, including one weight, three weights, four weights, and five weights. The weight distributions of the proposed codes with one weight and with three weights are determined. In addition, we discuss the minimum distance of the dual of the constructed codes and show that some of them achieve the sphere packing bound. Moreover, examples show that some codes in this paper have best-known parameters. [ABSTRACT FROM AUTHOR]

The goal of image steganography is to hide a full-sized image, termed secret, into another, termed cover. Prior image steganography algorithms can conceal only one secret within one cover. In this paper, we propose an adaptive local image steganography (AdaSteg) system that allows for scale- and location-adaptive image steganography. By adaptively hiding the secret on a local scale, the proposed system makes the steganography more secured, and further enables multi-secret steganography within one single cover. Specifically, this is achieved via two stages, namely the adaptive patch selection stage and secret encryption stage. Given a pair of secret and cover, first, the optimal local patch for concealment is determined adaptively by exploiting deep reinforcement learning with the proposed steganography quality function and policy network. The secret image is then converted into a patch of encrypted noises, resembling the process of generating adversarial examples, which are further encoded to a local region of the cover to realize a more secured steganography. Furthermore, we propose a novel criterion for the assessment of local steganography, and also collect a challenging dataset that is specialized for the task of image steganography, thus contributing to a standardized benchmark for the area. Experimental results demonstrate that the proposed model yields results superior to the state of the art in both security and capacity. [ABSTRACT FROM AUTHOR]

Spatial crowdsourcing (SC) allows requesters to crowdsource tasks to workers based on location proximity. To preserve privacy, the location should not be disclosed to untrustworthy entities (even the SC platform). Previous solutions to preserve workers’ location privacy require an online trusty third party (TTP), which is not practical in reality. In this paper, we design a framework that allows the SC platform to assign tasks to nearest workers in an online manner without knowing their actual locations. We propose an encryption algorithm to encrypt the locations of tasks and workers, and design an indexing method that assigns tasks to workers without losing too much privacy. We prove that there exists a trade-off between efficiency and security theoretically, which can be controlled based on user preference. We verify our method on real-world datasets and experimental results show that our method is efficient, effective and practical. [ABSTRACT FROM AUTHOR]

XOR-AND Graphs (XAGs) are an enrichment of the classical AND-Inverter Graphs (AIGs) with XOR nodes. In particular, XAGs are networks composed by ANDs, XORs, and inverters. Besides several emerging technologies applications, XAGs are often exploited in cryptography-related applications based on the multiplicative complexity of a Boolean function. The multiplicative complexity of a function is the minimum number of AND gates (i.e., multiplications) that are sufficient to represent the function over the basis {AND, XOR, NOT}. In fact, the minimization of the number of AND gates is important for high-level cryptography protocols such as secure multiparty computation, where processing AND gates is more expensive than processing XOR gates. Moreover, it is an indicator of the degree of vulnerability of the circuit, as a small number of AND gates corresponds to a high vulnerability to algebraic attacks. In this paper we study the multiplicative complexity of Boolean functions characterized by two particular regularities, called autosymmetry and D-reducibility. Moreover, we exploit these regularities for decreasing the number of AND nodes in XAGs. The experimental results validate the proposed approaches. [ABSTRACT FROM AUTHOR]

JPEG steganalysis aims to detect stego JPEG images. For some robust steganography methods, in order to enhance stego images’ robustness of resisting JPEG recompression from lossy channel such SNS or photo sharing websites, steganographer may intentionally recompress cover image several times with quantization matrix of targeted channel, which thereby make it possible to transmit stego data in such channel for better disguise. In addition, there are huge number of cover JPEG images may be recompressed for various reasons, such as processing by some tools. Thus a better steganalysis method for such images is needed. In this paper, we investigate the steganalysis method for images recompressed with the same quantization matrix, namely, discriminate recompressed JPEG cover images and its stego images. We present some observed phenomenon on recompressed JPEG images, and design methods to enhance the sensitivity of feature based and deep model based steganalysis methods for this task. To verify their effectiveness with different acquisition of recompression prior-knowledge, we conduct experiments in various settings including conventional setting and mixing samples of different recompressing times in training. Their results demonstrate that the proposed method can notably improve detection accuracy on recompressed JPEG images. [ABSTRACT FROM AUTHOR]

ChaCha has been one of the most prominent ARX designs of the last few years because of its use in several systems. The cryptanalysis of ChaCha involves a differential attack that exploits the idea of Probabilistic Neutral Bits (PNBs). For a long period, the single-bit distinguisher in this differential attack was found up to 3rd round. At Crypto 2020, Beierle et al. introduced for the first time the single bit distinguishers for 3.5th round, which contributed significantly to regaining the flow of the research work in this direction. This discovery became the primary factor behind the huge improvement in the key recovery attack complexity in that work. This was followed by another work at Eurocrypt 2021, where a single bit distinguisher at 3.5th round helped to produce a 7th round distinguisher of ChaCha and a further improvement in the key recovery. In this paper, first, we provide the theoretical framework for the distinguisher given by Beierle et al. We mathematically derive the observed differential correlation for the particular position where the output difference is observed at 3.5th round. Also, Beierle et al. mentioned the issue of the availability of proper IVs to produce such distinguishers, and pointed out that not all keys have such IVs available. Here we provide a theoretical insight of this issue. Next, we revisit the work of Coutinho et al. (Eurocrypt 2021). Using Differential-Linear attacks against ChaCha, they claimed the distinguisher and the key recovery with complexities 2218 and $2^{228.51}$ respectively. We show that the differential correlation for the 3.5th round is much smaller than the claim of Coutinho et al. This makes the attack complexities much higher than their claim. [ABSTRACT FROM AUTHOR]

Sensor communication in the smart home environment is still in its infancy as the information exchange between sensors is vulnerable to security threats. Many traditional solutions use single-layer or multi-layer (i.e., onion routing protocol) encryption/decryption algorithms. But, in the traditional onion routing protocol, if the directory server is compromised, it may not track the malicious onion nodes within the onion network. It questioned the path anonymity of the onion routing protocol. Motivated by this, we proposed a blockchain and onion routing (OR)-based secure and trusted framework in the paper. The anonymity of the proposed OR network is maintained by storing and tracking the onion nodes threshold values through the blockchain network. A long short-term memory (LSTM) model is also utilized to classify the sensors data requests as malicious and non-malicious. The performance of the proposed system is evaluated with different performance metrics such as F1 score and accuracy. The LSTM model significantly improves the initial detection rate of malicious data requests from smart home sensors. Over these benefits, we considered the entire communication via 6G channel, reducing the overall communication latency. Additionally, the OR network is simulated over the shadow simulator to analyze the OR network’s performance considering parameters such as packet delivery ratio and malicious onion node detection rate. [ABSTRACT FROM AUTHOR]

Besides developing new Cooperative, Connected and Automated Mobility (CCAM) services for the improvement of road safety and travel experience, researchers are considering protection mechanisms to ensure the security of these services and the safety of involved users (drivers but also, e.g., cyclists and pedestrians). In particular, several Identity Management (IDM) protocols have been designed as the first line of defence against external attackers. Among these protocols, a promising trend in research consists in the use of a Smart Card (SC) as a technical enabler for strong authentication. Indeed, many SC-based IDM protocols for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications in real-time CCAM services have been proposed in the literature which present interesting features and promising usability experimental results. However, this research line is far from being exhausted, especially considering the recent spread of SC technologies and use cases. For this reason, in this paper we propose a systematic literature review on SC-based IDM protocols for real-time CCAM services. In particular, we identify characterising assumptions of CCAM scenarios and extrapolate a unified high-level view of the steps composing a SC-based IDM protocol. Then, we present a detailed survey of several SC-based IDM protocols. Finally, we identify trends in research and formulate guidelines and useful recommendations to provide a solid base which researchers can use as a starting point for the design of new and improved SC-based IDM protocols for CCAM scenarios. [ABSTRACT FROM AUTHOR]

Internet of Vehicles (IoV) is a variant of Vehicular Ad-Hoc Network (VANET), it is being developed as an important communication way between vehicles. However, when some traffic messages are collected in IoV, these messages are usually linked to specific identifiable information. Therefore, there exists the privacy-preserving problem of vehicular identities in IoV. On the other hand, if the private information of vehicles is fully protected in IoV, then the true vehicular identities cannot be determined because the transferred messages are not related with the specific information of vehicles. Then it will also lead to more security problems in IoV. Additionally, fog computing seamlessly integrates heterogeneous computing resources widely distributed in edge networks and then provides stronger computing services for users. Therefore, in this paper we propose a decentralized traceable privacy-preserving scheme for vehicular identity in fog computing-based IoV, where our scheme uses multiple fog servers to trace the specific identity and most likely trajectory of a vehicle by the collected data under certain conditions. In our scheme, the true identity of a vehicle is hidden to some related parameters generated by the certificate authority; further the secret sharing scheme is used to hide and trace the true identity of a vehicle. We construct a voting mechanism to generate the most reliable fog server, which is able to calculate the true identity and corresponding trajectory of a vehicle by reconstructing the polynomial based on the secret sharing scheme. Additionally, we analyze that our scheme can satisfy the security requirements, and formally prove that the data collection procedure is secure under the real-or-random model. Also, the experimental results show our scheme is efficient in IoV. [ABSTRACT FROM AUTHOR]

The family of Goppa codes is one of the most interesting subclasses of linear codes. As the McEliece cryptosystem often chooses a random Goppa code as its key, knowledge of the number of inequivalent Goppa codes for fixed parameters may facilitate in the evaluation of the security of such a cryptosystem. In this paper we present a new approach to give an upper bound on the number of inequivalent extended irreducible binary Goppa codes. To be more specific, let $n>3$ be an odd prime number and $q=2^{n}$ ; let $r\geq 3$ be a positive integer satisfying $\gcd (r,n)=1$ and $\gcd \big (r,q(q^{2}-1)\big)=1$. We obtain an upper bound for the number of inequivalent extended irreducible binary Goppa codes of length $q+1$ and degree $r$. [ABSTRACT FROM AUTHOR]

This paper proposes a discrete Gaussian sampling hardware design that can flexibly support different sampling parameters, that is more efficient (in area-delay product) compared to the majority of earlier proposals, and that has constant execution time. The proposed design implements a Cumulative Distribution Table (CDT) approach, reduces the table size with Gaussian convolutions, and adopts an innovative fusion tree search algorithm to achieve a compact and fast sampling technique—to our best knowledge, this is the first hardware implementation of fusion tree search algorithm. The proposed hardware can support all the discrete Gaussian distributions used in post-quantum digital signatures and key encapsulation algorithms (FALCON, qTESLA, and FrodoKEM), the homomorphic encryption library of SEAL, and other algorithms such BLISS digital signature and LP public-key encryption. Our proposed hardware can be configured at design-time to optimize a single configuration or at run-time to support multiple Gaussian distribution parameters. Our design, furthermore, has constant-time behavior by design, eliminating timing side-channel attacks—this is achieved by reading all table contents at the same time to also reduce the latency. The results on a Xilinx Virtex-7 FPGA show that our solution can outperform all prior proposals in area-delay product by 1.67–235.88×, only falling short to those designed for the LP encryption scheme. [ABSTRACT FROM AUTHOR]

This paper initiates the study of “Cryptophasia in Hardware” – a phenomenon that allows hardware circuits/devices with no pre-established secret keys to securely exchange secret information over insecure communication networks. The study of cryptophasia is motivated by the need to establish secure communication channels between lightweight resource-constrained devices incapable of securely storing cryptographic keys and/or executing resource-intensive cryptographic protocols. In this paper, we introduce a novel concept called Physically Related Functions (PReFs) that can exchange secret information in a secure and authenticated manner over insecure networks. This function can be visualized as an abstraction of Strong Physically Unclonable Functions (PUFs). Strong PUFs have the limitation in communicating between two identical devices, an issue that we address in the definition of PReFs. We describe a formal framework for analyzing the functional and security requirements of PReFs. In this framework, we present a lightweight (in terms of computation cost) yet provably secure authenticated key-exchange protocol that relies only on PReFs and makes no additional assumptions (such as secure storage of cryptographic keys). Finally, we present a proof-of-concept realization of PReFs in hardware over Digilent Cora Z7 – a low-cost development platform (consisting of an ARM Cortex processor and a Xilinx FPGA) that is particularly suitable for real-world IoT applications involving resource-constrained devices. We validate that our realization of PReFs satisfies all the properties warranted by our formal framework. We further demonstrate the efficacy of our proposed protocol by analyzing its performance (in terms of computational and communication latency) over the Digilent Cora Z7 platform. [ABSTRACT FROM AUTHOR]

Over the past few years, Domain Name Service (DNS) remained a prime target for hackers as it enables them to gain first entry into networks and gain access to data for exfiltration. Although the DNS over HTTPS (DoH) protocol has desirable properties for internet users such as privacy and security, it also causes a problem in that network administrators are prevented from detecting suspicious network traffic generated by malware and malicious tools. To support their efforts in maintaining a secure network, in this paper, we have implemented an explainable AI solution using a novel machine learning framework. We have used the publicly available CIRA-CIC-DoHBrw-2020 dataset for developing an accurate solution to detect and classify the DNS over HTTPS attacks. Our proposed balanced and stacked Random Forest achieved very high precision (99.91%), recall (99.92%) and F1 score (99.91%) for the classification task at hand. Using explainable AI methods, we have additionally highlighted the underlying feature contributions in an attempt to provide transparent and explainable results from the model. [ABSTRACT FROM AUTHOR]

Although many network traffic protection methods have been developed to protect user privacy, encrypted traffic can still reveal sensitive user information with sophisticated analysis. In this paper, we propose ETC-PS, a novel encrypted traffic classification method with path signature. We first construct the traffic path with a session packet length sequence to represent the interactions between the client and the server. Then, path transformations are conducted to exhibit its structure and obtain different information. A multiscale path signature is finally computed as a kind of distinctive feature to train the traditional machine learning classifier, which achieves highly robust accuracy and low training overhead. Six publicly available datasets with different traffic types of HTTPS/1, HTTPS/2, QUIC, VPN, non-VPN, Tor, and non-Tor are used to conduct closed-world and open-world evaluations to verify the effectiveness of ETC-PS. The experimental results demonstrate that ETC-PS is superior to the state-of-the-art methods in terms of accuracy, $f_{1}$ score, time complexity, and stability. [ABSTRACT FROM AUTHOR]

Although significant progress has been achieved recently in automatic learning of steganographic cost, the existing methods designed for spatial images cannot be directly applied to JPEG images which are more common media in daily life. The difficulties of migration are mainly caused by the characteristics of the $8\times 8$ DCT mode structure. To address the issue, in this paper we extend an existing automatic cost learning scheme to JPEG, where the proposed scheme called JEC-RL (JPEG Embedding Cost with Reinforcement Learning) is explicitly designed to tailor the JPEG DCT structure. It works with the embedding action sampling mechanism under reinforcement learning, where a policy network learns the optimal embedding policies via maximizing the rewards provided by an environment network. Following a domain-transition design paradigm, the policy network is composed of three modules, i.e., pixel-level texture complexity evaluation module, DCT feature extraction module, and mode-wise rearrangement module. These modules operate in serial, gradually extracting useful features from a decompressed JPEG image and converting them into embedding policies for DCT elements, while considering JPEG characteristics including inter-block and intra-block correlations simultaneously. The environment network is designed in a gradient-oriented way to provide stable reward values by using a wide architecture equipped with a fixed preprocessing layer with $8\times 8$ DCT basis filters. Extensive experiments and ablation studies demonstrate that the proposed method can achieve good security performance for JPEG images against both advanced feature-based and modern CNN-based steganalyzers. [ABSTRACT FROM AUTHOR]

Polynomial multiplication is one of the most rigorous arithmetic construction of postquantum cryptosystems. Utilizing number-theoretic transformations, the product of such multiplication can be efficiently computed in quasi-linear time $O(n.lgn)$. Error detection schemes of number-theoretic transform (NTT) architectures are essential to ensure correct mathematical operations, improved security, and thwart active side-channel attacks mounted through faults. NTT is not only significant to post-quantum cryptosystems, but the structure is also valuable to the already existing security protocols, e.g., signature schemes, hash functions, and the like. This paper, for the first time, introduces new error detection schemes of NTT architectures, successfully detecting both permanent and transient faults. Our schemes are based on recomputing with negated, scaled, and swapped operands. We have implemented the proposed schemes on the application-specific integrated circuit (ASIC). Performance and implementation metrics on this hardware platform show acceptable hardware overhead. As our schemes provide acceptable complexity and high efficiency, they can be utilized in compact hardware implementations of constrained applications, e.g., deeply embedded architectures. [ABSTRACT FROM AUTHOR]

Recently, multiple ($k, n$) region-incrementing VCSs (RIVCSs) have been proposed that can gradually reconstruct secrets in a single image. In ($k, n$)-RIVCS, the secret image is subdivided into multiple regions in such a way that any $t$ shadow images, where $k \le t \le n$ , can be used to reveal the secret in the ($t-k+1$)th region. This region-incrementing property provides progressive decoding. However, the regions in previous RIVCSs are disjointed: no two regions have overlapping areas. In this paper, we discuss a ($k, n$) region-in-region progressive VCS (RPVCS). Our ($k, n$)-RPVCS has ($n-k+1$) secrecy-level regions, and each region can be located within any previous region. This new type of region allocation not only provides more areas in which to hide the secret compared with the non-overlapping regions in RIVCS but also provides different presentation methods in progressive decoding. [ABSTRACT FROM AUTHOR]

This paper shows how arrays of coupled resonant oscillators can provide wildly disordered phase responses corresponding to nonsynchronized regimes. The unpredictability of their time response makes oscillator arrays attractive randomness sources for cryptographic applications. We describe a possible implementation of a random number generator (RNG) combining the proposed randomness source with a few low cost elements needed for bit stream generation. Several bit stream sequences are simulated with a numerically efficient phase-domain model able to include oscillator phase noise and parameters variability. The randomness of the generated bit streams are checked with the tests provided by the National Institute of Standards and Technology. Our results show that the statistical properties of the proposed RNG are indeed resilient to temperature-induced thermal noise variations as well as to the statistical uncertainty of oscillating frequencies and coupling strengths. [ABSTRACT FROM AUTHOR]

This paper considers a distributed storage system, where multiple storage nodes can be reconstructed simultaneously at a centralized location. This centralized multi-node repair (CMR) model is a generalization of regenerating codes that allow for bandwidth efficient repair of a single-failed node. This paper focuses on the tradeoff between the amount of data stored and repair bandwidth in the CMR model. In particular, repair bandwidth bounds are derived for the minimum storage multi-node repair (MSMR) and the minimum bandwidth multi-node repair (MBMR) operating points. The tightness of these bounds is analyzed via code constructions. The MSMR point is characterized by codes achieving this point under functional repair for the general set of CMR parameters, as well as with codes enabling exact repair for certain CMR parameters. The MBMR point, on the other hand, is characterized with exact repair codes for all CMR parameters for systems that satisfy a certain entropy accumulation property. Finally, the model proposed here is utilized for the secret sharing problem, where the codes for the multi-node repair problem are used to construct communication efficient secret sharing schemes with the property of bandwidth efficient share repair. [ABSTRACT FROM AUTHOR]

High-performance steganography requires large embedding rate and small distortion, i.e., high embedding efficiency. Steganographic codes (stego-codes) derived from covering codes can improve embedding efficiency. In this paper, a new method is proposed to construct binary stego-codes for LSB embedding in gray-scale signals, which shows that not just one but a family of stego-codes can be generated from a covering code by combining Hamming codes and wet paper codes. This method can greatly expand the set of embedding schemes as applied to steganography. Performances of stego-code families (SCF) of structured codes and random codes are analyzed. SCFs of random codes can approach the rate-distortion bound on LSB embedding for any chosen embedding rate. Furthermore, SCFs are modified for applications in ±1 embedding, and a treble layered embedding method for ±2 embedding is obtained. By combining the modified SCFs and the treble layered method, a near-optimal scheme for ±2 embedding is presented. [ABSTRACT FROM AUTHOR]

In this paper, a class of binary three-weight linear codes is constructed. Their dual codes are also studied. The dual codes are either optimal or almost optimal. These codes have applications in authentication codes, secret sharing schemes, and association schemes, in addition to their applications in consumer electronics and communication and data storage systems. [ABSTRACT FROM PUBLISHER]