In this work, we present a configurable and side channel resistant implementation of the post-quantum key-exchange algorithm CRYSTALS-Kyber . The implemented design can be configured for different performance and area requirements leading to different trade-offs for different applications. A low area implementation can be achieved in 5,269 LUTs and 2,422 FFs, whereas a high performance implementation required 7,151 LUTs and 3,730 FFs. Due to a deeply pipelined architecture, a high operating speed of more than 250 MHz could be achieved on 28nm Xilinx FPGAs. The side channel resistance is implemented using a carefully chosen set of novel and known techniques such as Fault Detection Hashes, Instruction Randomization, FSM Protection and so on. resulting in a low overhead of less than 5% while being highly configurable. To the best of our knowledge, this work presents the first side-channel and fault attack protected configurable accelerator for CRYSTALS-Kyber . Using TVLA (test vector leakage assessment), we validate the implemented protection techniques and demonstrate that the design does not leak information even after 200 K traces. Furthermore, one of the configuration choices results in the smallest hardware implementation of CRYSTALS-Kyber known in the literature.

This article presents a thorough analysis of two distinct Physically Unclonable Functions (PUF), namely RO-PUF (Ring oscillator-based PUF) and RS-LPUF (RS Latch-based PUF), prototyped on FPGA. It is shown that the implemented PUFs possess significantly enhanced performance when compared to the state of the art. It is also identified that the enhancements are achieved through the incorporation of Programmable Delay Lines of FPGA Lookup Tables, the Temporal Majority Voting (TMV) scheme, and placed macro techniques for routing and placements of PUF units. The prototypes developed on Xilinx Artix-7 FPGAs are used for validation over the rated temperature range of 0-85° C with ±5% variation in the supply voltage. The proposed schemes when evaluated experimentally also achieve good uniformity, bit-aliasing, uniqueness, and reliability. Finally, it is shown that the proposed designs outperform the existing conventional PUFs in the area and speed tradeoff.

In 2016, Chang et al. proposed a Format Preserving Encryption (FPE) scheme over a finite field and used an MDS matrix in the diffusion layer of the scheme for optimal diffusion. Later that year, Gupta et al. defined an algebraic structure named Format Preserving Set (FPS) is the diffusion layer of an FPE scheme. In 2018, Barua et al. showed that it is not possible to construct an FPS over a finite field in the diffusion layer of an FPE scheme if the cardinality of the set is not a power of prime. They extended the search of FPS over a finite commutative ring$\mathcal {R}$and showed that if an FPS$S \subseteq \mathcal {R}$is closed under addition then it gets module structure over some subring of$\mathcal {R}$. Moreover, in this case, the only possible cardinalities of FPS are some power of the cardinalities of subrings when the module is free. The purpose of this article is twofold. Firstly, we show that it is possible to construct format preserving sets over a finite commutative ring which are not closed under addition. Secondly, we search for format preserving sets and MDS matrices over torsion modules. We provide examples of format preserving sets of cardinalities 26 and 52 over torsion modules and rings. These cardinalities are interesting because they correspond to the set of English alphabets, without and with capitalization. By considering a finite Abelian group as a torsion module over a PID, we show that a matrix$M$with entries from the PID is MDS if and only if$M$is MDS under the projection map on the same Abelian group.

Hardware-based security primitives play important roles in protecting and securing a system in Internet of Things (IoT) applications. The main primitives are physical unclonable functions (PUF) and true random number generator (TRNG) studied in this paper. Efficient FPGA implementation are proposed in the work along with relevant security analysis using prevalent metrics. Finally, an application of designed TRNG and PUF is proposed for implementing an authenticated key agreement protocol,

Threshold Implementation (TI) is one of the most widely used countermeasure for side channel attacks. Over the years several TI techniques have been proposed for randomizing cipher execution using different variations of secret-sharing and implementation techniques. For instance, sharing without decomposition (4-shares) is the most straightforward implementation of the threshold countermeasure. However, its usage is limited due to its high area requirements. On the other hand, sharing using decomposition (3-shares) countermeasure for cubic non-linear functions significantly reduces area and complexity in comparison to 4-shares. Nowadays, security of ciphers using a side channel countermeasure is of utmost importance. This is due to the wide range of security critical applications from smart cards, battery operated IoT devices, to accelerated crypto-processors. Such applications have different requirements (higher speed, energy efficiency, low latency, small area etc.) and hence need different implementation techniques. Although, many TI strategies and implementation techniques are known for different ciphers, there is no single study comparing these on a single cipher. Such a study would allow a fair comparison of the various methodologies. In this work, we present an in-depth analysis of the various ways in which TI can be implemented for a lightweight cipher. We chose GIFT for our analysis as it is currently one of the most energy-efficient lightweight ciphers. The experimental results show that different implementation techniques have distinct applications. For example, the 4-shares technique is good for applications demanding high throughput whereas 3-shares is suitable for constrained environments with less area and moderate throughput requirements. The techniques presented in the paper are also applicable to other blockciphers. For security evaluation, we performed TVLA (test vector leakage assessment) on all the design strategies. Experiments using up to 50 million traces show that the designs are protected against first-order attacks.

Breach in password databases has been a frequent phenomena in the software industry. Often these breaches go undetected for years. Sometimes, even the companies involved are not aware of the breach. Even after they are detected, publicizing such attacks might not always be in the best interest of the companies. This calls for a strong breach detection mechanism. Juels et al. (in ACM-CCS 2013) suggest a method called ‘Honeywords’, for detecting password database breaches. Their idea is to generate multiple fake passwords, called honeywords and store them along with the real password. Any login attempt with honeywords is identified as a compromise of the password database, since legitimate users are not expected to know the honeywords corresponding to their passwords. The key components of their idea are (i) generation of honeywords, (ii) typo-safety measures for preventing false alarms, (iii) alarm policy upon detection, and (iv) testing robustness of the system against various attacks. In this work, we analyze the limitations of existing honeyword generation techniques. We propose a new attack model called ‘Multiple System Intersection attack considering Input’. We show that the ‘Paired Distance Protocol’ proposed by Chakraborty et al., is not secure in this attack model. We also propose new and more practical honeyword generation techniques and call them the ‘evolving-password model’, the ‘user-profile model’, and the ‘append-secret model’. These techniques achieve ‘approximate flatness’, implying that the honeywords generated using these techniques are indistinguishable from passwords with high probability. Our proposed techniques overcome most of the risks and limitations associated with existing techniques. We prove flatness of our ‘evolving-password model’ technique through experimental analysis. We provide a comparison of our proposed models with the existing ones under various attack models to justify our claims.

In this article, we present a high-performance hardware architecture for Elliptic curve based (authenticated) key agreement protocol “Elliptic Curve Menezes, Qu and Vanstone” (ECMQV) over Binary Edwards Curve (BEC). We begin by analyzing inversion module on a 251-bit binary field. Subsequently, we present Field Programmable Gate Array (FPGA) implementations of the unified formula for computing elliptic curve point addition on BEC in affine and projective coordinates and investigate the relative performance of these two coordinates. Then, we implement the w -coordinate based differential addition formulae suitable for usage in Montgomery ladder. Next, we present a novel hardware architecture of BEC point multiplication using mixed w -coordinates of the Montgomery laddering algorithm and analyze it in terms of resistance to Simple Power Analysis (SPA) attack. In order to improve the performance, the architecture utilizes registers efficiently and uses efficient scheduling mechanisms for the BEC arithmetic implementations. Our implementation results show that the proposed architecture is resistant against SPA attack and yields a better performance when compared to the existing state-of-the-art BEC designs for computing point multiplication (PM). Finally, we present an FPGA design of ECMQV key agreement protocol using BEC defined over GF(2 251 ). The execution of ECMQV protocol takes 66.47μs using 32,479 slices on Virtex-4 FPGA and 52.34μs using 15,988 slices on Virtex-5 FPGA. To the best of our knowledge, this is the first FPGA design of the ECMQV protocol using BEC.

This paper analyses an image watermarking scheme based on Support Vector Regression (SVR) proposed by R. Shen et al. We describe various attacks against this scheme and show that watermark tampering can be done even when one does not know the secret key used to embed the watermark. Next we discuss methods to extract the keys used in the scheme under various usage scenarios. Our results show that Shen et al.'s scheme is not secure.

In this work, we study several properties of the SHA-2 design which have been utilized in recent collision attacks against reduced round SHA-2. Small modifications to the SHA-2 design are suggested to thwart these attacks. The modified round function provides the same resistance to linearization attacks as the original SHA-2 round function, but, provides better resistance to non-linear attacks. Our next contribution is to introduce the general idea of "multiple feed-forward" for the construction of cryptographic hash functions. This can provide increased resistance to the Chabaud-Joux type "perturbation-correction" collision attacks. The idea of feed-forward is taken further by introducing the idea of feed-forward across message blocks leading to resistance against generic multi-collision attacks. The net effect of the suggested changes to the SHA-2 design has insignificant impact on the efficiency of computing the digest.

Many attempts have been made to analyze gene expression data. Typical goals of such analysis include discovery of subclasses, designing predictors/classifiers for diseases, identifying marker genes, and trying to get a deeper understanding of underlying biological process. Success of each of these tasks strongly depends on the features used to solve the problem. The high dimensional nature of expression profiles makes the task very difficult. Consequently, many researchers have used some feature selection criteria to reduce the dimensionality of the problem. These approaches are off-line in nature, as feature selection is done in a separate phase from the system design phase. These approaches ignore the fact that utility of features depends on both the problem that is solved and the tool that is used to solve the problem. We here propose to use a novel neural scheme that picks up the necessary features on-line when the system learns the classification task. Because it considers all the features at one go, it does not miss any subtle combination of these features. We demonstrate the effectiveness of our on-line feature selection (OFS) scheme to distinguish between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) cancer expression data set. Our scheme could identify only five genes that can produce results as good as or even better than what is reported in the literature on this data set. It identifies an important marker gene that alone has a very good discriminating power. This analysis method is quite general in nature and can be effectively used in other areas of bioinformatics. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 453–467, 2006.