A MAC Mode for Lightweight Block Ciphers

status: accepte

Efficient enhanced keyword search for encrypted document in cloud

A sensitive public-key searchable encryption system in the prime-order groups, which lets keyword search policies to be uttered in conjunctive, disjunctive or any monotonic Boolean formulas and realizes momentous act enhancement over existing schemes. We legally express its sanctuary, and verify that it is selectively sheltered in the standard model. Correspondingly, we instrument the wished-for outline using a hasty prototyping tool so-called Charm and conduct more than a few experiments to estimate it show. The results determine that our scheme is plentiful more proficient than the ones assembled over the composite-order groups. Keyword research is one of the most imperative, valuable, and high return activities in the search marketing field. Position for the right keywords can make or interruption your website

Fine-Grained Static Detection of Obfuscation Transforms Using Ensemble-Learning and Semantic Reasoning

International audienceThe ability to efficiently detect the software protections used is at a prime to facilitate the selection and application of adequate deob-fuscation techniques. We present a novel approach that combines semantic reasoning techniques with ensemble learning classification for the purpose of providing a static detection framework for obfuscation transformations. By contrast to existing work, we provide a methodology that can detect multiple layers of obfuscation, without depending on knowledge of the underlying functionality of the training-set used. We also extend our work to detect constructions of obfuscation transformations, thus providing a fine-grained methodology. To that end, we provide several studies for the best practices of the use of machine learning techniques for a scalable and efficient model. According to our experimental results and evaluations on obfuscators such as Tigress and OLLVM, our models have up to 91% accuracy on state-of-the-art obfuscation transformations. Our overall accuracies for their constructions are up to 100%

Information Entropy Based Leakage Certification

Side-channel attacks and evaluations typically utilize leakage models to extract sensitive information from measurements of cryptographic implementations. Efforts to establish a true leakage model is still an active area of research since Kocher proposed Differential Power Analysis (DPA) in 1999. Leakage certification plays an important role in this aspect to address the following question: how good is my leakage model? . However, existing leakage certification methods still need to tolerate assumption error and estimation error of unknown leakage models. There are many probability density distributions satisfying given moment constraints. As such, finding the most unbiased and most reasonable model still remains an unresolved problem. In this paper, we address a more fundamental question: what\u27s the true leakage model of a chip? . In particular, we propose Maximum Entropy Distribution (MED) to estimate the leakage model as MED is the most unbiased, objective and theoretically the most reasonable probability density distribution conditioned upon the available information. MED can theoretically use information on arbitrary higher-order moments to infinitely approximate the true leakage model. It well compensates the theory vacancy of model profiling and evaluation. Experimental results demonstrate the superiority of our proposed method for approximating the leakage model using MED estimation

Secure Context Switching of Masked Software Implementations

Cryptographic software running on embedded devices requires protection against physical side-channel attacks such as power analysis. Masking is a widely deployed countermeasure against these attacksand is directly implemented on algorithmic level. Many works study the security of masked cryptographic software on CPUs, pointing out potential problems on algorithmic/microarchitecture-level, as well as corresponding solutions, and even show masked software can be implemented efficiently and with strong (formal) security guarantees. However, these works also make the implicit assumption that software is executed directly on the CPU without any abstraction layers in-between, i.e., they focus exclusively on the bare-metal case. Many practical applications, including IoT and automotive/industrial environments, require multitasking embedded OSs on which masked software runs as one out of many concurrent tasks. For such applications, the potential impact of events like context switches on the secure execution of masked software has not been studied so far at all. In this paper, we provide the first security analysis of masked cryptographic software spanning all three layers (SW, OS, CPU). First, we apply a formal verification approach to identify leaks within the execution of masked software that are caused by the embedded OS itself, rather than on algorithmic or microarchitecture level. After showing that these leaks are primarily caused by context switching, we propose several different strategies to harden a context switching routine against such leakage, ultimately allowing masked software from previous works to remain secure when being executed on embedded OSs. Finally, we present a case study focusing on FreeRTOS, a popular embedded OS for embedded devices, running on a RISC-V core, allowing us to evaluate the practicality and ease of integration of each strategy

Single-trace clustering power analysis of the point-swapping procedure in the three point ladder of Cortex-M4 SIKE

In this paper, the recommended implementation of the post-quantum key exchange SIKE for Cortex-M4 is attacked through power analysis with a single trace by clustering with the $k$-means algorithm the power samples of all the invocations of the elliptic curve point swapping function in the constant-time coordinate-randomized three point ladder. Because each sample depends on whether two consecutive bits of the private key are the same or not, a successful clustering (with $k=2$) leads to the recovery of the entire private key. The attack is naturally improved with better strategies, such as clustering the samples in the frequency domain or processing the traces with a wavelet transform, using a simpler clustering algorithm based on thresholding, and using metrics to prioritize certain keys for key validation. The attack and the proposed improvements were experimentally verified using the ChipWhisperer framework. Splitting the swapping mask into multiple shares is suggested as an effective countermeasure

Efficient and expressive keyword search over encrypted data in the cloud

National Research Foundation (NRF) Singapor

Security of Ubiquitous Computing Systems

The chapters in this open access book arise out of the EU Cost Action project Cryptacus, the objective of which was to improve and adapt existent cryptanalysis methodologies and tools to the ubiquitous computing framework. The cryptanalysis implemented lies along four axes: cryptographic models, cryptanalysis of building blocks, hardware and software security engineering, and security assessment of real-world systems. The authors are top-class researchers in security and cryptography, and the contributions are of value to researchers and practitioners in these domains. This book is open access under a CC BY license