Smart devices, especially Internet-connected devices, typically incorporate security protocols and cryptographic algorithms to ensure the control flow integrity and information security. However, various types of attacks try to tamper with these devices, including invasive and non-invasive. Chip-level shields have been proven effective against invasive attacks, but the potential of shields as a protection mechanism against side-channel analysis (SCA) attacks remains under-explored. To bridge this gap, we propose a shield-based multi-functional protection scheme, named EO-Shield, capable of simultaneously thwarting invasive and non-invasive attacks. EO-Shield is implemented using the chip’s top metal layer and includes an Information Leakage Obfuscation Module (ILOM) underneath. This module generates its protection patterns based on the operating conditions of the circuit that need to be protected, thus reducing the correlation between electromagnetic (EM) emanations and cryptographic data. Additionally, we introduce a simulation technique to test the protection efficacy of EO-Shield at the layout level, utilizing commercial Electronic Design Automation (EDA) tools and the EMSim/EMSim+ tool. Simulation experiments demonstrate that the ILOM decreases the signal-to-noise (SNR) ratio to below 0.6 and improves the difficulty of SCA attacks by more than 100 times. Compared to existing single-function protection methods against physical attacks, EO-Shield leverages the EM protection potential of shields to offer multi-functional protection.

Side-channel analysis (SCA) attacks pose a significant threat to cryptographic integrated circuits (ICs). While designers have endeavored to introduce various countermeasures during the IC development phase, many of these solutions incur substantial overheads in terms of area, power, and performance. Additionally, they often necessitate a full-custom circuit design for effective deployment. This issue arises due to the absence of systematic methodologies and analytical tools for circuit designers to accurately identify the sources of side-channel leakage within the hardware design. In this article, we propose the concept of side-channel tracking logic and, building upon this foundation, introduce a novel framework that seamlessly integrates with commercial design flows to automatically identify and safeguard leaky paths. Our approach begins by pinpointing partial logic cells that exhibit the highest information leakage using dynamic correlation analysis. Subsequently, formal-based leakage property checking constructs comprehensive leaky paths centered on these cells. In this process, side-channel tracking logic was proposed and applied for the first time to trace and extract side-channel leakage paths. Based on this, an automated formal modeling and leakage property verification tool was designed. Once these paths are discerned, we deploy apt hardware countermeasures, encompassing Boolean masking and random precharge, to eradicate information leakage along these routes. This framework has been experimentally validated across different encryption circuits and the efficacy of our methodology is corroborated through both simulated and real-world measurements on FPGA implementations. Empirical results showcase an enhancement of over 1000× in side-channel resistance, incurring a modest overhead of less than 6.53% across power, area, and performance metrics.

Electromagnetic side-channel analysis (EM SCA) attack poses a serious threat to integrated circuits (ICs), necessitating timely vulnerability detection before deployment to enhance EM side-channel security. Various EM simulation methods have emerged for analyzing EM side-channel leakage, providing sufficiently accurate results. However, these simulator-based methods still face two principal challenges in the design process of high security chips. Firstly, the large volume of measurement data required for a single security evaluation results in substantial time overhead. Secondly, design iterations lead to repetitive security evaluations, thus increasing the evaluation cost. In this paper, we propose EMSim+ which includes two efficient and accurate layout-level EM side-channel leakage evaluation frameworks named EMSim+GAN and EMSim+GAN+TL to mitigate the above challenges, respectively. EMSim+GAN integrates a Generative Adversarial Network (GAN) model that utilizes the chip’s cell current and power grid information to predict EM emanations quickly. EMSim+GAN+TL further incorporates transfer learning (TL) within the framework, leveraging the experience of existing designs to reduce the training datasets for new designs and achieve the target accuracy. We compare the simulation results of EMSim+ with the state-of-the-art EM simulation tool, EMSim as well as silicon measurements. Experimental results not only prove the high efficiency and high simulation accuracy of EMSim+, but also verify its generalization ability across different designs and technology nodes.

Smart devices, especially Internet-connected devices, typically incorporate security protocols and cryptographic algorithms to ensure the control flow integrity and information security. However, there are various invasive and non-invasive attacks trying to tamper with these devices. Chip-level active shield has been proved to be an effective countermeasure against invasive attacks, but existing active shields cannot be utilized to counter side-channel attacks (SCAs). In this paper, we propose a multi-function protection scheme and an active shield prototype to against invasive and non-invasive attacks simultaneously. The protection scheme has a complex active shield implemented using the top metal layer of the chip and an information leakage obfuscation module underneath. The leakage obfuscation module generates its protection patterns based on the operating conditions of the circuit that needs to be protected, thus reducing the correlation between electromagnetic (EM) emanations and cryptographic data. We implement the protection scheme on one Advanced Encryption Standard (AES) circuit to demonstrate the effectiveness of the method. Experiment results demonstrate that the information leakage obfuscation module decreases SNR below 0.6 and reduces the success rate of SCAs. Compared to existing single-function protection methods against physical attacks, the proposed scheme provides good performance against both invasive and non-invasive attacks.

Electromagnetic side-channel analysis (EM SCA) attack is a serious threat to integrated circuits (ICs). In order to detect vulnerabilities in time at the pre-silicon stage and to improve the chip's robustness to EM SCA attacks, several EM simulation methods have emerged for EM side-channel leakage evaluation. Although the simulated results are accurate, the chip security evaluation in practice requires up to hundreds of millions simulation traces, which imposes an unrealistic computational and time overhead on these simulator-based methods. In this paper, we develop a tool named EMSim+. Different from the general EM security evaluation process, EMSim+ introduces machine learning (ML) to accelerate the simulation of layout-level EM emanations. Based on the generative adversarial network (GAN), a well-trained EMSim+ model can accept the cell current and power grid information of the chip and rapidly predict the EM emanation of the chip surface. We apply EMSim+ to a series of representative cryptographic circuits and compare the simulation results with the state-of-the-art EM simulation method and silicon measurements. The experimental results prove that EMSim+ has high simulation accuracy and achieves more than 242 times evaluation time reduction for 1 M sample data.

The emergence of quantum computing and its impact on current cryptographic algorithms has triggered the migration to post-quantum cryptography (PQC). Among the PQC candidates, CRYSTALS-Kyber is a key encapsulation mechanism (KEM) that stands out from the National Institute of Standards and Technology (NIST) standardization project. While software implementations of Kyber have been developed and evaluated recently, Kyber’s hardware implementations especially those designed with parallel architecture, are rarely discussed. To help better understand Kyber hardware designs and their security against side-channel analysis (SCA) attacks, in this paper, we first adapt the two most recent Kyber hardware designs for FPGA implementations. We then perform SCA attacks against these hardware designs with different architectures, i.e., parallelization and pipelining. Our experimental results show that Kyber designs on FPGA boards are vulnerable to SCA attacks including electromagnetic (EM) and power side channels. An attacker only needs$27 \sim 1,600$power traces or$60 \sim 2,680$EM traces to recover the decryption key successfully. Furthermore, we propose two first-order IND-CPA Kyber decapsulation masking protected designs, and then we evaluate their securities and overheads. The experimental results demonstrate that the side channel security of masked Kyber designs has increased by more than 10x.

Side-channel analysis (SCA) attacks show an enormous threat to cryptographic integrated circuits (ICs). To address this threat, designers try to adopt various countermeasures during the IC development process. However, many existing solutions are costly in terms of area, power and/or performance, and may require full-custom circuit design for proper implementations. In this paper, we propose a tool, namely PathFinder, to automatically identify leaky paths and protect the design, and is compatible with the commercial design flow. The tool first finds out partial logic cells that leak the most information through dynamic correlation analysis. PathFinder then exploits static security checking to construct complete leaky paths based on these cells. After leaky paths are identified, PathFinder will leverage proper hardware countermeasures, including Boolean masking and random precharge, to eliminate information leakage from these paths. The effectiveness of PathFinder is validated both through simulation and physical measurements on FPGA implementations. Results demonstrate more than 1000X improvements on side-channel resistance, with less than 6.53% penalty to the power, area and performance.