Related papers: A Deep-Learning Technique to Locate Cryptographic …

Physical layer authentication relies on detecting unique imperfections in signals transmitted by radio devices to isolate their fingerprint. Recently, deep learning-based authenticators have increasingly been proposed to classify devices…

The digital transformation of power systems is accelerating the adoption of IEC 61850 standard. However, its communication protocols, including Sampled Values (SV), lack built-in security features such as authentication and encryption,…

Profiled side-channel analysis (SCA) leverages leakage from cryptographic implementations to extract the secret key. When combined with advanced methods in neural networks (NNs), profiled SCA can successfully attack even those crypto-cores…

This paper presents Packet Chasing, an attack on the network that does not require access to the network, and works regardless of the privilege level of the process receiving the packets. A spy process can easily probe and discover the…

The interest in quantum computing has grown rapidly in recent years, and with it grows the importance of securing quantum circuits. A novel type of threat to quantum circuits that dedicated attackers could launch are power trace attacks. To…

Model extraction is a major threat for embedded deep neural network models that leverages an extended attack surface. Indeed, by physically accessing a device, an adversary may exploit side-channel leakages to extract critical information…

Analog compute-in-memory (CIM) systems are promising for deep neural network (DNN) inference acceleration due to their energy efficiency and high throughput. However, as the use of DNNs expands, protecting user input privacy has become…

Regarding image forensics, researchers have proposed various approaches to detect and/or localize manipulations, such as splices. Recent best performing image-forensics algorithms greatly benefit from the application of deep learning, but…

Security can be seen as an optimisation objective in NoC resource management, and as such poses trade-offs against other objectives such as real-time schedulability. In this paper, we show how to increase NoC resilience against a concrete…

Federated Learning (FL) enables collaborative model training across distributed devices while safeguarding data and user privacy. However, FL remains susceptible to privacy threats that can compromise data via direct means. That said,…

Side-channel based instruction disassembly has been proposed as a low-cost and non-invasive approach for security applications such as IP infringement detection, code flow analysis, malware detection, and reconstructing unknown code from…

Cybersecurity of Industrial Control Systems (ICS) is drawing significant concerns as data communication increasingly leverages wireless networks. A lot of data-driven methods were developed for detecting cyberattacks, but few are focused on…

We are interested in investigating the security of source encryption with a symmetric key under side-channel attacks. In this paper, we propose a general framework of source encryption with a symmetric key under the side-channel attacks,…

In-memory computing (IMC) systems have great potential for accelerating data-intensive tasks such as deep neural networks (DNNs). As DNN models are generally highly proprietary, the neural network architectures become valuable targets for…

Cryptomining poses significant security risks, yet traditional detection methods like blacklists and Deep Packet Inspection (DPI) are often ineffective against encrypted mining traffic and suffer from high false positive rates. In this…

Artificial intelligence, and specifically deep neural networks (DNNs), has rapidly emerged in the past decade as the standard for several tasks from specific advertising to object detection. The performance offered has led DNN algorithms to…

Smart grid's objective is to enable electricity and information to flow two-way while providing effective, robust, computerized, and decentralized energy delivery. This necessitates the use of state estimation-based techniques and real-time…

Performing a comprehensive side-channel analysis evaluation of small embedded devices is a process known for its variability and complexity. In real-world experimental setups, the results are largely influenced by a huge amount of…

Side-channel information leakage is a known limitation of SGX. Researchers have demonstrated that secret-dependent information can be extracted from enclave execution through page-fault access patterns. Consequently, various recent research…

In this paper, we present an acoustic side channel attack which makes use of smartphone microphones recording a robot in operation to exploit acoustic properties of the sound to fingerprint a robot's movements. In this work we consider the…