Papers Side Channel Analysis
“Side Channel Analysis” 태그가 달린 논문 28편 · 필터 해제
It's Not Just a Phase: On Investigating Phase Transitions in Deep Learning-based Side-channel Analysis
Side-channel analysis (SCA) represents a realistic threat where the attacker can observe unintentional information to obtain secret data. Evaluation labs also use the same SCA techniques in the security certification pro…
Deep LearningSide Channel AnalysisImproving Location-based Thermal Emission Side-Channel Analysis Using Iterative Transfer Learning
This paper proposes the use of iterative transfer learning applied to deep learning models for side-channel attacks. Currently, most of the side-channel attack methods train a model for each individual byte, without cons…
Side Channel AnalysisTransfer LearningTrojanWhisper: Evaluating Pre-trained LLMs to Detect and Localize Hardware Trojans
Existing Hardware Trojans (HT) detection methods face several critical limitations: logic testing struggles with scalability and coverage for large designs, side-channel analysis requires golden reference chips, and form…
Natural Language UnderstandingSide Channel AnalysisSide-Channel Analysis of OpenVINO-based Neural Network Models
Embedded devices with neural network accelerators offer great versatility for their users, reducing the need to use cloud-based services. At the same time, they introduce new security challenges in the area of hardware a…
Side Channel AnalysisRethinking IC layout vulnerability: Simulation-based hardware Trojan threat assessment with high fidelity
Due to the escalating complexity of chip design and the exorbitant cost of building cutting-edge manufacturing facilities, outsourcing the fabrication of Integrated Circuits (ICs) is prevalent in modern semiconductor ind…
Side Channel AnalysisImpedance vs. Power Side-channel Vulnerabilities: A Comparative Study
Physical side channels emerge from the relation between internal computation or data with observable physical parameters of a chip. Previous works mostly focus on properties related to current consumption such as power c…
Side Channel AnalysisWhat Was Your Prompt? A Remote Keylogging Attack on AI Assistants
AI assistants are becoming an integral part of society, used for asking advice or help in personal and confidential issues. In this paper, we unveil a novel side-channel that can be used to read encrypted responses from …
Language ModelingLanguage ModellingLarge Language ModelSentence+1SNOW-SCA: ML-assisted Side-Channel Attack on SNOW-V
This paper presents SNOW-SCA, the first power side-channel analysis (SCA) attack of a 5G mobile communication security standard candidate, SNOW-V, running on a 32-bit ARM Cortex-M4 microcontroller. First, we perform a ge…
Side Channel AnalysisA Review and Comparison of AI Enhanced Side Channel Analysis
Side Channel Analysis (SCA) presents a clear threat to privacy and security in modern computing systems. The vast majority of communications are secured through cryptographic algorithms. These algorithms are often provab…
Deep LearningSide Channel AnalysisCNN architecture extraction on edge GPU
Neural networks have become popular due to their versatility and state-of-the-art results in many applications, such as image classification, natural language processing, speech recognition, forecasting, etc. These appli…
GPUimage-classificationImage ClassificationSide Channel Analysis+2Evasive Hardware Trojan through Adversarial Power Trace
The globalization of the Integrated Circuit (IC) supply chain, driven by time-to-market and cost considerations, has made ICs vulnerable to hardware Trojans (HTs). Against this threat, a promising approach is to use Mach…
Side Channel AnalysisRevealing CNN Architectures via Side-Channel Analysis in Dataflow-based Inference Accelerators
Convolutional Neural Networks (CNNs) are widely used in various domains, including image recognition, medical diagnosis and autonomous driving. Recent advances in dataflow-based CNN accelerators have enabled CNN inferenc…
Autonomous DrivingMedical DiagnosisSide Channel AnalysisCrossed-IoT device portability of Electromagnetic Side Channel Analysis: Challenges and Dataset
IoT (Internet of Things) refers to the network of interconnected physical devices, vehicles, home appliances, and other items embedded with sensors, software, and connectivity, enabling them to collect and exchange data.…
Side Channel AnalysisTransfer LearningA Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks
Model extraction attacks have been widely applied, which can normally be used to recover confidential parameters of neural networks for multiple layers. Recently, side-channel analysis of neural networks allows parameter…
Model extractionSide Channel AnalysisSide-channel analysis against ANSSI’s protected AES implementation on ARM: end-to-end attacks with multi-task learning
In 2019, ANSSI released a protected software implementation of AES running on an STM32 platform with ARM Cortex-M architecture, publicly available on Github. The release of the code was shortly followed by a first paper …
Multi-Task LearningSide Channel AnalysisNASCTY: Neuroevolution to Attack Side-channel Leakages Yielding Convolutional Neural Networks
Side-channel analysis (SCA) can obtain information related to the secret key by exploiting leakages produced by the device. Researchers recently found that neural networks (NNs) can execute a powerful profiling SCA, even…
Side Channel AnalysisA Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters
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 cr…
Model extractionSide Channel AnalysisConfiguration and Collection Factors for Side-Channel Disassembly
Myriad uses, methodologies, and channels have been explored for side-channel analysis. However, specific implementation considerations are often unpublished. This paper explores select test configuration and collection p…
Side Channel AnalysisTime SeriesTime Series AnalysisPlaying with blocks: Toward re-usable deep learning models for side-channel profiled attacks
This paper introduces a deep learning modular network for side-channel analysis. Our deep learning approach features the capability to exchange part of it (modules) with others networks. We aim to introduce reusable trai…
Deep LearningSide Channel AnalysisAutomated Side Channel Analysis of Media Software with Manifold Learning
The prosperous development of cloud computing and machine learning as a service has led to the widespread use of media software to process confidential media data. This paper explores an adversary's ability to launch sid…
Cloud ComputingRepresentation LearningSide Channel Analysis