Cover Image

Power side-channel leakage localization through adversarial training of deep neural networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gammell, Jimmy, Raghunathan, Anand, Roy, Kaushik
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to Localize Leakage of Cryptographic Sensitive Variables
by: Gammell, Jimmy, et al.
Published: (2025)

Are aligned neural networks adversarially aligned?
by: Carlini, Nicholas, et al.
Published: (2023)

Nonideality-aware training makes memristive networks more robust to adversarial attacks
by: Joksas, Dovydas, et al.
Published: (2024)

Feature compression is the root cause of adversarial fragility in neural network classifiers
by: Gao, Jingchao, et al.
Published: (2024)

Attack logics, not outputs: Towards efficient robustification of deep neural networks by falsifying concept-based properties
by: Dankworth, Raik, et al.
Published: (2025)

Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensemble
by: Xue, Yunzhe, et al.
Published: (2024)

Robust LLM safeguarding via refusal feature adversarial training
by: Yu, Lei, et al.
Published: (2024)

Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature
by: Ravikumar, Deepak, et al.
Published: (2024)

Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre
by: Carlini, Nicholas
Published: (2024)

Can sparsity improve the privacy of neural networks?
by: Gonon, Antoine, et al.
Published: (2023)

Augmenting Parameter-Efficient Pre-trained Language Models with Large Language Models
by: Anand, Saurabh, et al.
Published: (2026)

SHLIME: Foiling adversarial attacks fooling SHAP and LIME
by: Chauhan, Sam, et al.
Published: (2025)

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks
by: Clifford, Eleanor, et al.
Published: (2022)

Performance Evaluation of Knowledge Graph Embedding Approaches under Non-adversarial Attacks
by: Kapoor, Sourabh, et al.
Published: (2024)

User authentication system based on human exhaled breath physics
by: Karunanethy, Mukesh, et al.
Published: (2024)

Robustness bounds on the successful adversarial examples in probabilistic models: Implications from Gaussian processes
by: Maeshima, Hiroaki, et al.
Published: (2024)

DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
by: Roy, Arjun, et al.
Published: (2024)

Blending adversarial training and representation-conditional purification via aggregation improves adversarial robustness
by: Ballarin, Emanuele, et al.
Published: (2023)

Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models
by: Wen, Yuxin, et al.
Published: (2024)

A Machine Learning-Based Framework for Assessing Cryptographic Indistinguishability of Lightweight Block Ciphers
by: Dani, Jimmy, et al.
Published: (2024)

Unveiling Privacy, Memorization, and Input Curvature Links
by: Ravikumar, Deepak, et al.
Published: (2024)

Testing the Limits of Jailbreaking Defenses with the Purple Problem
by: Kim, Taeyoun, et al.
Published: (2024)

Sparsity in neural networks can improve their privacy
by: Gonon, Antoine, et al.
Published: (2023)

Enhancing the Robustness of QMIX against State-adversarial Attacks
by: Guo, Weiran, et al.
Published: (2023)

When AI Defeats Password Deception! A Deep Learning Framework to Distinguish Passwords and Honeywords
by: Dani, Jimmy, et al.
Published: (2024)

Towards Building Secure UAV Navigation with FHE-aware Knowledge Distillation
by: Kaushik, Arjun Ramesh, et al.
Published: (2024)

Ransomware threat mitigation through network traffic analysis and machine learning techniques
by: Mehrban, Ali, et al.
Published: (2024)

LiteLMGuard: Seamless and Lightweight On-Device Prompt Filtering for Safeguarding Small Language Models against Quantization-induced Risks and Vulnerabilities
by: Nakka, Kalyan, et al.
Published: (2025)

Malacopula: adversarial automatic speaker verification attacks using a neural-based generalised Hammerstein model
by: Todisco, Massimiliano, et al.
Published: (2024)

Non-omniscient backdoor injection with one poison sample: Proving the one-poison hypothesis for linear regression, linear classification, and 2-layer ReLU neural networks
by: Peinemann, Thorsten, et al.
Published: (2025)

Interpreting Emergent Features in Deep Learning-based Side-channel Analysis
by: Karayalçin, Sengim, et al.
Published: (2025)

Vulnerability of Text-Matching in ML/AI Conference Reviewer Assignments to Collusions
by: Hsieh, Jhih-Yi, et al.
Published: (2024)

Adversarial training with restricted data manipulation
by: Benfield, David, et al.
Published: (2025)

Effective backdoor attack on graph neural networks in link prediction tasks
by: Dai, Jiazhu, et al.
Published: (2024)

AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses
by: Carlini, Nicholas, et al.
Published: (2025)

Innovative tokenisation of structured data for LLM training
by: Karim, Kayvan, et al.
Published: (2025)

Selective Pre-training for Private Fine-tuning
by: Yu, Da, et al.
Published: (2023)

Confidential and Protected Disease Classifier using Fully Homomorphic Encryption
by: Malik, Aditya, et al.
Published: (2024)

SeqShield: A Behavioral Analysis Approach to Uncover Rootkits
by: Ghodeshwar, Paras, et al.
Published: (2026)

Pre-training Differentially Private Models with Limited Public Data
by: Bu, Zhiqi, et al.
Published: (2024)