Cover Image

HAMLOCK: HArdware-Model LOgically Combined attacK

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Amgain, Sanskar, Lobo, Daniel, Chatterjee, Atri, Bhunia, Swarup, Suya, Fnu
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Runtime Detection of Adversarial Attacks in AI Accelerators Using Performance Counters
by: Rahaman, Habibur, et al.
Published: (2025)

Security Enclave Architecture for Heterogeneous Security Primitives for Supply-Chain Attacks
by: Raj, Kshitij, et al.
Published: (2025)

SoK: Pitfalls in Evaluating Black-Box Attacks
by: Suya, Fnu, et al.
Published: (2023)

SoK: Can Trajectory Generation Combine Privacy and Utility?
by: Buchholz, Erik, et al.
Published: (2024)

Token Inflation: How Dishonest Providers Can Overcharge for Large Language Model Usage
by: Hoque, Shahinul, et al.
Published: (2026)

CIPHR: Cryptography Inspired IP Protection through Fine-Grain Hardware Redaction
by: Dasgupta, Aritra, et al.
Published: (2026)

Adversarial Hubness in Multi-Modal Retrieval
by: Zhang, Tingwei, et al.
Published: (2024)

SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges
by: Panzade, Prajwal, et al.
Published: (2022)

SoK: Machine Unlearning for Large Language Models
by: Ren, Jie, et al.
Published: (2025)

X-DFS: Explainable Artificial Intelligence Guided Design-for-Security Solution Space Exploration
by: Mahfuz, Tanzim, et al.
Published: (2024)

Combining Machine Learning Defenses without Conflicts
by: Duddu, Vasisht, et al.
Published: (2024)

Secure and Storage-Efficient Deep Learning Models for Edge AI Using Automatic Weight Generation
by: Rahaman, Habibur, et al.
Published: (2025)

SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks
by: Amit, Guy, et al.
Published: (2024)

Expressive Losses for Verified Robustness via Convex Combinations
by: De Palma, Alessandro, et al.
Published: (2023)

SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark
by: Wen, Rui, et al.
Published: (2025)

SoK: Privacy-aware LLM in Healthcare: Threat Model, Privacy Techniques, Challenges and Recommendations
by: Tahera, Mohoshin Ara, et al.
Published: (2026)

Compact: Approximating Complex Activation Functions for Secure Computation
by: Islam, Mazharul, et al.
Published: (2023)

Privacy-Preserving Vertical K-Means Clustering
by: Mazzone, Federico, et al.
Published: (2025)

SoK: Data Minimization in Machine Learning
by: Staab, Robin, et al.
Published: (2025)

Provenance of AI-Generated Images: A Vector Similarity and Blockchain-based Approach
by: Sharma, Jitendra, et al.
Published: (2025)

Library-Attack: Reverse Engineering Approach for Evaluating Hardware IP Protection
by: Dasgupta, Aritra, et al.
Published: (2025)

SALTY: Explainable Artificial Intelligence Guided Structural Analysis for Hardware Trojan Detection
by: Mahfuz, Tanzim, et al.
Published: (2025)

POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage
by: Mahfuz, Tanzim, et al.
Published: (2025)

SoK: What Makes Private Learning Unfair?
by: Yao, Kai, et al.
Published: (2025)

SoK: The Pitfalls of Deep Reinforcement Learning for Cybersecurity
by: McFadden, Shae, et al.
Published: (2026)

Adversaries Can Misuse Combinations of Safe Models
by: Jones, Erik, et al.
Published: (2024)

SoK: Dataset Copyright Auditing in Machine Learning Systems
by: Du, Linkang, et al.
Published: (2024)

Combining Stochastic Defenses to Resist Gradient Inversion: An Ablation Study
by: Scheliga, Daniel, et al.
Published: (2022)

Comparative Analysis of Hash-based Malware Clustering via K-Means
by: Thein, Aink Acrie Soe, et al.
Published: (2025)

SoK: Unintended Interactions among Machine Learning Defenses and Risks
by: Duddu, Vasisht, et al.
Published: (2023)

SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge
by: Fenaux, Lucas, et al.
Published: (2024)

WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles
by: Mesana, Patrick, et al.
Published: (2024)

Visual Privacy Auditing with Diffusion Models
by: Schwethelm, Kristian, et al.
Published: (2024)

Verifying LLM Inference to Detect Model Weight Exfiltration
by: Rinberg, Roy, et al.
Published: (2025)

Backdooring Masked Diffusion Language Models
by: Cao, Daniel Yiming, et al.
Published: (2026)

A PUF-Based Approach for Copy Protection of Intellectual Property in Neural Network Models
by: Dorfmeister, Daniel, et al.
Published: (2026)

SoK: Unlearnability and Unlearning for Model Dememorization
by: Zhang, Mengying, et al.
Published: (2026)

How Safe Are AI-Generated Patches? A Large-scale Study on Security Risks in LLM and Agentic Automated Program Repair on SWE-bench
by: Sajadi, Amirali, et al.
Published: (2025)

Breaking Distortion-free Watermarks in Large Language Models
by: Reynolds, Shayleen, et al.
Published: (2025)

DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
by: Pulido-Cortázar, Daniel, et al.
Published: (2025)