Cover Image

Cryptographic Backdoor for Neural Networks: Boon and Bane

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ngo, Anh Tu, Chattopadhyay, Anupam, Maitra, Subhamoy
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

BlockDoor: Blocking Backdoor Based Watermarks in Deep Neural Networks
by: Puah, Yi Hao, et al.
Published: (2024)

Persistence of Backdoor-based Watermarks for Neural Networks: A Comprehensive Evaluation
by: Ngo, Anh Tu, et al.
Published: (2025)

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks
by: Eggen, Marte, et al.
Published: (2026)

Learning Nonlinearity of Boolean Functions: An Experimentation with Neural Networks
by: Ranga, Sriram, et al.
Published: (2025)

Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits
by: Draguns, Andis, et al.
Published: (2024)

Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering
by: Effendi, Fabrianne, et al.
Published: (2024)

PrivGNN: High-Performance Secure Inference for Cryptographic Graph Neural Networks
by: Wang, Fuyi, et al.
Published: (2025)

Vaporizer: Breaking Watermarking Schemes for Large Language Model Outputs
by: Ng, Jonathan Hong Jin, et al.
Published: (2026)

Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)

Adaptive Backdoor Attacks with Reasonable Constraints on Graph Neural Networks
by: Dong, Xuewen, et al.
Published: (2025)

DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks
by: Sui, Hao, et al.
Published: (2024)

Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models
by: Kalavasis, Alkis, et al.
Published: (2024)

Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
by: Gosch, Lukas, et al.
Published: (2024)

Privacy and Security Implications of Cloud-Based AI Services : A Survey
by: Luqman, Alka, et al.
Published: (2024)

BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks
by: Li, Xinfu, et al.
Published: (2024)

Flatness-aware Sequential Learning Generates Resilient Backdoors
by: Pham, Hoang, et al.
Published: (2024)

PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
by: Wang, Yue, et al.
Published: (2022)

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

ArcGen: Generalizing Neural Backdoor Detection Across Diverse Architectures
by: Yang, Zhonghao, et al.
Published: (2025)

Model Inversion Attacks Meet Cryptographic Fuzzy Extractors
by: Prabhakar, Mallika, et al.
Published: (2025)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

Authority Backdoor: A Certifiable Backdoor Mechanism for Authoring DNNs
by: Yang, Han, et al.
Published: (2025)

BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning
by: Wu, Baoyuan, et al.
Published: (2024)

KiNETGAN: Enabling Distributed Network Intrusion Detection through Knowledge-Infused Synthetic Data Generation
by: Kotal, Anantaa, et al.
Published: (2024)

More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
by: Xu, Jing, et al.
Published: (2022)

Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)

Robust Semi-Supervised Temporal Intrusion Detection for Adversarial Cloud Networks
by: Chattopadhyay, Anasuya, et al.
Published: (2026)

Memory Backdoor Attacks on Neural Networks
by: Luzon, Eden, et al.
Published: (2024)

INTACT: Intent-Aware Representation Learning for Cryptographic Traffic Violation Detection
by: Ray, Rahul D
Published: (2026)

Hardware-Triggered Backdoors
by: Möller, Jonas, et al.
Published: (2026)

TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks
by: Hossain, Khondoker Murad, et al.
Published: (2024)

CodePurify: Defend Backdoor Attacks on Neural Code Models via Entropy-based Purification
by: Mu, Fangwen, et al.
Published: (2024)

Fusing Pruned and Backdoored Models: Optimal Transport-based Data-free Backdoor Mitigation
by: Lin, Weilin, et al.
Published: (2024)

A Deep-Learning Technique to Locate Cryptographic Operations in Side-Channel Traces
by: Chiari, Giuseppe, et al.
Published: (2024)

Beyond Static Tools: Evaluating Large Language Models for Cryptographic Misuse Detection
by: Masood, Zohaib, et al.
Published: (2024)

Backdoor Mitigation in Deep Neural Networks via Strategic Retraining
by: Dhonthi, Akshay, et al.
Published: (2022)

Detecting and Eliminating Neural Network Backdoors Through Active Paths with Application to Intrusion Detection
by: Høyheim, Eirik, et al.
Published: (2026)

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

Seal Your Backdoor with Variational Defense
by: Sabolić, Ivan, et al.
Published: (2025)

Persistent Backdoor Attacks in Continual Learning
by: Guo, Zhen, et al.
Published: (2024)