:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Srivastava, Aviral, Panda, Sourav
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Machine Learning I.2.m
Online Access:	https://arxiv.org/abs/2410.13897
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System
by: Broda-Milian, Kiernan, et al.
Published: (2024)

Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning
by: Semenov, Andrei, et al.
Published: (2024)

Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
by: Verma, Apurv, et al.
Published: (2025)

Learning Obfuscations Of LLM Embedding Sequences: Stained Glass Transform
by: Roberts, Jay, et al.
Published: (2025)

AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Models
by: Yin, Zhipeng, et al.
Published: (2025)

Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting
by: Zhao, Tianya, et al.
Published: (2025)

Attention Is Where You Attack
by: Srivastava, Aviral, et al.
Published: (2026)

Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping
by: Zhao, Linzh, et al.
Published: (2025)

AI Bill of Materials and Beyond: Systematizing Security Assurance through the AI Risk Scanning (AIRS) Framework
by: Nathanson, Samuel, et al.
Published: (2025)

Variables are a Curse in Software Vulnerability Prediction
by: Groppe, Jinghua, et al.
Published: (2024)

Mitigating Downstream Model Risks via Model Provenance
by: Wang, Keyu, et al.
Published: (2024)

It Is Time To Steer: A Scalable Framework for Analysis-driven Attack Graph Generation
by: Palma, Alessandro, et al.
Published: (2023)

SoK: A Review of Differentially Private Linear Models For High-Dimensional Data
by: Khanna, Amol, et al.
Published: (2024)

DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning
by: Lee, Kichang, et al.
Published: (2024)

MalDataGen: A Modular Framework for Synthetic Tabular Data Generation in Malware Detection
by: Paim, Kayua Oleques, et al.
Published: (2025)

Randomization Techniques to Mitigate the Risk of Copyright Infringement
by: Chen, Wei-Ning, et al.
Published: (2024)

AI-Driven Security Alert Screening and Alert Fatigue Mitigation in Security Operations Centers: A Survey
by: Ndichu, Samuel, et al.
Published: (2026)

Secure Decentralized Learning with Blockchain
by: Zhang, Xiaoxue, et al.
Published: (2023)

LLM Scalability Risk for Agentic-AI and Model Supply Chain Security
by: Ahi, Kiarash, et al.
Published: (2026)

Power-Softmax: Towards Secure LLM Inference over Encrypted Data
by: Zimerman, Itamar, et al.
Published: (2024)

PoTS: Proof-of-Training-Steps for Backdoor Detection in Large Language Models
by: Seddik, Issam, et al.
Published: (2025)

GuardVal: Dynamic Large Language Model Jailbreak Evaluation for Comprehensive Safety Testing
by: Zhang, Peiyan, et al.
Published: (2025)

Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks
by: Njungle, Nges Brian, et al.
Published: (2026)

JavelinGuard: Low-Cost Transformer Architectures for LLM Security
by: Datta, Yash, et al.
Published: (2025)

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
by: Boisvert, Léo, et al.
Published: (2025)

Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
by: Liu, Zhenlong, et al.
Published: (2024)

Dynamic Relation-Attentive Graph Neural Networks for Fraud Detection
by: Kim, Heehyeon, et al.
Published: (2023)

PrivSpike: Employing Homomorphic Encryption for Private Inference of Deep Spiking Neural Networks
by: Njungle, Nges Brian, et al.
Published: (2025)

Bridging the Gap Between Security Metrics and Key Risk Indicators: An Empirical Framework for Vulnerability Prioritization
by: Sherif, Emad, et al.
Published: (2026)

Optimizing Agent Planning for Security and Autonomy
by: Kolluri, Aashish, et al.
Published: (2026)

Safety, Security, and Cognitive Risks in World Models
by: Parmar, Manoj
Published: (2026)

FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF
by: Fan, Flint Xiaofeng, et al.
Published: (2024)

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
by: Garov, Kostadin, et al.
Published: (2023)

Correlation Analysis of Adversarial Attack in Time Series Classification
by: Li, Zhengyang, et al.
Published: (2024)

Facebook Report on Privacy of fNIRS data
by: Hossen, Md Imran, et al.
Published: (2024)

Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol
by: Alaiz-Moreton, Hector, et al.
Published: (2024)

Evaluating Membership Inference Attacks in heterogeneous-data setups
by: van Dartel, Bram, et al.
Published: (2025)

An Efficient Gradient-Based Inference Attack for Federated Learning
by: Montaña-Fernández, Pablo, et al.
Published: (2025)

Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems
by: Elnawawy, Mohammed, et al.
Published: (2024)

CRUPL: A Semi-Supervised Cyber Attack Detection with Consistency Regularization and Uncertainty-aware Pseudo-Labeling in Smart Grid
by: Dash, Smruti P., et al.
Published: (2025)