:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Das, Sanjay, Bhattacharya, Swastik, Kundu, Shamik, Raha, Arnab, Kundu, Souvik, Basu, Kanad
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Machine Learning
Online Access:	https://arxiv.org/abs/2512.15778
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs
by: Das, Sanjay, et al.
Published: (2024)

Enhancing Large Language Models for Hardware Verification: A Novel SystemVerilog Assertion Dataset
by: Menon, Anand, et al.
Published: (2025)

SafeCiM: Investigating Resilience of Hybrid Floating-Point Compute-in-Memory Deep Learning Accelerators
by: Bhattacharya, Swastik, et al.
Published: (2025)

LMN: A Tool for Generating Machine Enforceable Policies from Natural Language Access Control Rules using LLMs
by: Sonune, Pratik, et al.
Published: (2025)

Linearizing Models for Efficient yet Robust Private Inference
by: Sarkar, Sreetama, et al.
Published: (2024)

Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
by: Kundu, Satwik, et al.
Published: (2024)

Using Retriever Augmented Large Language Models for Attack Graph Generation
by: Prapty, Renascence Tarafder, et al.
Published: (2024)

Automated Consistency Analysis of LLMs
by: Patwardhan, Aditya, et al.
Published: (2025)

PrisonBreak: Jailbreaking Large Language Models with at Most Twenty-Five Targeted Bit-flips
by: Coalson, Zachary, et al.
Published: (2024)

Security Concerns in Quantum Machine Learning as a Service
by: Kundu, Satwik, et al.
Published: (2024)

Deep-Lock: Secure Authorization for Deep Neural Networks
by: Alam, Manaar, et al.
Published: (2020)

SWaRL: Safeguard Code Watermarking via Reinforcement Learning
by: Javidnia, Neusha, et al.
Published: (2026)

Testing Credibility of Public and Private Surveys through the Lens of Regression
by: Basu, Debabrota, et al.
Published: (2024)

Transfer Learning for Security: Challenges and Future Directions
by: Li, Adrian Shuai, et al.
Published: (2024)

Towards Harnessing the Power of LLMs for ABAC Policy Mining
by: Babasaheb, More Aayush, et al.
Published: (2025)

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
by: Ghosh, Archisman, et al.
Published: (2025)

Towards Strong Certified Defense with Universal Asymmetric Randomization
by: Hong, Hanbin, et al.
Published: (2025)

XAMBA: Enabling Efficient State Space Models on Resource-Constrained Neural Processing Units
by: Das, Arghadip, et al.
Published: (2025)

Generation of Human Comprehensible Access Control Policies from Audit Logs
by: Kumar, Gautam, et al.
Published: (2026)

A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
by: Purohit, Kiran, et al.
Published: (2023)

Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator
by: Ramachandran, Akshat, et al.
Published: (2025)

Catastrophic Overfitting: A Potential Blessing in Disguise
by: Zhao, Mengnan, et al.
Published: (2024)

Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
by: Feng, Shuya, et al.
Published: (2024)

Adversarial Attacks on Locally Private Graph Neural Networks
by: Varun, Matta, et al.
Published: (2026)

A Generative Approach to Surrogate-based Black-box Attacks
by: Moraffah, Raha, et al.
Published: (2024)

Impactful Bit-Flip Search on Full-precision Models
by: Benedek, Nadav, et al.
Published: (2024)

Graphene: Infrastructure Security Posture Analysis with AI-generated Attack Graphs
by: Jin, Xin, et al.
Published: (2023)

Advancing Honeywords for Real-World Authentication Security
by: Das, Sudiksha, et al.
Published: (2025)

CryptRISC: A Secure RISC-V Processor for High-Performance Cryptography with Power Side-Channel Protection
by: Srivastava, Amisha, et al.
Published: (2026)

SilentStriker:Toward Stealthy Bit-Flip Attacks on Large Language Models
by: Xu, Haotian, et al.
Published: (2025)

PLRV-O: Advancing Differentially Private Deep Learning via Privacy Loss Random Variable Optimization
by: Yang, Qin, et al.
Published: (2025)

Guardians of the Quantum GAN
by: Ghosh, Archisman, et al.
Published: (2024)

LMO-DP: Optimizing the Randomization Mechanism for Differentially Private Fine-Tuning (Large) Language Models
by: Yang, Qin, et al.
Published: (2024)

SpectralGuard: Detecting Memory Collapse Attacks in State Space Models
by: Bonetto, Davi
Published: (2026)

QubitHammer: Remotely Inducing Qubit State Change on Superconducting Quantum Computers
by: Tan, Yizhuo, et al.
Published: (2025)

State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space
by: Guo, Ji, et al.
Published: (2026)

Bit-Exact AI Inference Verification Without Performance Tradeoffs
by: Cankaya, Naci
Published: (2026)

Exploiting Class Probabilities for Black-box Sentence-level Attacks
by: Moraffah, Raha, et al.
Published: (2024)

Optimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques
by: Fahim, Abrar, et al.
Published: (2025)

Bits for Privacy: Evaluating Post-Training Quantization via Membership Inference
by: Zhang, Chenxiang, et al.
Published: (2025)