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20222026
most citedA Capability-based Distributed Authorization System to Enforce Context-aware Permission Sequences

7 citations · 8 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

PhantomCall: Evading ML Malware Detectors via Function Call Graph Perturbation

Md Ajwad Akil, Adrian Shuai Li, Imtiaz Karim +3

Prior adversarial attacks on Windows PE malware detectors target raw bytes, PE headers, or intra-function control-flow graphs, leaving the function call graph (FCG) unexplored as a…

cs.CR2026

Can Drift-Adaptive Malware Detectors Be Made Robust? Attacks and Defenses Under White-Box and Black-Box Threats

Adrian Shuai Li, Md Ajwad Akil, Elisa Bertino

Concept drift and adversarial evasion are two major challenges for deploying machine learning-based malware detectors. While both have been studied separately, their combination, t…

cs.CR2025

LFreeDA: Label-Free Drift Adaptation for Windows Malware Detection

Adrian Shuai Li, Elisa Bertino

Machine learning (ML)-based malware detectors degrade over time as concept drift introduces new and evolving families unseen during training. Retraining is limited by the cost and…

cs.CR2025

LLMalMorph: On The Feasibility of Generating Variant Malware using Large-Language-Models

Md Ajwad Akil, Adrian Shuai Li, Imtiaz Karim +4

Large Language Models (LLMs) have transformed software development and automated code generation. Motivated by these advancements, this paper explores the feasibility of LLMs in mo…

cs.CR2024

Revisiting Concept Drift in Windows Malware Detection: Adaptation to Real Drifted Malware with Minimal Samples

Adrian Shuai Li, Arun Iyengar, Ashish Kundu +1

In applying deep learning for malware classification, it is crucial to account for the prevalence of malware evolution, which can cause trained classifiers to fail on drifted malwa…

cs.CR2024★ 1 cited

Transfer Learning for Security: Challenges and Future Directions

Adrian Shuai Li, Arun Iyengar, Ashish Kundu +1

Many machine learning and data mining algorithms rely on the assumption that the training and testing data share the same feature space and distribution. However, this assumption m…

cs.CR2022★ 7 cited

A Capability-based Distributed Authorization System to Enforce Context-aware Permission Sequences

Adrian Shuai Li, Reihaneh Safavi-Naini, Philip W. L. Fong

Controlled sharing is fundamental to distributed systems. We consider a capability-based distributed authorization system where a client receives capabilities (access tokens) from…