collaborators

8 papers

cs.CR2026

HilEnT: Hilbert, Entropy Transformed Image Based Malware Detection

Rahul Kale, Thesath Wijayasiri, Kar Wai Fok +1

With the increasing threat of malware across various software related domains, malware detection and classification is critical to determine the response actions. Different strateg…

cs.CR2026

TIER: Trajectory-Invariant Explanation Regularization for Membership Privacy

Varun Sharma, Kar Wai Fok, Vrizlynn L. L. Thing

Explainability is central to building trustworthy AI, yet explanation interfaces can inadvertently provide adversaries with an expanded privacy-related attack surfaces. Recent stud…

cs.CR2026

DE-FIVE: Detecting Malicious Image Prompts via Fourier Features and Image Vector Embeddings

Xingwei Zhong, Varun Sharma, Kar Wai Fok +1

Vision language models (VLMs) employ both visual and textual modalities to enable advanced vision-language inference. However, incorporating visual modalities expands the attack su…

cs.CR2026

Enhanced Consistency Bi-directional GAN (CBiGAN) for Malware Anomaly Detection

Thesath Wijayasiri, Kar Wai Fok, Vrizlynn L. L. Thing

Static malware analysis remains a core technique in cybersecurity due to its ability to assess potentially malicious software without execution. Nevertheless, many existing static…

cs.CR2025

DefenSee: Dissecting Threat from Sight and Text -- A Multi-View Defensive Pipeline for Multi-modal Jailbreaks

Zihao Wang, Kar Wai Fok, Vrizlynn L. L. Thing

Multi-modal large language models (MLLMs), capable of processing text, images, and audio, have been widely adopted in various AI applications. However, recent MLLMs integrating ima…

cs.CR2025

Enhanced MLLM Black-Box Jailbreaking Attacks and Defenses

Xingwei Zhong, Kar Wai Fok, Vrizlynn L. L. Thing

Multimodal large language models (MLLMs) comprise of both visual and textual modalities to process vision language tasks. However, MLLMs are vulnerable to security-related issues,…