158 citations · 461 across the 37 of their papers we have counts for
6 papers · 1 filter
SAGEGAN: Style-Based Anomaly Detection with Gaussian Embeddings using Generative Adversarial Networks
Thesath Wijayasiri, Kar Wai Fok, Vrizlynn L. L. Thing
Malware evolves faster than rule-based and signature-driven detection pipelines. This paper presents SAGEGAN, a benign-only trained malware anomaly detection framework that convert…
Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents
Zihao Wang, Yiming Li, Yutong Wu +8
LLM-based web agents are increasingly deployed in real-world settings such as e-commerce, where they interact extensively with untrusted web content while executing actions that ca…
Explaining Intrusion Alert Decisions of Deep Learning-based Network Intrusion Detection Systems for Security Analysts
Ayush Kumar, Vrizlynn L. L. Thing
In this paper, we present EXP-SEC, a novel framework which can explain the intrusion detection decisions of DL-based NIDS (which lead to security alerts) in a way that is aligned w…
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…
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…
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…