195 citations · 225 across the 14 of their papers we have counts for
17 papers
Connecting the Dots in Agentic AI Security: A Cross-Dimensional Threat Taxonomy, Evaluation Maturity, and Open Challenges
Heewon Baek, Alsharif Abuadbba, Kristen Moore +2
Agentic AI extends LLM security beyond generated content to persistent state, autonomous actions, tool use, and interactions with humans and other agents. Existing threat classific…
DEFEAT: Stitching Fragmented File I/O Contexts for Early Ransomware Detection
Muhammad Ejaz Ahmed, Hyoungshick Kim, Mohsen Ali Alawami +4
Ransomware increasingly fragments its file operations across temporary and intermediate files, scattering the semantic context that links individual I/O events to an overarching en…
Shifting from Injection to Interaction: Rethinking Web Security in the Age of LLMs and Beyond
Nivedita Singh, Alsharif Abuadbba, Yansong Gao +2
Large language models (LLMs) are becoming integral to web applications and browser agents, transforming online interactions while introducing new attack vectors and reshaping longs…
Human Society-Inspired Approaches to Agentic AI Security: The 4C Framework
Alsharif Abuadbba, Nazatul Sultan, Surya Nepal +1
AI is moving from domain-specific autonomy in closed, predictable settings to large-language-model-driven agents that plan and act in open, cross-organizational environments. As a…
Adversarial Attacks Against Automated Fact-Checking: A Survey
Fanzhen Liu, Alsharif Abuadbba, Kristen Moore +5
In an era where misinformation spreads freely, fact-checking (FC) plays a crucial role in verifying claims and promoting reliable information. While automated fact-checking (AFC) h…
RINSER: Accurate API Prediction Using Masked Language Models
Muhammad Ejaz Ahmed, Christopher Cody, Muhammad Ikram +5
Malware authors commonly use obfuscation to hide API identities in binary files, making analysis difficult and time-consuming for a human expert to understand the behavior and inte…
Towards Faithful Class-level Self-explainability in Graph Neural Networks by Subgraph Dependencies
Fanzhen Liu, Xiaoxiao Ma, Jian Yang +6
Enhancing the interpretability of graph neural networks (GNNs) is crucial to ensure their safe and fair deployment. Recent work has introduced self-explainable GNNs that generate e…
Adaptive alert prioritisation in security operations centres via learning to defer with human feedback
Fatemeh Jalalvand, Mohan Baruwal Chhetri, Surya Nepal +1
Alert prioritisation (AP) is crucial for security operations centres (SOCs) to manage the overwhelming volume of alerts and ensure timely detection and response to genuine threats,…
Enhancing Malware Fingerprinting through Analysis of Evasive Techniques
Alsharif Abuadbba, Sean Lamont, Ejaz Ahmed +6
As malware detection evolves, attackers adopt sophisticated evasion tactics. Traditional file-level fingerprinting, such as cryptographic and fuzzy hashes, is often overlooked as a…
Comprehensive Evaluation of Cloaking Backdoor Attacks on Object Detector in Real-World
Hua Ma, Alsharif Abuadbba, Yansong Gao +2
The exploration of backdoor vulnerabilities in object detectors, particularly in real-world scenarios, remains limited. A significant challenge lies in the absence of a natural phy…
From Solitary Directives to Interactive Encouragement! LLM Secure Code Generation by Natural Language Prompting
Shigang Liu, Bushra Sabir, Seung Ick Jang +5
Large Language Models (LLMs) have shown remarkable potential in code generation, making them increasingly important in the field. However, the security issues of generated code hav…
Systematic Literature Review of AI-enabled Spectrum Management in 6G and Future Networks
Bushra Sabir, Shuiqiao Yang, David Nguyen +7
Artificial Intelligence (AI) has advanced significantly in various domains like healthcare, finance, and cybersecurity, with successes such as DeepMind's medical imaging and Tesla'…
SoK: Can Trajectory Generation Combine Privacy and Utility?
Erik Buchholz, Alsharif Abuadbba, Shuo Wang +2
While location trajectories represent a valuable data source for analyses and location-based services, they can reveal sensitive information, such as political and religious prefer…
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
Hua Ma, Shang Wang, Yansong Gao +7
All current backdoor attacks on deep learning (DL) models fall under the category of a vertical class backdoor (VCB) -- class-dependent. In VCB attacks, any sample from a class act…
TransCAB: Transferable Clean-Annotation Backdoor to Object Detection with Natural Trigger in Real-World
Hua Ma, Yinshan Li, Yansong Gao +6
Object detection is the foundation of various critical computer-vision tasks such as segmentation, object tracking, and event detection. To train an object detector with satisfacto…
SoftTRR: Protect Page Tables Against RowHammer Attacks using Software-only Target Row Refresh
Zhi Zhang, Yueqiang Cheng, Minghua Wang +7
Rowhammer attacks that corrupt level-1 page tables to gain kernel privilege are the most detrimental to system security and hard to mitigate. However, recently proposed software-on…
Deep Learning for Community Detection: Progress, Challenges and Opportunities
Fanzhen Liu, Shan Xue, Jia Wu +6
As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and d…