172 citations · 802 across the 171 of their papers we have counts for
23 papers · 1 filter
GrayShield: Bit-Level Sanitization for Transformer Model Supply-Chain Security
Armstrong Foundjem, Tsung-Hsien Chuang, Foutse Khomh +1
Transformer models such as BERT and Vision Transformer~(ViT) achieve strong performance via densely parameterized attention backbones. However, the least significant bits~(LSBs) of…
Swarm-Driven Multi-Agent Reasoning for Smart City Security
Saeid Jamshidi, Kawser Wazed Nafi, Carol Fung +1
Modern smart cities are interconnected cyber-physical ecosystems where heterogeneous devices exchange data and control commands. Coordinated attacks may appear as weak and distribu…
Security Engineering of OpenClaw: Analyzing Attack Surface Expansion and Trust-Boundary Violations
Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1
Agentic large language model (LLM) systems can now execute actions, not only produce text. When model outputs trigger privileged operations such as shell commands, browser automati…
Game-Theoretic Multi-Agent Control for Robust Contextual Reasoning in LLMs
Saeid Jamshidi, Amin Nikanjam, Arghavan Moradi Dakhel +2
Large Language Models (LLMs) in multi-turn interactions maintain evolving context rather than generating isolated responses, making them vulnerable to prompt-injection and context-…
Hallucination Cascade: Analyzing Error Propagation in Multi-Agent LLM Systems
Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1
Large Language Models (LLMs) generate fluent text but remain vulnerable to hallucinations, producing unsupported, inconsistent, and factually incorrect claims. Most prior work trea…
Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems
Saeid Jamshidi, Foutse Khomh, Carol Fung +1
The adoption of Internet of Things (IoT) systems at the network edge of smart architectures is increasing rapidly, intensifying the need for security mechanisms that are both adapt…
Multi-Agent LLM Governance for Safe Two-Timescale Reinforcement Learning in SDN-IoT Defense
Saeid Jamshidi, Negar Shahabi, Foutse Khomh +2
Software-Defined Networking (SDN) is increasingly adopted to secure Internet-of-Things (IoT) networks due to its centralized control and programmable forwarding. However, SDN-IoT d…
Tri-LLM Cooperative Federated Zero-Shot Intrusion Detection with Semantic Disagreement and Trust-Aware Aggregation
Saeid Jamshidi, Omar Abdul Wahab, Foutse Khomh +1
Federated learning (FL) has become an effective paradigm for privacy-preserving, distributed Intrusion Detection Systems (IDS) in cyber-physical and Internet of Things (IoT) networ…
Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines
Saeid Jamshidi, Kawser Wazed Nafi, Arghavan Moradi Dakhel +2
Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-augmented generation (RAG), and multi-…
Multi-Agent Framework for Threat Mitigation and Resilience in AI-Based Systems
Armstrong Foundjem, Lionel Nganyewou Tidjon, Leuson Da Silva +1
Machine learning (ML) underpins foundation models in finance, healthcare, and critical infrastructure, making them targets for data poisoning, model extraction, prompt injection, a…
Multi-LLM Energy Reasoning for Binary-Free Zero-Day IoT Detection
Saeid Jamshidi, Foutse Khomh, Kawser Wazed Nafi +2
Securing Internet of Things (IoT) firmware remains difficult due to proprietary binaries, stripped symbols, heterogeneous architectures, and limited access to executable code. Exis…
Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation
Saeid Jamshidi, Arghavan Moradi Dakhel, Kawser Wazed Nafi +1
The Model Context Protocol (MCP) enables Large Language Models (LLMs) to interact with external tools via tool descriptors, thereby extending their capabilities for task execution,…
Think Fast: Real-Time IoT Intrusion Reasoning Using IDS and LLMs at the Edge Gateway
Saeid Jamshidi, Amin Nikanjam, Negar Shahabi +4
As the number of connected IoT devices continues to grow, securing these systems against cyber threats remains a major challenge, especially in environments with limited computatio…
Green Deep Reinforcement Learning for IoT Edge Intrusion Detection
Saeid Jamshidi, Foutse Khomh, Rolando Herrero +2
The rapid expansion of the Internet of Things (IoT) has intensified cybersecurity challenges, particularly in detecting and mitigating Distributed Denial-of-Service (DDoS) attacks…
Application of Deep Reinforcement Learning for Intrusion Detection in Internet of Things: A Systematic Review
Saeid Jamshidi, Amin Nikanjam, Kawser Wazed Nafi +2
The Internet of Things (IoT) has significantly expanded the digital landscape, interconnecting an unprecedented array of devices, from home appliances to industrial equipment. This…
Leveraging Machine Learning Techniques in Intrusion Detection Systems for Internet of Things
Saeid Jamshidi, Amin Nikanjam, Nafi Kawser Wazed +1
As the Internet of Things (IoT) continues to expand, ensuring the security of connected devices has become increasingly critical. Traditional Intrusion Detection Systems (IDS) ofte…
Diffusion-based Adversarial Purification for Intrusion Detection
Mohamed Amine Merzouk, Erwan Beurier, Reda Yaich +2
The escalating sophistication of cyberattacks has encouraged the integration of machine learning techniques in intrusion detection systems, but the rise of adversarial examples pre…
Exploring Security Practices in Infrastructure as Code: An Empirical Study
Alexandre Verdet, Mohammad Hamdaqa, Leuson Da Silva +1
Cloud computing has become popular thanks to the widespread use of Infrastructure as Code (IaC) tools, allowing the community to conveniently manage and configure cloud infrastruct…
Reliable Malware Analysis and Detection using Topology Data Analysis
Lionel Nganyewou Tidjon, Foutse Khomh
Increasingly, malwares are becoming complex and they are spreading on networks targeting different infrastructures and personal-end devices to collect, modify, and destroy victim i…
Threat Assessment in Machine Learning based Systems
Lionel Nganyewou Tidjon, Foutse Khomh
Machine learning is a field of artificial intelligence (AI) that is becoming essential for several critical systems, making it a good target for threat actors. Threat actors exploi…
Data Driven Testing of Cyber Physical Systems
Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh
Consumer grade cyber-physical systems (CPS) are becoming an integral part of our life, automatizing and simplifying everyday tasks. Indeed, due to complex interactions between hard…
SIGMA : Strengthening IDS with GAN and Metaheuristics Attacks
Simon Msika, Alejandro Quintero, Foutse Khomh
An Intrusion Detection System (IDS) is a key cybersecurity tool for network administrators as it identifies malicious traffic and cyberattacks. With the recent successes of machine…
Distributed Differential Privacy via Shuffling
Albert Cheu, Adam Smith, Jonathan Ullman +2
We consider the problem of designing scalable, robust protocols for computing statistics about sensitive data. Specifically, we look at how best to design differentially private pr…