Mustafa Abdallah
Computer Science · Purdue University West Lafayette
Publications
82
Citations
703
Est. group size
~2
Recurring co-author estimate
Active years
12
Publishing since 2015
Mustafa Abdallah works on cybersecurity for networked and interdependent systems, including defense strategies for attack graphs, security in IoT and autonomous vehicle systems, and network intrusion detection. A major theme in his recent work is applying explainable AI (methods that make machine-learning decisions understandable to humans) and ensemble learning (combining multiple models for better accuracy) to detect network intrusions and anomalies. He also studies game-theory-based decision-making for allocating limited security resources across complex systems.
Publication output has grown substantially over the last decade, rising from just a few papers per year before 2020 to a peak of 26 in 2024, indicating an accelerating and currently high level of research activity.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Deceptive Defense Model for Better Securing Networked Systems Modeled by Attack Graphs
IEEE Transactions on Control of Network Systems · 2026
- A comparative analysis of DNN-based white-box explainable AI methods in network security
EURASIP Journal on Information Security · 2025
- A systematic evaluation of white-box explainable AI methods for anomaly detection in IoT systems
Internet of Things · 2025
- Evaluation-free Time-series Forecasting Model Selection via Meta-learning
ACM Transactions on Knowledge Discovery from Data · 2025
- Ensemble Learning Framework for Anomaly Detection in Autonomous Driving Systems
Sensors · 2025
- Ensemble-IDS: An Ensemble Learning Framework for Enhancing AI-Based Network Intrusion Detection Tasks
Applied Sciences · 2025
- E-RXAI-IoT: A Systematic Evaluation Framework of Rule-Based XAI Methods for Anomaly Detection in IoT Systems
IEEE Access · 2025
- Selfish or Malicious: Price of malice in human-centric security decision-making for attack graph-based interdependent systems
International Journal of Information Security · 2025
- An ensemble learning framework for enhanced anomaly and failure detection in IoT systems
Cyber Security and Applications · 2025
- AutoAI-IDS: A Meta-Learning-Based Approach for Automating Model Selection Approach for Network Intrusion Detection Tasks
2025
- Ensemble Feature Selection for Network Intrusion Detection Systems Using Explainable AI: A Frequency-Based Approach
2025
- CBDRA-IS: Centrality-Based Defense Resource Allocation for Securing Interdependent Systems
ACM Transactions on Privacy and Security · 2025
- SAG-ERC: Securing Attack-Graph-based Systems through Node Embedding, Ranking, and Clustering
2025
- Ensemble Feature Selection for Network Intrusion Detection Systems Using Explainable AI: A Frequency-Based Approach
2025
- A Novel Method for Risk Calculation of Access Control Policies for Physical Security of Buildings
2025
- arXiv (Cornell University)×19
- IEEE Access×8
- Research Square×4
- Applied Sciences×3
- Sensors×3
- Ankit Shah
Computer Science · Indiana University
- Sishuai Gong
Computer Science · Purdue University West Lafayette
- Charalampos Katsis
Computer Science · Purdue University West Lafayette
- Bharat Bhargava
Computer Science · Purdue University West Lafayette
- Anand Mudgerikar
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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