5 papers
ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to adapt, and limited in their abil…
Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +2
Cybersecurity demands both rapid pattern recognition and deliberative reasoning, yet purely neural or purely symbolic approaches each address only one side of this duality. Neuro-S…
SymRAG: Efficient Neuro-Symbolic Retrieval Through Adaptive Query Routing
Safayat Bin Hakim, Muhammad Adil, Alvaro Velasquez +1
Current Retrieval-Augmented Generation systems use uniform processing, causing inefficiency as simple queries consume resources similar to complex multi-hop tasks. We present SymRA…
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach
Safayat Bin Hakim, Muhammad Adil, Kamal Acharya +1
The escalating sophistication of Android malware poses significant challenges to traditional detection methods, necessitating innovative approaches that can efficiently identify an…
xIDS-EnsembleGuard: An Explainable Ensemble Learning-based Intrusion Detection System
Muhammad Adil, Mian Ahmad Jan, Safayat Bin Hakim +2
In this paper, we focus on addressing the challenges of detecting malicious attacks in networks by designing an advanced Explainable Intrusion Detection System (xIDS). The existing…