F. Mahammad

AI-Powered Contract Analysis System Using OCR, NLP, and Large Language Models

The process of manually analyzing contracts often takes long amounts of time, requires legal training and knowledge, and is not typically affordable to individuals and small businesses. In addition, current forms of analysis offer only moderately compliant output due to the fact that they typically only provide basic f...

SGAASS: A Closed-Loop Adaptive Framework for Personalized Skill Gap Analysis and Deadline-Aware Study Scheduling Using NLP

The fast-changing developments in industries present a new challenge by leaving learners' ability to meet the expectations of employers. Hence, available educational platforms keep providing learning materials that are based more on the general popularity of specific subjects than on assessing the skills lacking for fu...

Explainable Lightweight Hybrid Ensemble Learning for Android Malware Detection Using Optimized Permission Features

The increase in the number of Android applications being developed and used has increased the potential threat of malware attacks on mobile devices and Internet of Things (IoT) devices that have little processing power available to them. The current methods for detecting malware use two different types of techniques. O...

Variational Quantum Eigen Solver Based Molecular Toxicity Prediction for Drug Candidate Screening

Toxic molecular compounds can be identified early, which can lower drug development costs and avoid failures in candidate screening. However, current machine learning methods typically require the creation of handcrafted molecular descriptors and are not effective at modelling complex molecular relationships. In this s...

Quantum Reinforcement Learning Agent for Adaptive Firewall Rule Optimization Under Dynamic Attacks

As attacks grow in sophistication, the requirements for intelligent and adaptive security structures that can make real-time decisions on whether to defend or not, exceed what can be achieved with a rule-based approach. This paper aims to explore a Cyber Security system that uses a Quantum Deep Q-Network (QDQN) framewo...

Quantum Federated Learning for Privacy-Preserving Anomaly Detection

Generative Adversarial Network for Synthetic Cyber Attack Traffic Generation and IDS Augmentation

The proposed quantum computing leads to an important security problem in classic key exchange methods for secure file communication. In this paper, we propose a Quantum Key Distribution based secure file encryption scheme for secure storage and transmission of files which uses BB84 Quantum Key Distribution protocol alo...

Quantum Support Vector Machine for Encrypted Botnet Command and Control Traffic Detection Without Payload Inspection

Modern botnets use encrypted Command-and-Control (C2) communications, which poses a major challenge for network security given the fact that payloads are encrypted, which makes the use of traditional signature-based inspection methods ineffective. In this work, we introduce QSVM Shield, a hybrid quantum-classical solut...

Vision Transformer with Attention Rollout for Deepfake Face Image Detection and Localization

Generative AI and synthetic media generation tools have enabled widespread media manipulation tools and raised important privacy concerns with misinformation, identity fraud and the verification of authenticity of media. Most of the current convolution-based deepfake detection methods are hard to be deployed in real sc...

Quantum Computing-based Optimization of Cybersecurity Protocols for Secure Data Protection

The escalation of security attacks has led to a growing complexity and posed serious challenges for traditional IDS paradigms to securing and sustaining a resilient network infrastructure. Current solutions are generally inefficient at optimizing detection parameters, cannot detect attacks that have previously not been...

Graph Neural Network based Lateral Movement Detection in Enterprise Network Traffic

One of the most important pieces of the modern cyberattacks is lateral movement the ability to move around connected systems after the initial compromise and gain access to high-value organizational assets. Conventional approaches to intrusion detection often fail to recognize the sophisticated attack behaviors while b...

YOLOv8-Powered Intelligent Surveillance: An Integrated Real-Time Framework for Crowd Management, Crime Prevention, and Workplace Safety Monitoring using AI and ML

The evolving complexity of urban environments and the effectiveness of traditional CCTV surveillance is making it increasingly difficult to ensure public safety, effective crowd management, crime prevention, and workplace security solutions. However, the traditional approach to surveillance is largely manual, leading t...