M. Subramanyam

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...

Hybrid Quantum Classical Deep Learning Model for Encrypted HTTPS Traffic Classification

As cyberattacks evolve in greater impact and complexity, they have Network traffic classification is a key component of any modern or intelligent cybersecurity system, which includes monitoring, managing network resources, detecting intrusions, and managing application-aware network operations. Unfortunately, with the...

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...

Multi-Agent Reinforcement Learning System for Autonomous Network Intrusion Response

Cyber threats are becoming so complicated and rampant in today's highly connected digital world that there is a tremendous need for intelligent, adaptive IDS. Detecting and responding against network intrusions in real-time is the aim of the present work, which proposes a real-time Network Intrusion Detection and Autom...

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...

Autonomous LLM Agent for Real-Time DDoS Attack Classification and Mitigation Rule Generation

Large-scale DDoS attacks remain a serious threat to today's networked systems, which aim to make services unavailable by sending a massive amount of traffic. The traditional detection methods are mostly about attack categorization and are not that context-aware or actionable in providing support to security analysts. W...

LLM Fine-Tuned Threat Intelligence Summarization Agent for CVE Report Automation

In this paper, an intelligent cyber threat intelligence framework involving automated vulnerability severity assessment, contextual risk interpretation and generation of mitigation recommendation is presented. The proposed system has been designed to analyze the CVE-related description of vulnerabilities and the securi...

Transformer-based Network Anomaly Detection System for Intelligent Cyber Security Monitoring

As MNI becomes increasingly vulnerable to new kinds of attacks from the cyber world, accurate and timely detection of intrusions becomes a primary key to the power of cybersecurity. More complex attack patterns, complex traffic interactions within large scales are not very collaborable with the typical signature-based...