Dr. Sajal Saha
Department of Computer Science · Faculty of Mathematics & Science

Dr. Sajal Saha

Assistant Professor  ·  Founder, INFORM Lab  ·  Brock University

Cybersecurity Internet Traffic Forecasting Anomaly Detection Federated Learning Explainable AI IoT Security Deep Learning Blockchain Security LLMs for Networks

About

Dr. Sajal Saha is an Assistant Professor in the Department of Computer Science at Brock University. He is the founder of the Intelligent Network Forecasting, Observation, and Risk Mitigation (INFORM) Lab, where he leads research on cybersecurity, Internet traffic forecasting, and anomaly detection.

Before joining Brock, Dr. Saha held academic and research positions at the University of Northern British Columbia (UNBC), Western University, and Seneca College. His work spans AI-driven security systems, privacy-preserving machine learning, and next-generation network intelligence for 6G environments.

Dr. Saha is committed to Equity, Diversity, and Inclusion in his research group, and actively encourages applications from underrepresented communities in STEM.

Research Areas

Internet Traffic Forecasting

ML and LLM-based forecasting models for network traffic classification, anomaly detection, and proactive network management. Includes transfer learning and wavelet-based approaches for small ISP networks.

Cyber-Attack Detection & Mitigation

AI-driven real-time cyber-threat prediction including DDoS detection, RAG-based incident response, and explainable AI for transparent security decision-making.

Federated Learning & Privacy

Privacy-preserving anomaly detection using federated learning, differential privacy, and blockchain-based aggregation for resilient distributed security systems.

AI for Wireless & IoT Networks

Deep learning for spectrum sensing, anomaly forecasting, and end-to-end IoT security frameworks leveraging LLMs in next-generation 6G networks.

Large Language Models for Security

Fine-tuning and deploying domain-specific LLMs for cyberattack mitigation, network intrusion response, and privacy-preserving cross-silo applications.

Network Intrusion Detection

Ensemble deep learning frameworks (ENIDS), adversarially resilient ML models, and explainable AI for robust network intrusion detection in mobile and IoT environments.

Publications

762 Citations
13 h-index
15 i10-index
47 Total Papers
📊 Metrics from Google Scholar · Updated 2025
J14
A Hybrid Deep Learning Model for Adversarially Resilient Internet Traffic Prediction2026
S. Saha, S. Das, G.H.S. Carvalho
Computers and Electrical Engineering, Vol. 130, 2026 [Scholar ↗]
Elsevier Cited: 1
J13
Overcoming Data Limitations in Internet Traffic Forecasting: LSTM Models with Transfer Learning and Wavelet Augmentation2025
S. Saha, A. Haque, G. Sidebottom
Computer Communications, Vol. 242, 2025 [PDF]
IF: 4.3 Q1 Elsevier · SCIE Cited: 4
J12
Predicting and Mitigating Cyber Threats through Data Mining and Machine Learning2024
N. Samia, S. Saha, A. Haque
Computer Communications, Vol. 228, 2024 [PDF]
IF: 4.3 Q1 Elsevier · SCIE Cited: 24
J11
ENIDS: A Deep Learning-Based Ensemble Framework for Network Intrusion Detection Systems2024
I.M. Sayem, M.I. Sayed, S. Saha, A. Haque
IEEE Transactions on Network and Service Management, Vol. 21(5), 2024 [PDF]
IF: 5.4 CiteScore: 10.5 Q1 IEEE · SCIE Cited: 37
J10
Multi-Step Internet Traffic Forecasting Models with Variable Forecast Horizons for Proactive Network Management2024
S. Saha, A. Haque, G. Sidebottom
Sensors, 24(6), 1871, 2024 [DOI]
IF: 3.5 Q2 MDPI · SCIE Cited: 10
J9
Analyzing the Impact of Outlier Data Points on Multi-Step Internet Traffic Prediction using Deep Sequence Models2023
S. Saha, A. Haque, G. Sidebottom
IEEE Transactions on Network and Service Management, Vol. 20(2), pp. 1345–1362, 2023 [PDF]
IF: 5.4 CiteScore: 10.5 Q1 IEEE · SCIE Cited: 25
J8
Android Malware Classification using Optimum Feature Selection and Ensemble Machine Learning2023
R. Islam, M.I. Sayed, S. Saha, M.J. Hossain, M.A. Masud
Internet of Things and Cyber-Physical Systems, Vol. 3, pp. 100–111, 2023 [PDF]
Elsevier · KeAi Cited: 102
J7
L-fuzzy Concept Analysis using Fuzzy Categories2023
G. Addison, A. Izadpanahi, S. Saha, M. Winter
Fuzzy Sets and Systems, Vol. 460, pp. 72–102, 2023 [PDF]
IF: 3.9 Q1 Elsevier · SCIE Cited: 4
J6
Towards an Optimized Ensemble Feature Selection for DDoS Detection using Both Supervised and Unsupervised Method2022
S. Saha, A.T. Priyoti, A. Sharma, A. Haque
Sensors, Vol. 22(23), 9144, 2022 [PDF]
IF: 3.5 Q2 MDPI · SCIE Cited: 27
J5
Network Intrusion Detection and Comparative Analysis using Ensemble Machine Learning and Feature Selection2021
S. Das, S. Saha, A.T. Priyoti, E.K. Roy, F.T. Sheldon, A. Haque, S. Shiva
IEEE Transactions on Network and Service Management, Vol. 19(4), pp. 4821–4833, 2021
IF: 5.4 CiteScore: 10.5 Q1 IEEE · SCIE Cited: 137
C25
Weighted Reciprocal Rank Fusion RAG for Context-Aware DoS Attack Mitigation2026
A. Kafi, S. Saha, N. Shahriar
IEEE CCNC, 2026
CORE: B IEEE ComSoc Cited: 1
C24
RAID: A Reputation-Based Aggregation for Intrusion Detection in Federated Learning2026
N. Parvizi, S. Saha, N. Shahriar
IEEE CCNC, 2026
CORE: B IEEE ComSoc
C23
Modeling and Prediction of Network Failures: A Machine Learning Approach2025
C. Saha, S. Saha, A. Haque
IEEE ICC Workshops, 2025
CORE: B IEEE ComSoc Cited: 1
C22
Autonomous Cyber Incident Response Using Reasoning and Action2025
S. Baral, S. Saha, A. Haque
IEEE IWCMC, 2025
IEEE ComSoc Cited: 2
C21
Resilient Federated Learning for DDoS Detection with Multi-Krum Aggregation and Anomaly Detection2025
S. Saha, M. Sayed, M.M. Rahman, M. Faezipour, S. Bhatt
IEEE SmartNet, 2025
IEEE Cited: 3
C20
ConvLSTMTransNet: A Hybrid Deep Learning Approach for Internet Traffic Telemetry2024
S. Saha, S. Das, G.H.S. Carvalho
IEEE VCC, 2024
IEEE Cited: 6
C19
An Adaptive End-To-End IoT Security Framework Using Explainable AI and LLMs2024
S. Saha, S. Baral, A. Haque
IEEE WF-IoT, 2024
IEEE ComSoc Cited: 29
C18
Optimizing Internet Traffic Predictions with a Novel Deep Learning EMD-KNN Framework2024
S. Saha, S. Baral, A. Haque
IEEE IWCMC, 2024
IEEE ComSoc Cited: 3
C17
Advancing Network Resilience Through Data Mining and Machine Learning in Cybersecurity2024
N. Samia, S. Saha, A. Haque
IEEE DRCN, 2024
IEEE Cited: 5
C16
Examining Generative Adversarial Network for Smart Home DDoS Traffic Generation2023
R.I. Nekvi, S. Saha, Y. Al Mtawa, A. Haque
IEEE ISNCC, 2023
IEEE Cited: 5
C15
Empirical Mode Decomposition and Stationary Wavelet Transformation in Internet Traffic Prediction2023
S. Saha, M.I. Sayed, A. Haque
IEEE INFOCOM Workshops, 2023
CORE: A* IEEE · Top Networking Venue Cited: 3
C14
Wavelet-Based Hybrid Machine Learning Model for Out-of-distribution Internet Traffic Prediction2023
S. Saha, A. Haque
IEEE/IFIP NOMS, 2023
IEEE · IFIP Cited: 3
C13
Out-of-Distribution Internet Traffic Prediction Generalization using Deep Sequence Model2023
S. Saha, A. Haque
IEEE ICC, 2023
CORE: B IEEE ComSoc · Flagship Cited: 3
C12
Transfer Learning Based Efficient Traffic Prediction with Limited Training Data2023
S. Saha, A. Haque, G. Sidebottom
IEEE CCNC, 2023
CORE: B IEEE ComSoc Cited: 10
C11
Deep Learning Based Malapps Detection in Android Powered Mobile Cyber-Physical System2023
M.I. Sayed, S. Saha, A. Haque
IEEE ICNC, 2023
IEEE Cited: 6
C10
A Multi-Classifier for DDoS Attacks using Stacking Ensemble Deep Neural Network2022
M.I. Sayed, I.M. Sayem, S. Saha, A. Haque
IEEE IWCMC, 2022
IEEE ComSoc Cited: 28
C9
An Empirical Study on Internet Traffic Prediction using Statistical Rolling Model2022
S. Saha, A. Haque, G. Sidebottom
IEEE IWCMC, 2022
IEEE ComSoc Cited: 17
C8
Towards an Ensemble Regressor Model for ISP Traffic Prediction with Anomaly Detection and Mitigation2022
S. Saha, A. Haque, G. Sidebottom
IEEE ISNCC, 2022
IEEE Cited: 8
C7
Deep Sequence Modeling for Anomalous ISP Traffic Prediction2022
S. Saha, A. Haque, G. Sidebottom
IEEE ICC, 2022
CORE: B IEEE ComSoc · Flagship Cited: 19
C6
Towards an Optimal Feature Selection Method for AI-Based DDoS Detection System2022
S. Saha, A.T. Priyoti, A. Sharma, A. Haque
IEEE CCNC, 2022
CORE: B IEEE ComSoc Cited: 38
C5
Which Programming Language and Platform Developers Prefer for the Development? A Study Using Stack Overflow2018
S. Saha, G.M.M. Bashir, M.R. Talukder, J. Karmaker, M.S. Islam
ICISET 2018, IEEE
IEEE Cited: 4
C4
IoT Based Automated Fish Farm Aquaculture Monitoring System2018
S. Saha, R.H. Rajib, S. Kabir
ICISET 2018, IEEE
IEEE Cited: 148

Teaching

COSC 4P84
Introduction to Natural Language Processing
📅 Fall 2024 4th Year 0.5 Credits
A theoretical and methodological introduction to computational modelling of natural language, covering language modelling, parsing, machine translation, transformers, LLMs, and ML techniques for NLP.
Coming Soon
More courses will be added
Additional courses for Winter 2025 and future terms will appear here.

Awards & Distinctions

🥇
Nominee — Governor General's Gold Medal Award Western University · Outstanding academic achievement at the graduate level
🎓
Distinguished Graduate Student Award Goodman School of Business, Brock University · Exceptional professional and personal achievements
💼
Mitacs Accelerate Research Fellowship Western University · Supporting research projects with industry collaboration
📚
Western Graduate Research Scholarship (WGRS) Western University · In recognition of academic excellence
🌐
Provost's Brock University International Scholarship Brock University · Supporting international graduate students
🔬
DGS Spring Research Fellowship Brock University · Spring 2019 research activities funding
🏅
Graduate Fellowship Brock University · Acknowledging academic and research excellence
🏅
Prime Minister Gold Award & Chancellor Gold Award & Dean's Award Patuakhali Science & Technology University · Outstanding academic performance

Prospective Students

The INFORM Lab at Brock University welcomes highly motivated undergraduate, MSc, and prospective PhD students passionate about cybersecurity, Internet traffic forecasting, federated learning, and AI-driven security systems.

What We Look For

  • Strong background in CS, ML, or cybersecurity
  • Excellent Python / deep learning skills
  • Research curiosity and long-term commitment
  • Network/AI security experience (a plus)

Current Opportunities

  • MSc Research Positions
  • Undergraduate Research Assistants
  • Mitacs Globalink / Accelerate Internships

Supervision Philosophy

  • Mentorship-focused, research-independent
  • Strong technical foundations
  • Ethical AI practices
  • Interdisciplinary collaboration

EDI Commitment

  • Inclusive and welcoming environment
  • Aligned with Tri-Agency EDI Statement
  • Underrepresented groups actively encouraged

How to Apply

Email with subject line Prospective Student – INFORM Lab and attach your CV, unofficial transcripts, a 1-page research statement, and any publications or GitHub links.

ssaha@brocku.ca

Contact

Office

Department of Computer Science
Brock University
1812 Sir Isaac Brock Way
St. Catharines, ON L2S 3A1