Md Mokammel Haque

Md Mokammel Haque

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

PhD in Computer Science from Macquarie University, Australia. Year: 2014

MSc in Computer Engineering from Kyung Hee University, South Korea. Year: 2008

BSc in Computer Science & Engineering from Chittagong University of Engineering & Technology (CUET), Bangladesh. Year: 2004

Ongoing research

Anomaly Reduction Boundary-Based Oversampling for Rule Miner Model in Financial Fraud Detection

Financial fraud continues to threaten the stability of financial institutions and global markets, necessitating advanced detection mechanisms. Although preventative and security measures are implemented to reduce financial fraud, criminals are constantly adapting and devising new ways to evade fraud prevention systems. In this research we introduce AR-Miner, a novel rule-mining framework that integrates Anomaly Reduction Boundary-Based Oversampling (ARBBO) to address class imbalance and redundant anomalies in financial datasets. By extracting high-confidence relational rules and generating synthetic samples within a safe boundary, we hope AR-Miner significantly improves classification performance.

Detection of Cyclic Alternating Patterns in Sleep Using Deep Learning

Detection of sleep stages is essential for assessing sleep quality and significantly linked to neurological pathologies. Especially, the cyclic alternating patterns (CAP) is considered as vital for understanding and improving sleep quality. Determining CAP phases using electroencephalography (EEG) is mostly rely on classical machine learning techniques and often require manual feature extraction. Here, we want to propose a fully automated deep learning-based technique to detect CAP phases. We want to investigate the possibility of combining Convolution Neural Network with Recurrent Neural Network to improve feature extraction process and detection accuracy. The current state of the art method can detect CAP phases with accuracy of around 80%. 

A Comprehensive Phishing Detection Framework Using Machine Learning Techniques

This framework leverages machine learning (ML) to detect phishing attacks by analyzing various features of websites and emails. It employs supervised learning algorithms trained on datasets containing both phishing and legitimate instances, enabling the model to identify patterns indicative of phishing. Key features analyzed include URL characteristics, website content, and metadata. The framework emphasizes real-time detection, adaptability to new phishing strategies, and scalability to handle large volumes of data. By continuously learning from new data, the ML models enhance their accuracy and efficiency in identifying and mitigating phishing threats.

This research aims a detailed framework for detecting phishing through a URL-based methodology, wherein features derived from URLs are evaluated utilizing machine learning techniques.

 

Research Interest: Cryptography, Information Security, AI driven Cyber Security, Blockchain technology, Algorithm design & Analysis, Computer Networks

  • Journals
    Year Citation
    2024 Islam, S., Haque, M. M., & Karim, A. N. M. R. (2024). A rule-based machine learning model for financial fraud detection. International Journal of Electrical and Computer Engineering, 14(1), 759-771.
    DOI Scopus20
    2023 Reno, S., & Haque, M. M. (2023). Solving blockchain trilemma using off-chain storage protocol. IET Information Security, 17(4), 681-702.
    DOI Scopus15
    2022 Biswas, C., Haque, M. M., & Das Gupta, U. (2022). A Modified Key Sifting Scheme with Artificial Neural Network Based Key Reconciliation Analysis in Quantum Cryptography. IEEE Access, 10, 72743-72757.
    DOI Scopus10
    2022 Haque, M. M., Sarker, S., & Dewan, M. A. A. (2022). Driving maneuver classification from time series data: a rule based machine learning approach. Applied Intelligence, 52(14), 16900-16915.
    DOI Scopus10
    2021 Hossain, M. K., Haque, M. M., & Dewan, M. A. A. (2021). A comparative analysis of semi-supervised learning in detecting burst header packet flooding attack in optical burst switching network. Computers, 10(8), 95.
    DOI Scopus1
    2021 Sarker, S., Haque, M. M., & Dewan, M. A. A. (2021). Driving Maneuver Classification Using Domain Specific Knowledge and Transfer Learning. IEEE Access, 9, 86590-86606.
    DOI Scopus6
    2020 Hossain, M. K., & Haque, M. M. (2020). Semi-supervised learning approach using modified self-training algorithm to counter burst header packet flooding attack in optical burst switching network. International Journal of Electrical and Computer Engineering, 10(4), 4340-4351.
    DOI Scopus3
    2019 Forhad, M. S. A., Hossain, M. S., Rahman, M. O., Rahaman, M. M., Haque, M. M., & Patwary, M. K. H. (2019). An improved fitness function for automated cryptanalysis using genetic algorithm. Indonesian Journal of Electrical Engineering and Computer Science, 13(2), 643-648.
    DOI Scopus14
    2019 Deb, S., & Haque, M. M. (2019). Elliptic curve and pseudo-inverse matrix based cryptosystem for wireless sensor networks. International Journal of Electrical and Computer Engineering, 9(5), 4479-4492.
    DOI Scopus5
    2019 Haque, M. M., & Rahman, M. O. (2019). Analyzing Progressive-BKZ Lattice Reduction Algorithm. International Journal of Computer Network and Information Security, 11(1), 40-46.
    DOI Scopus2
    2019 Patwary, M. K. H., & Haque, M. M. (2019). A semi-supervised machine learning approach using K-means algorithm to prevent burst header packet flooding attack in optical burst switching network. Baghdad Science Journal, 16(3), 804-815.
    DOI Scopus8
    2018 Haque, M. M., & Pieprzyk, J. (2018). Preprocessing optimisation: Revisiting recursive-BKZ lattice reduction algorithm. Iet Information Security, 12(6), 551-557.
    DOI
    2018 Chowdhury, A., Shankaran, R., Kavakli, M., & Haque, M. M. (2018). Sensor Applications and Physiological Features in Drivers' Drowsiness Detection: A Review. IEEE Sensors Journal, 18(8), 3055-3067.
    DOI Scopus160
    2017 Haque, M. M., & Pieprzyk, J. (2017). Analysing recursive preprocessing of BKZ lattice reduction algorithm. Iet Information Security, 11(2), 114-120.
    DOI Scopus2
    2008 Haque, M. M., Pathan, A. S., Hong, C. S., & Huh, E. N. (2008). An asymmetric key-based security architecture for wireless sensor networks. Ksii Transactions on Internet and Information Systems, 2(5), 265-279.
    DOI Scopus25

  • Book Chapters
    Year Citation
    2023 Talukder, D., & Haque, M. M. (2023). A machine learning approach to clinically diagnose human pyrexia cases. In N. Siddique, M. Shamsul Arefin, & A. S. M. Kaiser (Eds.), Applied Intelligence for Industry 4.0 (pp. 90-103). Chapman and Hall/CRC.
    DOI
    2022 Badiuzzaman Biplob, M., & Mokammel Haque, M. (2022). Development of an Efficient ETL Technique for Data Warehouses. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 95, pp. 243-255). Springer Singapore.
    DOI
    2020 Patwary, M. K. H., & Mokammel Haque, M. (2020). A semi-supervised approach to detect malicious nodes in OBS network dataset using gaussian mixture model. In J. Kacprzyk (Ed.), Lecture Notes in Networks and Systems (Vol. 89, pp. 707-719). Springer Singapore.
    DOI Scopus3

  • Conference Papers
    Year Citation
    2024 Provat, A. A., & Haque, M. M. (2024). An Efficient Lightweight Cryptosystem Using Substitution-Shuffling Based Key Generation. In 2023 26th International Conference on Computer and Information Technology, ICCIT 2023 (pp. 1-6). Cox's Bazar, Bangladesh: IEEE.
    DOI
    2024 Reno, S., & Haque, M. M. (2024). An Off-Chain-Based Blockchain with Improved Decentralization. In International Conference on Computer and Information Technology, ICCIT 2023 (pp. 1-6). Cox's Bazar, Bangladesh: IEEE.
    DOI
    2024 Gupta, U. D., Haque, M. M., Reza, A. W., & Arefin, M. S. (2024). Profit Demand Delegated Proof of Stake: Hypothetical Design Concept for Blockchain. In 2024 IEEE Conference on Computing Applications and Systems, COMPAS 2024 (pp. 1-6). Bangladesh: IEEE.
    DOI
    2024 Biplob, M. B., & Haque, M. M. (2024). An Efficient Machine Learning Classification Model for Rainfall Prediction in Bangladesh. In Lecture Notes in Networks and Systems Vol. 867 LNNS (pp. 169-180). Dhaka: Springer Nature Singapore.
    DOI
    2023 Rimon, S. I., & Haque, M. M. (2023). Malware Detection and Classification Using Hybrid Machine Learning Algorithm. In Lecture Notes in Networks and Systems Vol. 569 LNNS (pp. 419-428). Virtual, online: Springer International Publishing.
    DOI Scopus4
    2023 Uddin, M. A., Shahriar, K. T., Haque, M. M., & Sarker, I. H. (2023). Cyber-Attack Detection Through Ensemble-Based Machine Learning Classifier. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST Vol. 491 LNICST (pp. 386-396). Noakhali, Bangladesh: Springer Nature Switzerland.
    DOI
    2023 Reno, S., & Haque, M. M. (2023). Utilizing Off-Chain Storage Protocol for Solving the Trilemma Issue of Blockchain. In Advances in Intelligent Systems and Computing (pp. 169-179). Kolkata, India: Springer.
    DOI
    2022 Shaha, R., Talukder, D., Iqbal, M. A., & Haque, M. M. (2022). TOS: A Relative Metric Approach for Model Selection in Machine Learning Solutions. In Proceedings of 2021 IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2021 (pp. 26-31). Dhaka, Bangladesh: IEEE.
    DOI Scopus3
    2021 Talukder, D., Jahara, F., Barua, S., & Haque, M. M. (2021). OkkhorNama: BdSL Image Dataset for Real Time Object Detection Algorithms. In TENSYMP 2021 - 2021 IEEE Region 10 Symposium (pp. 1-6). Jeju, Korea, Republic of: IEEE.
    DOI Scopus8
    2021 Bhowmik, C., Momin, M. A. I., Shanta, F. J., & Haque, M. M. (2021). Database Security as a Gateway to Privacy Preserving Data Mining. In International Conference on Robotics, Electrical and Signal Processing Techniques (pp. 125-130). DHAKA, Bangladesh: IEEE.
    DOI Scopus3
    2021 Sarker, S., & Haque, M. M. (2021). An Approach Towards Domain Knowledge-Based Classification of Driving Maneuvers with LSTM Network. In Unknown Conference (pp. 469-484). Springer Singapore.
    DOI
    2020 Sarker, S., & Haque, M. M. (2020). A data change rule based empirical framework for labeling unlabeled time series driving data. In 2020 2nd International Conference on Advanced Information and Communication Technology, ICAICT 2020 (pp. 476-479). Dhaka, Bangladesh: IEEE.
    DOI Scopus1
    2019 Biswas, C., Gupta, U. D., & Haque, M. M. (2019). An Efficient Algorithm for Confidentiality, Integrity and Authentication Using Hybrid Cryptography and Steganography. In 2nd International Conference on Electrical Computer and Communication Engineering Ecce 2019 (pp. 1-5). IEEE.
    DOI Scopus39
    2019 Mahmud, N., & Haque, M. M. (2019). Solving Multiple Depot Vehicle Routing Problem (MDVRP) using Genetic Algorithm. In 2nd International Conference on Electrical Computer and Communication Engineering Ecce 2019 (pp. 1-6). IEEE.
    DOI Scopus9
    2019 Naher, N., Asaduzzaman., & Haque, M. M. (2019). Authentication of diffie-hellman protocol against man-in-the-middle attack using cryptographically secure CRC. In Advances in Intelligent Systems and Computing Vol. 811 (pp. 139-150). Springer Singapore.
    DOI Scopus8
    2018 Quaum, M. A., Uddin Haider, S., & Haque, M. M. (2018). An Improved Asymmetric Key Based Security Architecture for WSN. In International Conference on Computer Communication Chemical Material and Electronic Engineering Ic4me2 2018 (pp. 1-5). IEEE.
    DOI Scopus1
    2017 Islam, M. M., Paul, S., & Haque, M. M. (2017). Reducing network overhead of IoTDTLS protocol employing ChaCha20 and Poly1305. In 20th International Conference of Computer and Information Technology Iccit 2017 Vol. 2018-January (pp. 1-7). IEEE.
    DOI Scopus2
    2017 Biswas, C., Das Gupta, U., & Haque, M. (2017). A Hierarchical Key Derivative Symmetric Key Algorithm using Digital Logic. In Ecce 2017 International Conference on Electrical Computer and Communication Engineering (pp. 604-609). BANGLADESH, Coxs Bazar: IEEE.
    DOI Scopus4
    2017 Haque, M., Sheikh, J., & Rashid, J. A. (2017). An improved steganographic technique based on diamond encoding method. In Ecce 2017 International Conference on Electrical Computer and Communication Engineering (pp. 583-588). BANGLADESH, Coxs Bazar: IEEE.
    DOI Scopus2
    2016 Chowdhury, A., Tanzila, F. A., Chowdhury, S., & Haque, M. M. (2016). A secret key-based security architecture for wireless sensor networks. In 1st International Conference on Computer and Information Engineering Iccie 2015 (pp. 79-82). IEEE.
    DOI
    2016 Mokammel Haque, M., & Pieprzyk, J. (2016). Optimizing preprocessing method of recursive-BKZ lattice reduction algorithm. In 2nd International Conference on Electrical Information and Communication Technologies Eict 2015 (pp. 19-23). IEEE.
    DOI
    2016 Chowdhury, A., Tanzila, F. A., Chowdhury, S., & Haque, M. M. (2016). An efficient security architecture for Wireless Sensor Networks using pseudo-inverse matrix. In 2015 18th International Conference on Computer and Information Technology Iccit 2015 (pp. 396-400). IEEE.
    DOI Scopus5
    2015 Haque, M. M., & Pieprzyk, J. (2015). Evaluating the performance of the practical lattice reduction algorithms. In 8th International Conference on Electrical and Computer Engineering Advancing Technology for A Better Tomorrow Icece 2014 (pp. 341-344). IEEE.
    DOI
    2014 Haque, M. M., Pieprzyk, J., & Asaduzzaman. (2014). Predicting tours and probabilistic simulation for BKZ lattice reduction algorithm. In 2014 9th International Forum on Strategic Technology Ifost 2014 (pp. 1-4). BANGLADESH, Coxs Bazar: IEEE.
    DOI
    2008 Haque, M. M., Pathan, A. S. K., & Hong, C. S. (2008). Securing U-healthcare sensor networks using public key based scheme. In International Conference on Advanced Communication Technology Icact Vol. 2 (pp. 1108-1111). SOUTH KOREA, Phoenix Pk: IEEE.
    DOI Scopus30
    2007 Pathan, A. S. K., Ryu, J. H., Haque, M. M., & Hong, C. S. (2007). Security management in wireless sensor networks with a public key based scheme. In S. Ata, & C. S. Hong (Eds.), Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics Vol. 4773 LNCS (pp. 503-506). JAPAN, Sapporo: SPRINGER-VERLAG BERLIN.
    DOI Scopus1
    2007 Haque, M. M., Pathan, A. S. K., Choi, B. G., & Hong, C. S. (2007). An efficient PKC-based security architecture for wireless sensor networks. In Proceedings IEEE Military Communications Conference MILCOM (pp. 1-7). IEEE.
    DOI Scopus7
    2007 Haque, M. M., Pathan, A. -S. K., Choi, B. G., & Hong, C. S. (2007). An efficient PKC-based security architecture for wireless sensor networks. In 2007 IEEE MILITARY COMMUNICATIONS CONFERENCE, VOLS 1-8 (pp. 1722-1728). FL, Orlando: IEEE.

  • Preprint
    Year Citation
    2020 Sarker, S., & Haque, M. M. (2020). A Data Change Rule Based Empirical Framework for Labeling Unlabeled Time Series Driving Data.
    DOI
    2020 Sarker, S., & Haque, M. M. (2020). An approach towards data change rule based classification of driving maneuver with LSTM network.
    DOI

Semester 2, 2025

COMP SCI 1500 Cyber Security (Course Coordinator & Lecturer)

COMP SCI 1013 Introduction to Computer Systems, Network & Security (Course Coordinator and Lecturer)

Semester 1, 2025

COMP SCI 3308_7308 Advanced Cyber Security: Techniques & Concepts (Course Coordinator & Lecturer)

Trimester 1, 2025

COMP SCI 7308 Advanced Cyber Security: Techniques & Concepts (Course Coordinator & Lecturer)

COMP SCI 7328 Concepts in Cyber Security (Course Coordinator & Lecturer)

Trimester 3, 2024

COMP SCI 7101A, 7101B Cyber Security Research Project (Course Coordinator and Supervisor)

COMP SCI 7102A, 7102B Cyber Security Industry Project (Course Coordinator and Supervisor)

Semester 2, 2024

COMP SCI 1013 Introduction to Computer Systems, Network & Security (Lecturer and Course Coordinator)

COMP SCI 1500 Cyber Security (Lecturer and Course Coordinator)

COMP SCI 3307_7307 Secure Programming (Tutor)

Trimester 2, 2024

COMP SCI 7307 Secure Programming (Tutor)

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