Dr. MOHD SHAHID HUSAIN

@cas.edu.om

Assistant Professor IT Department
College of Applied Sciences, University of Technology & Applied Sciences, Oman

Dr. MOHD SHAHID HUSAIN


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https://researchid.co/mshusain
Dr. Mohd. Shahid Husain is a Research professional and Faculty member with 14 years of teaching & research experience. He is currently working as Assistant Professor in College of Applied Sciences, UTAS, Oman.
His area of interest includes Artificial Intelligence, Information Retrieval, Data Mining, Web mining, Sentiment Analysis and Computer Networks & Security.
He has published 4 books, 10 book chapters & more than 30 research papers in Journals/conferences of international repute. He was involved with many sponsored projects as PI/Co-PI. Currently he is involved in ongoing project sponsored by CAS, MoHE. He is also contributing his knowledge and experience as member of Editorial Board/Advisory committee and TPC in various international Journals/Conferences of repute. He is active member of different professional bodies including ACM, IEEE young professionals, IEEE-TCII, ISTE, CSTA, IACSIT.

EDUCATION

PhD (Computer Science & Engineering)
M. Tech. (Information Technology)
B. Tech. (Information Technology)

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence
36

Scopus Publications

1107

Scholar Citations

16

Scholar h-index

32

Scholar i10-index

Scopus Publications

  • Fake News Detection System for Textual Data Using Sequential Deep Learning Model
    Mohd Shahid Husain, Umar Sathic, Nawazish Naveed, Hemalatha Gunasekaran
    International Conference on Artificial Intelligence Computer Data Sciences and Applications Acdsa 2026, 2026
  • LWLCM: A novel lightweight stream cipher using logistic chaos function and multiplexer for IoT communications
    Shahnwaz Afzal, Mohammad Ubaidullah Bokhari, Mahfooz Alam, Mohd Shahid Husain, Mohammad Zunnun Khan, et al.
    Plos One, 2025
    The Internet of Things (IoT) includes vehicles, homes, and integrated sensors and many interconnected physical devices that gather and share data to interact with their environment. Data moving across multiple levels is vulnerable to various security threats, including leaks and unauthorized access. IoT faces significant challenges in balancing strict security with optimal performance metrics such as energy efficiency, throughput, and memory. We present a novel lightweight stream cipher designed to secure IoT communication and address these challenges. The proposed architecture features four main components: a logistic round module that produces 32-bit chaotic outputs; two 80-bit shift registers, LFSR and NLFSR, for key expansion; and multiplexer units to enhance confusion and diffusion. This model improves the randomness and robustness of the keystream, strengthening the cipher against cryptanalytic attacks. An ablation research is performed by methodically eliminating the chaotic map, NLFSR, and multiplexer components to assess their individual effects on encryption/decryption duration, throughput, entropy, and avalanche analysis. Experimental results demonstrate that each component significantly improves the cipher’s overall performance and security, hence confirming the architecture’s design and also demonstrate that the proposed cipher exceeds the performance of current algorithms, including Grain-128 and RSA-1024, in terms of encryption/decryption time, throughput, and energy efficiency, while maintaining comparable statistical randomness to AES and Trivium. This method achieves an average Shannon entropy of 7.9996, and successfully passing all 15 NIST statistical randomness tests. A subsequent study analyzing the avalanche effect and correlation coefficients reinforces the strength of the encryption. The proposed encryption method, designed for resource-constrained environments, provides efficient and robust cryptographic security to protect IoT data effectively.
  • Enhanced Viral Genome Classification Using Large Language Models
    Hemalatha Gunasekaran, Nesaian Reginal Wilfred Blessing, Umar Sathic, Mohammad Shahid Husain
    Algorithms, 2025
    The classification of genomic sequences is a crucial area of research in the field of virology. This is due to the increasing number of outbreaks we have faced in recent times. We have a vast repository of genomic sequences from various species, including humans, animals, plants, bacteria, and viruses, which tend to mutate and form new variants or strains. In the realm of machine learning, several models are employed for genome sequence classification. Among these are traditional algorithms such as Random Forest (RF), K-nearest neighbors (KNNs), Decision Tree (DT), and Naive Bayes (NB), each offering unique advantages in handling genetic data. Additionally, deep learning models like Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Bi-Directional LSTM networks are utilized for their robust capabilities in capturing complex patterns and dependencies within genomic sequences. In this study, we explored the application of Natural Language Processing (NLP) techniques to classify the genomic sequences. The focus of our research involves utilizing advanced large language models (LLMs) such as DNABERT, DNAGPT, and GENA LM, which are fine-tuned explicitly on the language of DNA. In this research, after a detailed analysis, we found that DNAGPT achieved an accuracy of 96%, which exceeds the performance of state-of-the-art machine learning and deep learning models.
  • Exploring the cybersecurity landscape through cyber forensics
    Mohd Shahid Husain
    Exploring the Cybersecurity Landscape Through Cyber Forensics, 2025
  • Intelligent Management of Resources for Smart Edge Computing in 5G Heterogeneous Networks Using Blockchain and Deep Learning
    Mohammad Tabrez Quasim, Khair Ul Nisa, Mohammad Shahid Husain, Abakar Ibraheem Abdalla Aadam, Mohammed Waseequ Sheraz, et al.
    Computers Materials and Continua, 2025
    .
  • Cyberology: An Optimized Approach to the Cyber-World
    Mohd. Shahid Husain, Mohammad Faisal, Halima Sadia, Tasneem Ahmed, Saurabh Shukla, et al.
    Cyberology an Optimized Approach to the Cyber World, 2025
  • A Deep Learning-based Approach to Predict the Flood Patterns Using Sentinel-1A Time Series Images
    Mohammed Siddique, Tasneem Ahmed, Mohammad Shahid Husain
    Journal of the Indian Society of Remote Sensing, 2024
  • Enhanced mechanism to prioritize the cloud data privacy factors using AHP and TOPSIS: a hybrid approach
    Mohammad Zunnun Khan, Mohd Shoaib, Mohd Shahid Husain, Khair Ul Nisa, Mohammad. Tabrez Quasim
    Journal of Cloud Computing, 2024
    Cloud computing is a new paradigm in this new cyber era. Nowadays, most organizations are showing more reliability in this environment. The increasing reliability of the Cloud also makes it vulnerable. As vulnerability increases, there will be a greater need for privacy in terms of data, and utilizing secure services is highly recommended. So, data on the Cloud must have some privacy mechanisms to ensure personal and organizational privacy. So, for this, we must have an authentic way to increase the trust and reliability of the organization and individuals The authors have tried to create a way to rank things that uses the Analytical Hieratical Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). Based on the result and comparison, produce some hidden advantages named cost, benefit, risk and opportunity-based outcomes of the result.In this paper, we are developing a cloud data privacy model; for this, we have done an intensive literature review by including Privacy factors such as Access Control, Authentication, Authorization, Trustworthiness, Confidentiality, Integrity, and Availability. Based on that review, we have chosen a few parameters that affect cloud data privacy in all the phases of the data life cycle. Most of the already available methods must be revised per the industry’s current trends. Here, we will use Analytical Hieratical Process and Technique for Order Preference by Similarity to the Ideal Solution method to prove that our claim is better than other cloud data privacy models. In this paper, the author has selected the weights of the individual cloud data privacy criteria and further calculated the rank of individual data privacy criteria using the AHP method and subsequently utilized the final weights as input of the TOPSIS method to rank the cloud data privacy criteria.
  • Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
    Saurabh Shukla, Shahid Hussain, Reyazur Rashid Irshad, Ahmed Abdu Alattab, Subhasis Thakur, et al.
    Computer Standards and Interfaces, 2024
  • A service-categorized security scheme with physical unclonable functions for internet of vehicles
    Nadhir Ben Halima, Ala Saleh Alluhaidan, Mohammad Zunnun Khan, Mohd Shahid Husain, Mohammad Ayoub Khan
    Journal of Big Data, 2023
    In smart cities, communication and information exchange for the Internet of Vehicles rely on open and closed infrastructures along the roadside. Secure communications rely on the sender and receiver devices having self-sustaining authentication methods. The perquisites of the authentication methods are to grip communication without being falsified by an adversary or unidentified third parties. This article introduces the Service-Categorized Security Scheme (SCSS) with a physically unclonable function (PUF) for handling sensitive guidance/communication information. The vehicle-side authentication, access control, and service demands are governed using service-based PUF factors such as digital signatures, passwords, etc. To prevent anonymous third parties and adversaries, the PUF operates over compromised and uncompromised communication devices. Device-specific keys generated by PUFs based on intrinsic physical variances help identify between compromised and uncompromised devices, while keys generated by uncompromised devices conform to their expected profiles In the service-sharing process, mutual authentication using synchronized keys is used for security and service verification. The synchronized keys are integrated with the PUF for monitoring de-synchronization and individual operation. This decision is made using federated learning from the external service provider and the communicator of the vehicle. Through the learning process, a de-synchronization occurrence at the service provider and vehicle is identified as the reason for disconnecting the session. As a result, any suspicious activity that contradicts service security is identified, and the information of the communicating vehicle is secured. The proposed scheme is analyzed using the metrics authentication time, adversary detection ratio, complexity, de-synchronization time, and successful sessions.
  • An internet of things enabled machine learning model for Energy Theft Prevention System (ETPS) in Smart Cities
    Mohammad Tabrez Quasim, Khair ul Nisa, Mohammad Zunnun Khan, Mohammad Shahid Husain, Shadab Alam, et al.
    Journal of Cloud Computing, 2023
  • Flood Monitoring and Early Warning Systems – An IoT Based Perspective
    Dr Tasneem Ahmed, Mohammed Siddique, Mohammad Shahid Husain
    Eai Endorsed Transactions on Internet of Things, 2023
  • A critical analysis of cyber threats and their global impact
    Syed Adnan Afaq, Mohd. Shahid Husain, Almustapha Bello, Halima Sadia
    Computational Intelligent Security in Wireless Communications, 2023
  • The Rise of Deepfake Technology: Issues, Challenges, and Countermeasures
    Mohd Akbar, Mohd Suaib, Mohd Shahid Hussain
    Advances in Cyberology and the Advent of the Next Gen Information Revolution, 2023
  • Big Data Concepts, Technologies and Applications
    Mohammad Shahid Husain, Mohammad Zunnun Khan, Tamanna Siddiqui
    Big Data Concepts Technologies and Applications, 2023
  • An Integrated Image Classification Approach to Detect the Flood Prone Areas using Sentinel-1 Images
    Proceedings of the 17th Indiacom 2023 10th International Conference on Computing for Sustainable Global Development Indiacom 2023, 2023
  • Advances in Cyberology and the Advent of the Next-Gen Information Revolution
    Advances in Cyberology and the Advent of the Next Gen Information Revolution, 2023
  • Preface
    Advances in Cyberology and the Advent of the Next Gen Information Revolution, 2023
  • An Empirical Approach to Monitor the Flood-Prone Regions of North India Using Sentinel-1 Images
    Mohammed Siddique, Tasneem Ahmed, Mohd Shahid Husain
    Annals of Emerging Technologies in Computing, 2022
  • Random Forest Based Flood Monitoring Using Sentinel-1 Images: A Case Study of Flood Prone Regions of North-East India
    Mohammed Siddique, Tasneem Ahmed, Mohd Shahid Husain
    International Geoscience and Remote Sensing Symposium IGARSS, 2022
  • Security in Digital Healthcare System
    Manish Madhava Tripathi, Mohammad Haroon, Zunnun Khan, Mohammad Shahid Husain
    Eai Springer Innovations in Communication and Computing, 2022
  • Preface
    Eai Springer Innovations in Communication and Computing, 2022
  • Exploiting Artificial Immune System to Optimize Association Rules for Word Sense Disambiguation
    Mohd Shahid Husain
    International Journal of Intelligent Systems and Applications in Engineering, 2021
  • Cloud Computing in E-Governance: Indian Perspective
    Mohd. Shahid Husain, M. Akheela Khanum
    Research Anthology on Architectures Frameworks and Integration Strategies for Distributed and Cloud Computing, 2021
  • Breast cancer diagnosis using wrapper-based feature selection and artificial neural network
    Applied Computer Science, 2021

RECENT SCHOLAR PUBLICATIONS

  • Fake News Detection System for Textual Data Using Sequential Deep Learning Model
    MS Husain, U Sathic, N Naveed, H Gunasekaran
    2026 International Conference on Artificial Intelligence, Computer, Data … , 2026
    2026
  • VertiDaX: an explainable hybrid deep learning model for dropout prediction with vertical integration
    M Waseem, S Abidin, M Alam, MS Husain, MZ Khan, Z Ashraf
    PeerJ Computer Science 12, e3718 , 2026
    2026
  • LWLCM: A novel lightweight stream cipher using logistic chaos function and multiplexer for IoT communications
    S Afzal, MU Bokhari, M Alam, MS Husain, MZ Khan, Z Ashraf
    Plos one 20 (9), e0330976 , 2025
    2025
    Citations: 7
  • Intelligent Management of Resources for Smart Edge Computing in 5G Heterogeneous Networks Using Blockchain and Deep Learning.
    MT Quasim, KU Nisa, MS Husain, AIA Aadam, MW Sheraz, MZ Khan
    Computers, Materials & Continua 84 (1) , 2025
    2025
  • Enhanced viral genome classification using large language models
    H Gunasekaran, NR Wilfred Blessing, U Sathic, MS Husain
    Algorithms 18 (6), 302 , 2025
    2025
    Citations: 3
  • Cyberology An Optimized Approach to the Cyber-World
    MS Husain, M Faisal, H Sadia, T Ahmed, S Shukla, A Kaleem
    2025
    Citations: 6
  • Exploring the Cybersecurity Landscape Through Cyber Forensics
    MS Husain
    2025
    Citations: 1
  • FAULT TOLERANCE PREDICTION IN DISTRIBUTED SYSTEMS USING GRU, TCN AND LSTM
    F Ahmad, M Haroon, ZA Siddiqui, M Husain
    Malaysian Journal of Computer Science 38 (4), 287-309 , 2025
    2025
  • A deep learning-based approach to predict the flood patterns using Sentinel-1A time series images
    M Siddique, T Ahmed, MS Husain
    Journal of the Indian Society of Remote Sensing 52 (12), 2753-2767 , 2024
    2024
    Citations: 4
  • Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
    S Shukla, S Hussain, RR Irshad, AA Alattab, S Thakur, JG Breslin, ...
    Computer Standards & Interfaces 88, 103799 , 2024
    2024
    Citations: 34
  • Enhanced mechanism to prioritize the cloud data privacy factors using AHP and TOPSIS: a hybrid approach
    MZ Khan, M Shoaib, MS Husain, KU Nisa, MT Quasim
    Journal of Cloud Computing 13 ((42)) , 2024
    2024
    Citations: 18
  • A service-categorized security scheme with physical unclonable functions for internet of vehicles
    NB Halima, AS Alluhaidan, MZ Khan, MS Husain, MA Khan
    Journal of Big Data 10 (1), 1-23 , 2023
    2023
    Citations: 11
  • An internet of things enabled machine learning model for Energy Theft Prevention System (ETPS) in Smart Cities
    MS Husain, MZ Khan, MT Quasim, K Nisa, S Alam, M Shuaib, M Meraj, ...
    Journal of Cloud Computing 12 , 2023
    2023
    Citations: 22
  • Big Data Concepts, Technologies, and Applications
    MS Husain, MZ Khan, T Siddiqui
    CRC, Taylor & Francis group , 2023
    2023
    Citations: 16
  • Advances in Cyberology and the Advent of the Next-Gen Information Revolution
    MS Husain, M Faisal, H Sadia, T Ahmad, S Shukla
    IGI Global. , 2023
    2023
    Citations: 87
  • Flood Monitoring and Early Warning Systems--An IoT Based Perspective.
    M Siddique, T Ahmed, MS Husain
    EAI endorsed transactions on internet of things 9 (2) , 2023
    2023
    Citations: 36
  • The rise of deepfake technology: issues, challenges, and countermeasures
    M Akbar, M Suaib, MS Hussain
    Advances in Cyberology and the Advent of the Next-Gen Information Revolution … , 2023
    2023
    Citations: 9
  • A Critical Analysis of Cyber Threats and Their Global Impact
    H Afaq, S. A., Husain, M. S., Bello, A., & Sadia
    Computational Intelligent Security in Wireless Communications, 201-220 , 2023
    2023
    Citations: 32
  • An Integrated Image Classification Approach to Detect the Flood Prone Areas using Sentinel-1 Images
    M Siddique, T Ahmed, MS Husain
    2023 10th International Conference on Computing for Sustainable Global … , 2023
    2023
    Citations: 3
  • An Empirical Approach to Monitor the Flood-Prone Regions of North India Using Sentinel-1 Images
    M Siddique, T Ahmed, MS Husain
    Annals of Emerging Technologies in Computing (AETiC) 6 (4), 1-14 , 2022
    2022
    Citations: 9

MOST CITED SCHOLAR PUBLICATIONS

  • Methodological study of opinion mining and sentiment analysis techniques
    PK Singh, MS Husain
    International Journal on Soft Computing 5 (1), 11 , 2014
    2014
    Citations: 146
  • Critical Concepts, Standards, and Techniques in Cyber Forensics
    MS Husain, MZ Khan
    IGI Global , 2019
    2019
    Citations: 113
  • Advances in Cyberology and the Advent of the Next-Gen Information Revolution
    MS Husain, M Faisal, H Sadia, T Ahmad, S Shukla
    IGI Global. , 2023
    2023
    Citations: 87
  • Pervasive Healthcare: A Compendium of Critical Factors for Success
    MS Husain, MHBM Adnan, MZ Khan, S Shukla, FU Khan
    Springer International Publishing AG , 2022
    2022
    Citations: 77
  • An Unsupervised Approach to Develop a Stemmer
    MS Husain
    International Journal on Natural Language Computing (IJNLC) 1 (2), 15-23 , 2012
    2012
    Citations: 37
  • Flood Monitoring and Early Warning Systems--An IoT Based Perspective.
    M Siddique, T Ahmed, MS Husain
    EAI endorsed transactions on internet of things 9 (2) , 2023
    2023
    Citations: 36
  • Network analysis in a peer-to-peer energy trading model using blockchain and machine learning
    S Shukla, S Hussain, RR Irshad, AA Alattab, S Thakur, JG Breslin, ...
    Computer Standards & Interfaces 88, 103799 , 2024
    2024
    Citations: 34
  • Application of artificial intelligence in fighting against cyber crimes: a review
    MZ Siddiqui, S Yadav, MS Husain
    International Journal of Advanced Research in Computer Science 9 (2), 118-121 , 2018
    2018
    Citations: 33
  • A Critical Analysis of Cyber Threats and Their Global Impact
    H Afaq, S. A., Husain, M. S., Bello, A., & Sadia
    Computational Intelligent Security in Wireless Communications, 201-220 , 2023
    2023
    Citations: 32
  • Analysis of mental state of users using social media to predict depression: A survey
    A Khan, MS Husain, A Khan
    International Journal of Advanced Research in Computer Science 9 (2), 100-106 , 2018
    2018
    Citations: 30
  • Different technique of load balancing in distributed system: A review paper
    HM M Shahid Husain, Khan Riyaz
    Global Conference on Communication Technologies (GCCT), 2015, 371-375 , 2015
    2015
    Citations: 30
  • A Compendium Over Cloud Computing Cryptographic Algorithms and Security Issues
    Neha Mishra, M Shahid Husain, Jitesh P Tripathi
    BIJIT - BVICAM’s International Journal of Information Technology 7 (1), 810-814 , 2015
    2015
    Citations: 28
  • An internet of things enabled machine learning model for Energy Theft Prevention System (ETPS) in Smart Cities
    MS Husain, MZ Khan, MT Quasim, K Nisa, S Alam, M Shuaib, M Meraj, ...
    Journal of Cloud Computing 12 , 2023
    2023
    Citations: 22
  • Enhanced mechanism to prioritize the cloud data privacy factors using AHP and TOPSIS: a hybrid approach
    MZ Khan, M Shoaib, MS Husain, KU Nisa, MT Quasim
    Journal of Cloud Computing 13 ((42)) , 2024
    2024
    Citations: 18
  • Security in Digital Healthcare System
    MM Tripathi, M Haroon, Z Khan, MS Husain
    Pervasive Healthcare: A Compendium of Critical Factors for Success, 217-231 , 2022
    2022
    Citations: 17
  • Big Data Classification using Evolutionary Techniques: A Survey
    N Khan, M S Husain, M R Beg
    IEEE International Conference on Engineering and Technology (ICETECH), 243-247 , 2015
    2015
    Citations: 17
  • Big Data Concepts, Technologies, and Applications
    MS Husain, MZ Khan, T Siddiqui
    CRC, Taylor & Francis group , 2023
    2023
    Citations: 16
  • A Social Media Analytics Framework to Increase Prospective Students’ Interests in STEM and TVET Education
    MHM Adnan, SA Ariffin, HF Hanafi, MS Husain, IY Panessai
    Asian Journal of University Education 16 (4), 82-90 , 2021
    2021
    Citations: 15
  • Analytical study of feature extraction techniques in opinion mining
    PK Singh, MS Husain
    Computer Science 85 , 2013
    2013
    Citations: 15
  • A language Independent Approach to develop Urdu stemmer
    MS Husain, F Ahamad, S Khalid
    Advances in Computing and Information Technology: Proceedings of the Second … , 2013
    2013
    Citations: 15