S FAIZAL MUKTHAR HUSSAIN

@msec.org.in

ASSISTANT PROFESSOR-COMPUTER SCIENCE
mohamed sathak engineering college

S FAIZAL MUKTHAR HUSSAIN


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https://researchid.co/faizaldwyc

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Networks and Communications, Artificial Intelligence, Information Systems
15

Scopus Publications

57

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Enhanced Secure Transmission Using Cryptology in the Internet of Drones
    S. Faizal Mukthar Hussain, R. Karthikeyan, S. Ramamoorthi, V. Balaji, S. Syed Musthafa Gani, Majjari Sudhakar
    International Conference on Emerging Trends and Innovations in ICT Icei 2026, 2026
    Recent research heavily focuses on drones. Drones have been used for many applications including defense, healthcare, traffic control etc. IoT is also mixed with many fields thus it fits with drone as well. Drone become internet of drone as it is combined with internet of things area. When we use the internet of drones for communication in defense then security will be the major part to tackle. In this research we also represents about the difficulties occurred during applying and using the security algorithms. Also we picture the results of various algorithms with respect to security level and computational cost. Elliptic curve cryptography comparison with RSA is highlighted and suggests using ECC for secure communication between drones which are connected via internet of things in this paper. Vehicular Adhoc Network (VANET) is also taken into count for gathering security related information for achieving better security level in IoD secure communication. Future directions are represented towards handling enemy drones that carry the missile using optimization algorithm.
  • Enhanced LLM-Based Question Answering Tool for Effective Article Analysis
    S. Surendhar, R. Karthikeyan, S. Ramamoorthi, S. Faizal Mukthar Hussain, Majjari Sudhakar, V. Balaji
    International Conference on Emerging Trends and Innovations in ICT Icei 2026, 2026
    In today's digital landscape, where users are inundated with vast amounts of data, there is a growing need for systems that can distill precise and meaningful insights. This project presents the development of a sophisticated, inter- active question-answering (QA) platform that extracts relevant information from extensive textual datasets. Leveraging cutting edge advancements in natural language processing (NLP) and information retrieval, the system is capable of delivering contextaware and accurate responses derived directly from uploaded or indexed article content. At the heart of this framework are three core technologies: LangChain, Streamlit, and FAISS. LangChain enables flexible orchestration of language models to perform advanced text analysis and response generation. Streamlit offers a streamlined and accessible user interface, making it simple for individuals—regardless of technical expertise—to pose questions and receive instant responses. Meanwhile, FAISS (Facebook AI Similarity Search) plays a pivotal role in managing large-scale document retrieval by performing efficient similarity matching and indexing, thereby ensuring low-latency and high-accuracy results. The synergy between these components results in a responsive, scalable, and user-centric QA solution tailored for navigating and understanding complex document repositories.
  • Enhanced Medical Image Classification Using LSA and PCA in CNN
    Thasneem Suhaifa S, Faizal Mukthar Hussain S, Karthikeyan R, Sheik Yousuf T, Rasina Begum B, Mohammed Uveise S A
    E3s Web of Conferences, 2025
    We are presently living in the era where in medical field, the use of technology plays a major role in disease diagnosis and in treatment. In recent years Medical Image Processing play a significant role in modern diagnostics, where precision and accuracy are of highly important for planning and treatment of diseases. In this study, we present an enhanced approach that integrates Least Squares (LSA) alongside with Principal Component Analysis (PCA) within the Convolutional Neural Network (CNN) framework of deep learning to improve image processing and image resolution for medical diagnostics .Here LSA is employed to reduce the noise to the greater extent and to refine the feature for better clarity, while PCA employed in dimensionality reduction for efficient processing and preserving critical image details and at the same time CNN enables the automatic feature extraction and interpretation of image. Our results demonstrate that this combined LSA and PCA in CNN model offers significant improvement in image processing speed, efficiency in computation, reduction in noise present in the medical image, increasing sharpness of the image for high resolution leads to the accuracy in detection of diseases making it a promising method for advanced and enhanced medical imaging applications.
  • Advanced privacy protection (APP) machine learning model using cryptographic techniques for IoT
    K. Senthil, R. Karthikeyan, S. Shanmuga Priya, R. Monikaa, S. Ramamoorthi, S. Faizal Mukthar Hussain
    Discover Applied Sciences, 2025
    Because of the continuous computational and communication growth, the Internet of Things (IoT) plays a significant role in many real-time applications. Hence, huge amount of data are produced by the IoT devices, requires privacy preserving models for securing the data. For preserving the privacy of data, many machine learning models are developed, still, certain models lack in efficiency. For this, an Advanced Privacy Protection (APP) Machine Learning Model is proposed in this paper. The model uses cryptographic techniques for preserving the data privacy in efficient manner. Moreover, the model contains a Secure Data Provider (SDP) for processing the privacy protection-based training with the data on the nodes. The data privacy is ensured and the model factors can be acquired by SDP, where Support Vector Machine (SVM) is the training model employed. The results show that the model significantly increases the accuracy of training model and data privacy, minimizes the communication overhead, computational complexities.
  • Security Assurance of the IoT Environment by Applying Machine Learning: A Survey
    S. Faizal Mukthar Hussain, R. Karthikeyan, S. Ramamoorthi, V. Balamurugan, Prakash Kumar Sarangi
    Signals and Communication Technology, 2025
  • A Dynamically Revocable Three-Factor MAKA Protocol with Schnorr Signatures for Secure Multi-Server Environments
    S. Karthiyayini, S. Faizal Mukthar Hussain, S. P. Santhoshkumar, Kamalakannan Machap, S. Ramamoorthi, Mohammed Uveise S A
    2025 5th International Conference on Emerging Research in Electronics Computer Science and Technology Icerect 2025, 2025
    Many services are being implemented on cloud platforms at an increasing rate due to the quick development of cloud computing technology, which raises serious concerns about preserving network security while guaranteeing smooth service accessibility. The majority of Multi-Server Authentication Key Agreement (MAKA) protocols currently in use either have high computational and communication costs or lack formal security proofs, leaving them open to different types of attacks. Additionally, the static revocation mechanisms used by the three-factor MAKA protocols currently in use allow for possible abuse by hostile users. This paper suggests a dynamically revocable three-factor MAKA protocol that incorporates Schnorr signatures and offers a formal security proof in the random oracle model in order to get around these restrictions. Strong defense against security threats is ensured by the suggested scheme's support for dynamic user management. Performance analysis validates its effectiveness and suitability for resource-constrained smart devices, while security analysis shows its appropriateness for multi-server environments. A thorough security assessment and full implementation confirm the protocol's usefulness and efficacy.
  • Contrastive Learning for Improved Abstractive Sentence Summarization
    Ulligaddala Srinivasarao, Karthikeyan R, Mohamed Sithik M, Faizal Mukthar Hussain S, Mohammed Uveise S A, Hariharan Shanmugasundaram
    International Conference on Advanced Computing Technologies Icoact 2025, 2025
    Text summarizing aims to overview the material while maintaining essential details concisely. Lately, summary tasks have been included in the contrastive learning process in addition to visual representation. To optimize their similarities, contrastive learning summarizing algorithms currently concentrate on modelling and semantic similarity in all documents, targets, and data summaries. They do not, however, consider the impact that sentence semantics have on the text. In this study, we propose an RNN technique to develop the model for detecting the salient information. The sentence salience is based on the semantic similarity between the summary sentences of the original content, taking into account the distance of the loss of contrast in the form of soft weights functions. Consequently, our proposed model minimizes the semantic similarity given the textual summaries and possible noise and maximizes the semantic words between summaries and relevant information. Three popular datasets—multi news, CNN/Daily Mail, and Booksum datasets achieved the highest accuracy of 0.69% in the news datasets. The experiment outcomes demonstrate that the suggested strategy can considerably raise baseline performance and outperform other contrastive learning techniques.
  • Intrusion Detection on Self Organizing Network using PCA and Random Forest
    Nivetha V, S. Faizal Mukthar Hussain, R. Karthikeyan, T. Sheik Yousuf, B. Rasina Begum, S. Ramamoorthi
    Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
    There are several hazards to internet security as a result of the development of network technology. One cannot stress how crucial intrusion detection systems (IDS) are to network and computer security. Addressing the challenge of class imbalance in intrusion detection data, this study explores the development of an efficient Intrusion Detection System (IDS). Using the KDDCUP'99 dataset, we propose an IDS based on the Random Forest classification algorithm enhanced with Principal Component Analysis (PCA). The system's performance was evaluated using accuracy, precision, recall, F-score, and Confusion Matrix analysis. The diverse precision levels inherent in different IDS methods underscore the need for a reliable and effective solution.
  • Federated Learning-Assisted Coati Deep Learning-Based Model for Intrusion Detection in MANET
    S. Faizal Mukthar Hussain, S. M. H. Sithi Shameem Fathima
    International Journal of Computational Intelligence Systems, 2024
    MANET is a set of self-arranged, wirelessly connected nodes. Each mobile ad hoc network node acts as a router to send the packet from the source node to the destination node. MANET nodes’ random movements and decentralized architecture pose security challenges, making them vulnerable to various attacks like node selfishness, network partition, black hole, and DoS due to limited hardware resources. In this paper, a novel Hybrid Intrusion DEtection for MANet (HIDE-MAN) technique has been proposed to detect intrusion like DDoS and MitM attacks in MANET. The proposed HIDE-MAN framework initiates by preprocessing malicious data packets through data cleaning and data transformation resulting in the creation of high-dimensional vectors. The intrusion detection system then makes use of the CO-BiLSTM model, which is based on the actions of Coati and BiLSTM. It categorizes outputs into DDoS attacks, MitM attacks, or the absence of any attacks. Federated learning with GAN networks allows for the aggregation of updates from multiple local models distributed across MANET. Assessment metrics such as accuracy, precision, F1 score, detection rate, recall, and security rate have been utilized to assess the efficacy of the proposed HIDE-MAN method. The comparative analysis shows that the detection rate of the proposed HIDE-MAN is greater by 18.9%, 18.07%, and 4.03% than that of the current KBIDS, WOA-DNN, and MSA-GCNN techniques, respectively.
  • Enhanced Model for Medical Image Data Security Using Machine Learning
    S. Karthiyayini, Jeniffer John Simon Christopher, I. Sheik Arafat, Faizal Mukthar Hussain Syed Moomin
    SN Computer Science, 2024
  • Demystifying Applications of Explainable Artificial Intelligence (XAI) in e-Commerce
    S. Faizal Mukthar Hussain, R. Karthikeyan, M. A. Jabbar
    Studies in Computational Intelligence, 2024
  • Security Enhanced Smart Hospital Management System achieved through SELSTM Technique
    S.Faizal Mukthar Hussain, R. Karthikeyan, S.Ramamoorthi, I.Sheik Arafat, N.Ahamed Hussain Asif
    2024 2nd International Conference on Artificial Intelligence Trends and Pattern Recognition Icaitpr 2024, 2024
  • AI Based Model for the Creation of Chatbots to Help in the Instructional Process
    Kachi Anvesh, Bharati Mahantayya Reshmi, R. Karthikeyan, S. Ramamoorthi, S.Faizal Mukthar Hussain
    2024 2nd International Conference on Computing and Data Analytics Iccda 2024 Proceedings, 2024
  • Denial of Service Attack Analysis Using Machine Learning Techniques
    S.Faizal Mukthar Hussain, R. Karthikeyan, S. Ramamoorthi, I.Sheik Arafat, S.Syed Musthafa Gani
    Proceedings of the 2nd International Conference on Edge Computing and Applications Icecaa 2023, 2023
  • Enhanced Protection for Information and Network using Intrusion Detection System
    S. Faizal Mukthar Hussain, R. Karthikeyan, S. Ramamoorthi, I. Sheik Arafat, S. Syed Musthafa Gani
    Proceedings of the 2nd International Conference on Edge Computing and Applications Icecaa 2023, 2023

RECENT SCHOLAR PUBLICATIONS

  • Enhanced LLM-Based Question Answering Tool for Effective Article Analysis
    S Surendhar, R Karthikeyan, S Ramamoorthi, SFM Hussain, M Sudhakar, ...
    2026 International Conference on Emerging Trends and Innovations in ICT … , 2026
    2026
  • Enhanced Secure Transmission Using Cryptology in the Internet of Drones
    SFM Hussain, R Karthikeyan, S Ramamoorthi, V Balaji, SSM Gani, ...
    2026 International Conference on Emerging Trends and Innovations in ICT … , 2026
    2026
  • A Dynamically Revocable Three-Factor MAKA Protocol with Schnorr Signatures for Secure Multi-Server Environments
    S Karthiyayini, SFM Hussain, SP Santhoshkumar, K Machap, ...
    2025 5th International Conference on Emerging Research in Electronics … , 2025
    2025
  • Intrusion Detection on Self Organizing Network using PCA and Random Forest
    V Nivetha, SFM Hussain, R Karthikeyan, TS Yousuf, BR Begum, ...
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
  • Impacts of Artificial Intelligence and the Internet of Things in Financial Management and Its Benefits in Agricultural Business
    SFM Hussain, R Karthikeyan, NAH Asif, B Sundaravadivazhagan, ...
    AI Integration for Business Sustainability: For a Resilient Future, 341-355 , 2025
    2025
  • Contrastive Learning for Improved Abstractive Sentence Summarization
    U Srinivasarao, R Karthikeyan, M Sithik, MU SA, H Shanmugasundaram
    2025 International Conference on Advanced Computing Technologies (ICoACT), 1-6 , 2025
    2025
  • Advanced privacy protection (APP) machine learning model using cryptographic techniques for IoT
    K Senthil, R Karthikeyan, SS Priya, R Monikaa, S Ramamoorthi, ...
    Discover Applied Sciences 7 (3), 213 , 2025
    2025
    Citations: 18
  • Enhanced Medical Image Classification Using LSA and PCA in CNN
    T Suhaifa S, F Mukthar Hussain S, K R, S Yousuf T, R Begum B, ...
    E3S Web of Conferences 619, 02013 , 2025
    2025
  • Security Enhanced Smart Hospital Management System achieved through SELSTM Technique
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, NAH Asif
    2024 2nd International Conference on Artificial Intelligence Trends and … , 2024
    2024
    Citations: 1
  • Enhanced Model for Medical Image Data Security Using Machine Learning
    S Karthiyayini, J John Simon Christopher, I Sheik Arafat, FM Hussain
    SN Computer Science 5 (8), 1-16 , 2024
    2024
    Citations: 7
  • Federated learning-assisted coati deep learning-based model for intrusion detection in MANET
    SFM Hussain, SMHSS Fathima
    International Journal of Computational Intelligence Systems 17 (1), 285 , 2024
    2024
    Citations: 8
  • AI Based Model for the Creation of Chatbots to Help in the Instructional Process
    K Anvesh, BM Reshmi, R Karthikeyan, S Ramamoorthi, SFM Hussain
    2024 2nd International Conference on Computing and Data Analytics (ICCDA), 1-6 , 2024
    2024
  • Demystifying applications of explainable artificial intelligence (XAI) in e-commerce
    SFM Hussain, R Karthikeyan, MA Jabbar
    Role of Explainable Artificial Intelligence in E-Commerce, 101-116 , 2024
    2024
    Citations: 2
  • Gain-Scheduling and Fuzzy Techniques with Fault Isolation and Detection are used to Control Distribution Voltage in DC Microgrids
    SSMGSAMU N.Ahamed Hussain Asif, S. Faizal Mukthar Hussain
    Solovyov Studies ISPU 72 (2), 93-98 , 2024
    2024
  • Security Assurance of the IoT Environment by Applying Machine Learning: A Survey
    SFM Hussain, R Karthikeyan, S Ramamoorthi, V Balamurugan, ...
    International Conference on Innovation, Sustainability, and Applied Sciences … , 2023
    2023
  • Denial of service attack analysis using machine learning techniques
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, SSM Gani
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023
    Citations: 10
  • Enhanced protection for information and network using intrusion detection system
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, SSM Gani
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023
    Citations: 11
  • Enhanced Secure Internet of Drones For Defense Using Cryptography
    A Kumar, N Iniyanayagam
    Dept of Computer Science Engineering, Mohamed Sathak Engineering College , 2023
    2023
  • Drone Based Cyber-Physical System for Water Quality Monitoring in Rural Areas
    S Faizal Mukthar Hussain
    IN Patent 202,331,020,780 , 2023
    2023
  • A Smart Agriculture Monitoring System Based on Web of Things Finance Future Patterns in the Market Using Artificial Intelligence
    Dr. M.VIJAYARAJ, M.MOHAMED SITHIK, Mr. S.A.MOHAMMED UVEISE, S.RAMAMOORTHI ...
    IN Patent 202,241,046,585 , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Advanced privacy protection (APP) machine learning model using cryptographic techniques for IoT
    K Senthil, R Karthikeyan, SS Priya, R Monikaa, S Ramamoorthi, ...
    Discover Applied Sciences 7 (3), 213 , 2025
    2025
    Citations: 18
  • Enhanced protection for information and network using intrusion detection system
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, SSM Gani
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023
    Citations: 11
  • Denial of service attack analysis using machine learning techniques
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, SSM Gani
    2023 2nd International Conference on Edge Computing and Applications (ICECAA … , 2023
    2023
    Citations: 10
  • Federated learning-assisted coati deep learning-based model for intrusion detection in MANET
    SFM Hussain, SMHSS Fathima
    International Journal of Computational Intelligence Systems 17 (1), 285 , 2024
    2024
    Citations: 8
  • Enhanced Model for Medical Image Data Security Using Machine Learning
    S Karthiyayini, J John Simon Christopher, I Sheik Arafat, FM Hussain
    SN Computer Science 5 (8), 1-16 , 2024
    2024
    Citations: 7
  • Demystifying applications of explainable artificial intelligence (XAI) in e-commerce
    SFM Hussain, R Karthikeyan, MA Jabbar
    Role of Explainable Artificial Intelligence in E-Commerce, 101-116 , 2024
    2024
    Citations: 2
  • Security Enhanced Smart Hospital Management System achieved through SELSTM Technique
    SFM Hussain, R Karthikeyan, S Ramamoorthi, IS Arafat, NAH Asif
    2024 2nd International Conference on Artificial Intelligence Trends and … , 2024
    2024
    Citations: 1
  • Enhanced LLM-Based Question Answering Tool for Effective Article Analysis
    S Surendhar, R Karthikeyan, S Ramamoorthi, SFM Hussain, M Sudhakar, ...
    2026 International Conference on Emerging Trends and Innovations in ICT … , 2026
    2026
  • Enhanced Secure Transmission Using Cryptology in the Internet of Drones
    SFM Hussain, R Karthikeyan, S Ramamoorthi, V Balaji, SSM Gani, ...
    2026 International Conference on Emerging Trends and Innovations in ICT … , 2026
    2026
  • A Dynamically Revocable Three-Factor MAKA Protocol with Schnorr Signatures for Secure Multi-Server Environments
    S Karthiyayini, SFM Hussain, SP Santhoshkumar, K Machap, ...
    2025 5th International Conference on Emerging Research in Electronics … , 2025
    2025
  • Intrusion Detection on Self Organizing Network using PCA and Random Forest
    V Nivetha, SFM Hussain, R Karthikeyan, TS Yousuf, BR Begum, ...
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
  • Impacts of Artificial Intelligence and the Internet of Things in Financial Management and Its Benefits in Agricultural Business
    SFM Hussain, R Karthikeyan, NAH Asif, B Sundaravadivazhagan, ...
    AI Integration for Business Sustainability: For a Resilient Future, 341-355 , 2025
    2025
  • Contrastive Learning for Improved Abstractive Sentence Summarization
    U Srinivasarao, R Karthikeyan, M Sithik, MU SA, H Shanmugasundaram
    2025 International Conference on Advanced Computing Technologies (ICoACT), 1-6 , 2025
    2025
  • Enhanced Medical Image Classification Using LSA and PCA in CNN
    T Suhaifa S, F Mukthar Hussain S, K R, S Yousuf T, R Begum B, ...
    E3S Web of Conferences 619, 02013 , 2025
    2025
  • AI Based Model for the Creation of Chatbots to Help in the Instructional Process
    K Anvesh, BM Reshmi, R Karthikeyan, S Ramamoorthi, SFM Hussain
    2024 2nd International Conference on Computing and Data Analytics (ICCDA), 1-6 , 2024
    2024
  • Gain-Scheduling and Fuzzy Techniques with Fault Isolation and Detection are used to Control Distribution Voltage in DC Microgrids
    SSMGSAMU N.Ahamed Hussain Asif, S. Faizal Mukthar Hussain
    Solovyov Studies ISPU 72 (2), 93-98 , 2024
    2024
  • Security Assurance of the IoT Environment by Applying Machine Learning: A Survey
    SFM Hussain, R Karthikeyan, S Ramamoorthi, V Balamurugan, ...
    International Conference on Innovation, Sustainability, and Applied Sciences … , 2023
    2023
  • Enhanced Secure Internet of Drones For Defense Using Cryptography
    A Kumar, N Iniyanayagam
    Dept of Computer Science Engineering, Mohamed Sathak Engineering College , 2023
    2023
  • Drone Based Cyber-Physical System for Water Quality Monitoring in Rural Areas
    S Faizal Mukthar Hussain
    IN Patent 202,331,020,780 , 2023
    2023
  • A Smart Agriculture Monitoring System Based on Web of Things Finance Future Patterns in the Market Using Artificial Intelligence
    Dr. M.VIJAYARAJ, M.MOHAMED SITHIK, Mr. S.A.MOHAMMED UVEISE, S.RAMAMOORTHI ...
    IN Patent 202,241,046,585 , 2022
    2022