Open Access
Research Article·pp. 1033–1044·Vol. 29, Issue 4Apr 2026
Gayathri Ananthakrishnan, Hayder M. A. Ghanimi, Kolluru Suresh Babu, Anilambica Kata, Gunaganti Sravanthi, Aseel Smerat, Sudhakar Sengan, Pankaj Dadheech
Published Online: 09 Apr 2026DOI: 10.47974/JIM-2573 In this paper: Conventional mathematical models and data-driven deep learning (DL) methods are both tested for Human Decision-Making (HDM) in Complex Sequential Tasks (CST). These methods include complicated cogniti...
Open Access
Research Article·pp. 1887–1898·Vol. 28, Issue 5-BAug 2025
Vishnu Priya Arivanantham, Hayder M. A. Ghanimi, Vijaya Krishna Sonthi, Firas Tayseer Ayasrah, Reena Mahapatra Lenka, P. Hemalatha, Sudhakar Sengan, Pankaj Dadheech
Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2365 In this paper: The software development model is changing fast, and the challenge of security remains the primary attention, particularly with the implementation of Development and Operations (DevOps), Distributed L...
Open Access
Research Article·pp. 1911–1922·Vol. 28, Issue 5-BAug 2025
N. Keerthana, Hayder M. A. Ghanimi, P. V. V. S. Srinivas, Naveen Reddy Pendli, Firas Tayseer Ayasrah, M. Anto Bennet, Sudhakar Sengan, Pankaj Dadheech
Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2367 In this paper: Suspicious activities in the cyber-crime world are increasing, so modern security measures of Cyber-Physical Systems (CPS) are required. This proposed model for Cybersecurity is known as the Predictiv...
Open Access
Research Article·pp. 1935–1944·Vol. 28, Issue 5-BAug 2025
K. R. Praneeth, Hayder M. A. Ghanimi, M. Srinivasa Narayana, Kafila, Sireesha Nanduri, Ravi Kumar Bommisetti, Sudhakar Sengan, Pankaj Dadheech
Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2369 In this paper: In the background of the contemporary Supply Chain (SC) environment, the motivation is on cyber security of Cyber-Physical Systems (CPS), openness, and optimization. This paper aims to develop a Secur...
Open Access
Research Article·pp. 2081–2092·Vol. 28, Issue 5-BAug 2025
Vishnu Priya Arivanantham, Hayder M. A. Ghanimi, Sagar Rane, V. Jasmine Sowmya, Kamal Poon, N. Mythili, Sudhakar Sengan, Pankaj Dadheech
Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2366 In this paper: Ensuring the confidentiality and integrity of healthcare records in Blockchain (BC)-based Medi-Cloud Systems (MCS) is vital, with a focus on Key Management Systems (KMS). This investigation presents a...
Open Access
Research Article·pp. 2103–2114·Vol. 28, Issue 5-BAug 2025
V. Ramachandran, Hayder M. A. Ghanimi, Bhaskar Marapelli, Navleen Kaur, M. Rajya Laxmi, Ravi Kumar Bommisetti, Sudhakar Sengan, Pankaj Dadheech
Published Online: 30 Aug 2025DOI: 10.47974/JDMSC-2368 In this paper: This paper introduces a Cyber-Physical System (CPS) that can be used to improve privacy protection in enterprise Blockchain (BC) systems, particularly in Hyperledger Fabric (HF). The proposed CPS empl...
Open Access
Research Article·pp. 2143–2154·Vol. 27, Issue 7Oct 2024
T. Gopalakrishnan, Hayder M. A. Ghanimi, Tanweer Alam, K. Sreekanth, K. E. Purushothaman, Sudhakar Sengan, Pankaj Dadheech
Published Online: 15 Oct 2024DOI: 10.47974/JDMSC-2087 In this paper: Counterfeit technology propagation and deepfake systems threaten authenticity, trust, and data integrity. This research article proposes a novel technique that leverages Blockchain Technology (BT) int...
Open Access
Research Article·pp. 2155–2167·Vol. 27, Issue 7Oct 2024
Gayathri Ananthakrishnan, Hayder M. A. Ghanimi, P. Pushpa, T. K. Rama Krishna Rao, M. Vedaraj, Sudhakar Sengan, Pankaj Dadheech
Published Online: 15 Oct 2024DOI: 10.47974/JDMSC-2088 In this paper: Secure data transmission is essential for securing sensitive data generated in huge volumes in today’s growing digital era. In today’s growing digital world, secure data transfer is essential for secu...
Open Access
Research Article·pp. 2219–2230·Vol. 27, Issue 7Oct 2024
Madan Mohan Tito Ayyalasomayajula, Hayder M. A. Ghanimi, M. Manimaran, Vijaya Krishna Sonthi, Abrar Ahmed Katiyan, Sudhakar Sengan, Pankaj Dadheech
Published Online: 15 Oct 2024DOI: 10.47974/JDMSC-2093 In this paper: The growing threat of cyberattacks has rendered the research of secure online systems an issue of concern. Elliptic Curve Cryptography (ECC) is an enhanced security benchmark that provides high-securi...
Open Access
Research Article·pp. 203–214·Vol. 27, Issue 2-AMar 2024
Hayder M. A. Ghanimi, T. Gopalakrishnan, G. Joel Sunny Deol, K. Amarendra, Pankaj Dadheech, Sudhakar Sengan
Published Online: 06 Apr 2024DOI: 10.47974/JDMSC-1880 In this paper: Integrating Deep Learning (DL) techniques in Convolutional Neural Networks (CNNs) with encrypted data analysis is an emerging field for enhancing data privacy and security. A significant challenge in...
Open Access
Research Article·pp. 237–248·Vol. 27, Issue 2-AMar 2024
Hayder M. A. Ghanimi, Romel P. Melgarejo-Bolivar, Alfredo Tumi-Figueroa, Samrat Ray, Pankaj Dadheech, Sudhakar Sengan
Published Online: 06 Apr 2024DOI: 10.47974/JDMSC-1878 In this paper: The integration of Blockchain (BC) technology with the Merkle-Damgård Structure (M-DS) presents a practical model for securing Electronic Health Records (EHR). This research study examines how these c...
Open Access
Research Article·pp. 249–259·Vol. 27, Issue 2-AMar 2024
P. Vidya Sagar, Hayder M. A. Ghanimi, L. Arokia Jesu Prabhu, L. Raja, Pankaj Dadheech, Sudhakar Sengan
Published Online: 06 Apr 2024DOI: 10.47974/JDMSC-1879 In this paper: Ensuring data privacy while applying Deep Learning (DL) on distributed datasets represents an essential task in the current period of critical data security. Data privacy and accuracy of models are ty...
Open Access
Research Article·pp. 361–370·Vol. 27, Issue 2-AMar 2024
Ganga Rama Koteswara Rao, Hayder M. A. Ghanimi, V. Ramachandran, Dokhyl Al-Qahtani, Pankaj Dadheech, Sudhakar Sengan
Published Online: 06 Apr 2024DOI: 10.47974/JDMSC-1891 In this paper: A significant novel approach in distributed ML, Federated Learning (FL), enables multiple parties to work simultaneously on developing models while securing the confidentiality of their unique dataset...
