Sunil Kumar Muttoo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Sunil Kumar Muttoo has a total of 18 co-authors. Here are the top co-authors by number of shared publications:
- Vinita Verma
University of Delhi
4 shared publications - V. B. Singh
Jawaharlal Nehru University
3 shared publications - Daniel Arockiam
School of Engineering and IT, Manipal Academy of Higher Education, Dubai, UAE
2 shared publications - Nisha
University of Delhi
2 shared publications - Pulkit Ohri
Amity University, Gwalior, India
2 shared publications - Rajan Gupta
Artificial Intelligence & Innovation (AI&I) Lab, Tamaulipas Autonomous University (UAT), Mexico
2 shared publications
Latest Publications
- 17 April 2025
- Published by Springer Nature in International Journal of System Assurance Engineering and Management
- Vol. 16 (5) , 1933-1944
An improved differential privacy-preserving technique for educational dataset
- 17 April 2025
- Published by Springer Nature in International Journal of System Assurance Engineering and Management
- Vol. 16 (5) , 1933-1944
An improved differential privacy-preserving technique for educational dataset
- 17 June 2024
- Published by Springer Nature in International Journal of Information Technology
- Vol. 17 (9) , 5591-5603
Blockchain-based security framework for mitigating network attacks in multi-SDN controller environment
- 17 June 2024
- Published by Springer Nature in International Journal of Information Technology
- Vol. 17 (9) , 5591-5603
Blockchain-based security framework for mitigating network attacks in multi-SDN controller environment
- 23 September 2023
- Published by Springer Nature
- p. 15-26
Removing Stegomalware from Digital Image Files
- 17 August 2023
- Published by Springer Nature in International Journal of System Assurance Engineering and Management
- Vol. 15 (5) , 1756-1776
Sentiment analysis and topic modeling of COVID-19 tweets of India
- 17 August 2023
- Published by Springer Nature in International Journal of System Assurance Engineering and Management
- Vol. 15 (5) , 1756-1776
Sentiment analysis and topic modeling of COVID-19 tweets of India
- 19 June 2023
- Published by Springer Nature in International Journal of Information Technology
- Vol. 15 (6) , 3307-3325
A novel privacy-preserving technique using steganography and L-diversity for multi-relational educational dataset
- 19 June 2023
- Published by Springer Nature in International Journal of Information Technology
- Vol. 15 (6) , 3307-3325
A novel privacy-preserving technique using steganography and L-diversity for multi-relational educational dataset
- 8 April 2022
- Published by Springer Nature
- p. 103-116
Detecting Stegomalware: Malicious Image Steganography and Its Intrusion in Windows
- 8 April 2022
- Published by Springer Nature
- p. 103-116
Detecting Stegomalware: Malicious Image Steganography and Its Intrusion in Windows
- 1 January 2022
- Published by Inderscience Publishers in International Journal of Information and Computer Security
- Vol. 18 (3/4) , 327-347
GENDroid - a graph-based ensemble classifier for detecting Android malware
Recent years have witnessed a noticeable growth in the development of stealthy Android-based malware which has led to a pressing need for accurate malware detection systems. In this paper, we propo...
- 1 January 2022
- Published by Inderscience Publishers in International Journal of Information and Computer Security
- Vol. 18 (3/4) , 327-347
GENDroid - a graph-based ensemble classifier for detecting Android malware
Recent years have witnessed a noticeable growth in the development of stealthy Android-based malware which has led to a pressing need for accurate malware detection systems. In this paper, we propo...
- 6 December 2020
- Published by Springer Nature
- p. 253-266
Detection of Malign and Benign PE Files Using Texture Analysis
- 6 December 2020
- Published by Springer Nature
- p. 253-266
Detection of Malign and Benign PE Files Using Texture Analysis
- Open Access
- 25 December 2019
- Published by Korean Institute of Intelligent Systems in International Journal of Fuzzy Logic and Intelligent Systems
- Vol. 19 (4) , 290-298
Meta-Heuristic Algorithms to Improve Fuzzy C-Means and K-Means Clustering for Location Allocation of Telecenters Under E-Governance in Developing Nations
The telecenter, popularly known as the rural kiosk or common service center, is an important building block for the improvement of e-governance in developing nations as they help in better citizen engagement. Setting up of these centers at appropriate locations is a challenging task; inappropriate locations can lead to a huge loss to the government and allied stakeholders. This study proposes the use of various meta-heuristic algorithms (particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering approaches (K-means and fuzzy C-means) used in the facility location allocation problem and maps them for the betterment of telecenter location allocation. A dataset from the Indian region was considered for the purpose of this experiment. The performance of the algorithms when applied to traditional facility location allocation problems such as set-cover, P-median, and the P-center problem was investigated, and it was found that their efficiency improved by 20%-25% over that of existing algorithms.
- 25 December 2019
- Published by Korean Institute of Intelligent Systems in International Journal of Fuzzy Logic and Intelligent Systems
- Vol. 19 (4) , 290-298
Open AccessMeta-Heuristic Algorithms to Improve Fuzzy C-Means and K-Means Clustering for Location Allocation of Telecenters Under E-Governance in Developing Nations
The telecenter, popularly known as the rural kiosk or common service center, is an important building block for the improvement of e-governance in developing nations as they help in better citizen engagement. Setting up of these centers at appropriate locations is a challenging task; inappropriate locations can lead to a huge loss to the government and allied stakeholders. This study proposes the use of various meta-heuristic algorithms (particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering approaches (K-means and fuzzy C-means) used in the facility location allocation problem and maps them for the betterment of telecenter location allocation. A dataset from the Indian region was considered for the purpose of this experiment. The performance of the algorithms when applied to traditional facility location allocation problems such as set-cover, P-median, and the P-center problem was investigated, and it was found that their efficiency improved by 20%-25% over that of existing algorithms.