Facilities Provided by CCI

This Centre for Cyber Intelligence aims to create awareness about Cyber Security with Artificial Intelligence (AI) techniques with its practical applications. To ensure security in various sectors that address real-world problems through an AI approach. Cyber intelligence-based research and projects were given to scholars and various students from M.Sc Computer Science, Master of Computer Applications (MCA), and M.Sc Information Technology. Cyber Security certification courses were introduced for Information Technology and through hybrid mode various hands-on training programs, Workshops, Faculty Development Programs, and Internship programs are provided to the participants and students from inside and from all over India. This Centre is standalone for providing security solutions to facilitate the students and researchers to build the cyber ecosystem. The Centre also expands its boundary by collaborating with international tie-ups with Soebit Cyber Security, The Netherlands, Europe.

• CCI Research Lab

• Accessibility of  Open Source Tools for Cyber Security

• Kali Linux Tool

• Wireshark for Network Traffic Monitoring

• Python for Cyber Intelligence

• 2.4TB Dell PowerEdge R740 - Rack Server 

Thrust Areas of CCI

• Mobile Malware Detection
• Insider Threat Detection in Cloud
• Phishing Detection
• Spam Detection
• IoT attack Detection
• Network Intrusion Detection
• User Authentication Biometrics
• Vulnerability Assessment
• Security Auditing
• Template attack Detection
• Anomaly Detection
• Face Spoofing/Deep Fake Detection

Services

Research

Software tools provided for Cyber Security and Cyber Intelligence 

• Kali Linux for Cyber Security
• Wireshark for Network Traffic Monitoring
• Python for Cyber Intelligence

                                                                                                                                                          

Consultancy Services

S.No.	Consultancy Service	Total Hours	Charges
1.	Machine Learning Model Development for Cyber attack detection and mitigation	Depends on the Model	Rs. 500 / model
2.	Biometric authentication for fraud detection	Depends on the Model	Rs. 500 / model

 

Training Services

S.No.	Title	Total Hours	Charges
1.	Mobile Malware Classification using Supervised Machine Learning Methods in Python	16 Hrs	Rs. 500
2.	Vulnerability Assessment with Nessus	8 hrs	Rs. 200
3.	Mobile Malware Analysis with Unsupervised Machine Learning Methods using Python	9 hrs	Rs. 200
4.	Ensemble Methods of Feature Selection for Detecting Phishing Websites using Python	7 hrs	Rs. 200
5.	Sampling Techniques for Detection of Malicious Insiders in Cloud using Python	7 hrs	Rs.200
6.	Security Auditing using NMAP	8 hrs	Rs. 200
7.	Cyber Threat Intelligence	30 hrs	Rs. 2000
8.	Web Application Security Testing with Burp Suite	8 hrs	Rs. 200
9.	Mobile Malware Data Analysis using Regression Models with Python	9 hrs	Rs. 200
10.	Network Simulator 2 Scratch with Techies	12 hrs	Rs. 300
11.	Data Protection and Privacy	30 hrs	Rs. 2000
12.	Open Source Tools for Cyber Security	8 hrs	Rs. 200
13.	Ethical Hacking using Open Source Tools	8 hrs	Rs. 200
14.	Vulnerability Assessment and Penetration Testing	36 hrs	Rs. 2500
15.	Quantum Secure Computing	8 hrs	Rs. 200
16.	Demystifying IoT Security	8 hrs	Rs. 200
17.	Vulnerability Assessment and Management	40 hrs	Rs. 3000
18.	Malware Detection using Machine Learning with Python	30 hrs	Rs. 2000

Certificate Courses

S.No.	Course Name	Total Hours	Charges
1.	Malware Detection using Machine Learning with Python	40 hrs	Rs. 3000
2.	Vulnerability Assessment and Management	40 hrs	Rs. 3000
3.	Web Application Security with Burp Suite	40 hrs	Rs. 3000
4.	Digital Forensics	40 hrs	Rs. 3000

Team

Staff In-charge

Dr.G.Padmavathi

Staff In-charge

Centre for Cyber Intelligence

Dean - School of Physical Sciences and Computational Sciences

               Mail id : padmavathi_cs@avinuty.ac.in

 

Dr.D.Shanmugapriya

Assistant Professor and Head

Department of Information Technology

 

Mrs.S.Karthika

Assistant Professor 

Department of Information Technology

 

Dr.D.Nethra Pingala Suthishni

Assistant Professor

Department of Information Technology

 

Dr.A.Sumi

Assistant Professor

Department of Information Technology

 

Mrs.A.Roshni

Research Assistant

Centre for Cyber Intelligence

Research Title: Malware Detection and Prediction using Machine Learning and Deep Learning Techniques

Research Scholars

Mrs.S.Asha

Research Scholar

Department of Computer Science

Research Title: Detection and Mitigation of Cloud Insider Threat Using Machine Learning and Deep Learning Techniques

 

 

 

Certificate Courses

• Certificate course on Malware Detection using Machine Learning with Python Details Click here to Register
• Certificate course on Vulnerability Assessment and Management Details Click here to Register
• Certificate course on Web Application Security with Burpsuite Details Click here to Register
• Certificate course on Digital Forensics Details Click here to Register

Publications

Copyrights - 3

• 1. Ganapathi, P. ., Shanmugapriya, D. ., & Roshni, A. . (2022). Dynamic Analysis Based Mobile Malware Classification Using Supervised Machine Learning Methods, 1–168. https://doi.org/10.9734/bpi/mono/978-93-5547-441-4, B P International. ISBN 978-93-5547-441-4 (Print), ISBN 978-93-5547-442-1 (eBook) 

  2. Padmavathi Ganapathi, S. Karthika (2022), Vulnerability Assessment with Nessus, 1-107,  Notion Press, ISBN: 9798886848632  https://notionpress.com/read/vulnerability-assessment-with-nessus 

  3. Padmavathi Ganapathi, D. Nethra Pingala Suthishni (2023). Security Auditing with NMAP. pp. 1 - 114. ISBN: 9798889350699, Publisher: Notion Press. https://notionpress.com/read/security-auditing-with-nmap

Journals - 7

1. Asha S, Shanmugapriya D, Padmavathi G, “Malicious insider threat detection using variation of sampling methods for anomaly detection in cloud environment” Computers and Electrical Engineering, Volume 105, 2023,108519, ISSN 0045-7906, DOI: https://doi.org/10.1016/j.compeleceng.2022.108519. 

2. Asha S., Shanmugapriya D., "Understanding insiders in cloud adopted organizations: A survey on taxonomies, incident analysis, defensive solutions, challenges", Future Generation Computer Systems, Volume 158, 2024, Pages 427-446, ISSN 0167-739X, DOI: https://doi.org/10.1016/j.future.2024.04.033.

3. Padmavathi Ganapathi, Roshni Arumugam, Shanmugapriya Dhathari., "An intelligent obfuscated mobile malware detection using deep supervised learning algorithms", Bulletin of Electrical Engineering and Informatics, Volume 13, Issue 4, Pages 2604-2612, ISSN: 2089-3191, e-ISSN: 2302-9285, DOI: https://doi.org/10.11591/eei.v13i4.6974

4. Shanmugapriya, D.; Pingala Suthishni, D. Nethra; Sasirekha, V.; Padmavathi, G.; Keerthika, M., "A Survey on Spoofing and Selective Forwarding Attacks on Zigbee Based WSN.", Mapana Journal of Sciences, 2023, Vol 22, p397,ISSN 0975-3303, DOI: 10.12723/mjs.sp2.23

5. Bhuvaneswari, K.; Roshni, A.; Padmavathi, G.,"Evaluation of Selected Supervised Machine Learning Models for Phishing Website Detection.", Grenze International Journal of Engineering & Technology (GIJET), 2024, Vol 10, p2011, ISSN 2395-5287

6. Kiruthika, S.; Roshni, A.; Padmavathi, G., "Detection of Obfuscated Malware using Ensemble Learning Techniques.", Grenze International Journal of Engineering & Technology (GIJET), 2024, Vol 10, p1978, ISSN 2395-5287

7. Sneha, S.; Roshni, A.; Padmavathi, G., "A Stacked Ensemble Model to Detect Network Intrusions.", Grenze International Journal of Engineering & Technology (GIJET), 2024, Vol 10, p2045, ISSN 2395-5287

Conferences - 11

1. Padmavathi,G.,Shanmugapriya,D.,Asha,S.(2022). "A Framework for Improving the Accuracy with Different Sampling Techniques for Detection of Malicious Insider Threat in Cloud" In:Uddin,M.S.,Jamwal,P.K.,Bansal,J.C.(eds) Proceedings of International Joint Conference on Advances in Computational Intelligence.Algorithms for Intelligent Systems. Springer,Singapore.https://doi.org/10.1007/978-981-19-0332-8_36   (Springer)

2. G.Padmavathi, D.Shanmugapriya and A.Roshni, "Performance Analysis of Unsupervised Machine Learning Methods for Mobile Malware Detection," 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),2022,pp.201-206, doi:10.23919/INDIACom54597.2022.9763180. (Scopus Indexed)

3. G.Padmavathi , D.Shanmugapriya and S.Asha, "A Framework to Detect the Malicious Insider Threat in Cloud Environment using Supervised Learning Method," 2022 9th International Conference on Computing for Sustainable Global Developement (INDIACom), 20222,pp.354,doi:10.23919/INDIACom54597.2022.9763205. (Scopus Indexed)

4. Dr.D.Nethra Pingala Suthishni , Dr.D.Shanmugapriya, Dr.V.Sasirekha, and Dr.G.Padmavathi, "Performance Evaluation on Selective Forwarding Attack Detection using Machine Learning Techniques implemented in ZIGBEE Network", Springer Proceedings of 2nd International Conference on Next Generation Computer System. (ICNGCS - 2023)

5. D.Shanmugapriya,G.Padmavathi and A.Aysha, "Detection of Iris Template Attacks using Machine Learning and Deep Learning Methods", 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom),2023. (Scopus Indexed).

6. S. Sneha, A. Roshni, and G. Padmavathi, "A Stacked Ensemble Model to Detect Network Intrusions", Fourteenth International Conference on Advances in Communication, Network, and Computing - CNC 2023. (Scopus Indexed) 

7. K. Bhuvaneswari, A. Roshni, and G. Padmavathi, "Evaluation of Selected Supervised Machine Learning Models for Phishing Website Detection", Fourteenth International Conference on Advances in Communication, Network, and Computing - CNC 2023. (Scopus Indexed) 

8. S. Kiruthika, A. Roshni, and G. Padmavathi, "Detection of Obfuscated Malware using Ensemble Learning Techniques", Fourteenth International Conference on Advances in Communication, Network, and Computing - CNC 2023. (Scopus Indexed)

9. S. Karthika, G. Padmavathi, A. Roshni and S. Varshini, "Detecting Cross-Site Scripting Attack using Machine Learning Algorithms," 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2024, pp. 991-995, doi: 10.23919/INDIACom61295.2024.10499119. (Scopus Indexed)

10. D. N. P. Suthisini, J. J. Merlien, D. Shanmugapriya, G. Padmavathi and A. Roshni, "Performance Analysis of Cyberbullying Threats in Social Media using Machine Learning Techniques," 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2024, pp. 751-757, doi: 10.23919/INDIACom61295.2024.10499020. (Scopus Indexed)

11. D. Shanmugapriya, C. J. Dhanya, S. Asha, G. Padmavathi and D. N. P. Suthisini, "Cloud Insider Threat Detection using Deep Learning Models," 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2024, pp. 434-438, doi: 10.23919/INDIACom61295.2024.10498767. (Scopus Indexed)

Book Chapters - 5

1. G Padmavathi , D Shanmugapriya, S Asha (2022), "Detection of Malicious Insider in Cloud Environment based on Behavior Analysis", Progressions made in Cyber-Security World , pg : 1-9,ISBN:978-1-003-30238-4(ebk) DOI:10.201/9781003302384, CRC Press.  (Taylor and Francis)

2. G Padmavathi , D Shanmugapriya , A Roshni (2022), "Evaluation of Supervised Machine Learning Classifiers to Detect Mobile Malware", Progessions made in Cyber-Security World , pg:1-9 , ISBN:978-1-003-30238-4(ebk) DOI :10.201/9781003302384, CRC Press . (Taylor and Francis)

3. Ganapathi , P. ., Shanmugapriya , D . .,Roshni, A. .(2022). "Evaluation of Principal Component Analysis Variants to Assess Their Suitability for Mobile Malware Detection". In (Ed.), Advances in Principal Component Analysis.IntechOpen. https://doi.org/10.5772/intechopen.105418

4. Gaayathri M., Padmavathi Ganapathi, Roshni A., Shanmugapriya D (2023), “Wrapper-Based Feature Selection for Detecting the Lexical Phishing Websites Using Ensemble Learning Algorithms”, Malware Analysis and Intrusion Detection in Cyber-Physical Systems, IGI Global, DOI: 10.4018/978-1-6684-8666-5, ISBN13: 9781668486665 | ISBN10: 1668486660 | EISBN13: 9781668486689 

5. Sri Danalaksmi P., Geethalakshmi S. N., Roshni A., Padmavathi Ganapathi (2023), “Classification of Firewall Log Files Using Supervised Machine Learning Techniques”, Malware Analysis and Intrusion Detection in Cyber-Physical Systems, IGI Global, DOI: 10.4018/978-1-6684-8666-5, ISBN13: 9781668486665 | ISBN10: 1668486660 | EISBN13: 9781668486689 

Activities

• Organizing hands-on training and workshops on security tools and techniques
• Guiding and motivating UG and PG students to take up projects
• Creating awareness among women, girl children and public on Cyber Frauds, Scams and Threats
• Promotion of best practices for Social Media Security
• Orienting the Information Technology Act, its amendments, and Cyber laws
• Development of video lessons for training
• Promotion of Security Audit practice within the institution
• Establishment of tie-ups and interactions with organizations
• Conduct research in Cyber Intelligence domain and encourage publications, copyrights and patents

CCI Trainings and Workshops

CCI Training Programmes