PI Details | Co-PI Details |
---|---|
Dr. Divya Bansal | Dr. Sanjeev Sofat |
Funding Agency | Project Cost |
---|---|
Department of Science & Technology, New Delhi |
Rs. 69.90 Lacs Amount Received till date (in Rs.) Ist Grant Rs. 15,50,000.00 - Recurring |
Start Date | Completion Date | Status |
---|---|---|
2019-07-15 | 2023-09-30 | Ongoing |
The research project aims to address various terrorist activities, such as cyber recruitment and illegal procurement of modern weapons for potential mass attacks. The primary focus is on designing and developing a framework capable of extracting actionable intelligence related to terrorist activities from diverse sources, including emails, physical devices, news items, online media, social media, blogs, and formal sources. The ultimate goal is to enhance national security by predicting potential threats and taking corrective action through the analysis of criminals/terrorists' behavioral models.
The project emphasizes the efficient use of free and open-source tools available in the market to extract the most accurate and relevant information for national interests. It also aims to design a system that can predict terror attacks and perform perception management for national security agencies, providing clear indications of whether citizens should be alerted. Threats will be classified into five levels: Not Expected, Possible, Probable, Expected, and Certain.
An essential aspect of the research is to detect and classify "Radical/Anti National" or "Extremist" online social content based on specific criteria, such as religious or political motivation, unethical provocation, racism, and more. This will help identify and tag sources spreading anti-national ideologies as "Radical."
Another significant component of the research involves conducting a comprehensive study of terrorist groups operating in India. The aim is to detect malicious users, including those involved in child pornographic content, fake accounts, and followers market activities. A model will be developed to assign Trust Scores and assess online social network users.
The proposed framework will utilize probabilistic modeling techniques, machine learning approaches, and big data analytics methodologies employed by organizations like NSA, Google, and Amazon. These techniques will be used to model behaviors and maintain public welfare through surveillance or make predictions about users/customers of web services.
The anticipated outcomes of the project are twofold. Firstly, the framework's practical application will enable the prediction of potential threats to national security, facilitating timely corrective actions through the analysis of criminals/terrorists' behavioral patterns. Secondly, the system will include a predictive terror attack engine to aid national security agencies in making informed decisions about citizen alerts and alarms. Additionally, an Automated Perception Management and Influence Maximization System will be developed using machine learning and deep learning techniques, along with mobile applications employing sensors to propagate "Perceptions" and enhance influence on individuals through a chat-bot.
In conclusion, the research project seeks to contribute significantly to national security efforts by utilizing advanced technologies to detect and mitigate potential terrorist activities. By extracting actionable intelligence from various sources and employing sophisticated modeling techniques, the project aims to enhance threat prediction and perception management for the benefit of society and the nation at large.
Manpower Sanctioned/Hired | Manpower Trained |
---|---|
JRF (Nos) : 01 |
Ph.D. Produced : 04 |
Name of Equipment | Make & Model | Year of Purchase | Cost | Salient Features of Equipment | Condition (Working/ Not Working) |
---|---|---|---|---|---|
Purchase of Apple MAC Book Pro | Apple | 2021 | 1,60,080 | Working | |
Purchase of Apple MAC Book Pro | Apple | 2021 | 1,97,600 | Working |
Authors name |
Title of paper |
Journal name |
Volum e |
No. |
Page No. |
Year |
DOI |
---|---|---|---|---|---|---|---|
Shubhangi Rastogi & Divya Bansal |
Visualization of Twitter Sentiments on Kashmir Territorial Conflict,
|
Cybernetics & Systems |
52 |
7 | 1-28 | 2021 | https://doi.org/10.1080/01969722.2021.1949520 |
Jaspal Kaur Saini & Divya Bansal |
Detecting Online Recruitment of Terrorists, Towards Smarter Solutions to Counter Terrorism |
International Journal of Information Technology |
13 |
1 |
697-702 |
2021 |
https://doi.org/10.1007/s41870-021-00620-2 |
Parmod Kalia, Divya Bansal, Sanjeev Sofat |
A hybrid approach for preserving privacy for real estate data, |
International Journal of Information and Computer Security, |
15 |
4 |
400-410 |
2021 |
https://dx.doi.org/10.1504/IJICS.2021.116942 |
Amardeep Singh, Monika Singh, Divya Bansal, Sanjeev Sofat, |
Optimised K-Anonymisation Technique to Deal with Mutual Friends and Degree Attacks, |
International Journal of Information and Computer Security |
14 |
3-4 |
281-99 |
2021 |
https://doi.org/10.1504/IJICS.2021.114706 |
Jaspal Kaur Saini, Divya Bansal, |
A Comparative Study and Automated Detection of Illegal Weapon Procurement Over Dark Web, |
Cybernetics and Systems, |
50 |
5 |
405-16 |
2019 |
https://doi.org/10.1080/01969722.2018.1553591 |
Monika Singh, Amardeep Singh, Divya Bansal, Sanjeev Sofat |
An Analytical Model for Identifying Suspected Users on Twitter |
Cybernetics and Systems |
50 |
4 |
383-404 |
2019 |
https://doi.org/10.1080/01969722.2019.1588968 |
Armaan Kaur, Jaspal Kaur Saini, and Divya Bansal |
Detecting Radical Text over Online Media using Deep Learning." |
arXiv preprint arXiv:1907.12368 (2019) In First International Workshop Intelligent Information Feed, in conjunction with KDD 2019, Alaska USA. |
|
|
|
2019 |
https://doi.org/10.48550/arXiv.1907.12368 |
Shubhangi Rastogi, Divya Bansal, |
Misinformation Analysis during Covid-19 Pandemic” |
ICT Systems and Sustainability. Springer AISC/ LNNS, Singapore |
|
|
553-561 |
2021 |
http://dx.doi.org/10.1007/978-981-15-8289-9_54 |
Megha Chaudhary & Divya Bansal |
Open-Source Intelligence Extraction for Terrorism-Related Information: A Review
|
Wiley Interdisciplinary Reviews on Data Mining and Knowledge Discovery |
|
|
|
July 2022 |
|
Chesta Sofat & Divya Bansal |
RadScore: An Automated Technique to Measure Radicalness Score of Online Social Media Users
|
Cybernetics and Systems, Taylor and Francis |
|
|
|
2022 |
DOI: 10.1080/01969722.2022.2059134 |
Shubhangi Rastogi, Divya Bansal |
Disinformation detection on social media: An integrated approach |
Multimed Tools Appl, Springer |
|
|
1-33 |
May 12, 2022 |
https://doi.org/10.1007/s11042-022-13129-y |
Megha Chaudhary, Sachin Vashistha & Divya Bansal, |
Automated Detection of Anti-National Textual Response to Terroristic Events on Online Media, Cybernetics and Systems |
Taylor & Francis |
|
|
|
19 Jul 2021 |
|
Parmod Kalia, Divya Bansal, Sanjeev Sofat |
Privacy Preservation in Cloud Computing Using Randomized Encoding, Wireless Personal Communications |
Springer US |
118 |
4 |
1-13 |
2021 |
|
Authors Name | Title of Paper | Name of Conference | Place | National/ International | Page No. | Year | DOI Number |
---|---|---|---|---|---|---|---|
Tamanna Goyal, Jaspal Kaur Saini, Divya Bansal |
Analyzing Behavior of ISIS and Al-Qaeda using Association Rule Mining. |
Proceedings of 2nd International Conference on Communication, Computing and Networking |
|
International |
|
2019 |
https://doi.org/10.1007/978-981-13-1217-5_66 |
Megha Chaudhary, Divya Bansal, |
“Agitation on Social Media amid Terrorist Attacks: A case study on Jammu and Kashmir” |
IEM-ICDC 2020, International Conference on Computational Intelligence, Data Science and Cloud Computing, Springer |
Virtual Conference |
International |
|
2020 |
https://doi.org/10.1007/978-981-33-4968-1_30 |
Shubhangi Rastogi, Divya Bansal, |
“An Adaptive Approach for Fake News Detection in Social Media: Single vs Cross Domain” |
International Conference on Computational Science and Computational Intelligence (CSCI’21) December 15-17, 2021, Las Vegas, USA
|
Las Vegas, USA |
International |
|
2021 |
https://doi.org/10.1109/CSCI54926.2021.00280 |
Shubhangi Rastogi, Divya Bansal |
“Time is Important in Fake News Detection: a short review”, |
International Conference on Computational Science and Computational Intelligence (CSCI’21) December 15-17, 2021, Las Vegas, USA
|
Las Vegas, USA |
International |
|
2021 |
https://doi.org/10.1109/CSCI54926.2021.00286 |
Parmod Kalia, Divya Bansal, Sanjeev Sofat |
An Approach of Optimal Anonymization for Preserving Privacy in Cloud, |
Proceedings of the 5th International Conference on Cyber Security & Privacy in Communication Networks (ICCS), |
|
International |
1556-5068 |
2019 |
|