Framework for Generating Actionable – Intelligence from Cyber Space Using Computational Techniques & Analysis” under ICPS Programme of DST, GOI, New Delhi

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.)
Grant Rs. 16,50,000.00 Non – Recurring

Ist Grant Rs. 15,50,000.00 - Recurring
2nd Grant Rs. 18,95,698.00 - 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
RA (Nos) : 01
Others (Nos) : Project Attendant = 02

Ph.D. Produced : 04
M.Tech Produced : 03 Nos

Equipment Sanctioned/Procured
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


List of SCI Publications under Project

Authors name

Title of paper

Journal name

Volum e


Page No.



Shubhangi Rastogi & Divya Bansal

Visualization of Twitter Sentiments on Kashmir Territorial Conflict,





Cybernetics & Systems


7 1-28 2021

Jaspal Kaur Saini & Divya Bansal

Detecting Online Recruitment of Terrorists, Towards Smarter Solutions to Counter Terrorism

International Journal of Information Technology





Parmod Kalia, Divya Bansal, Sanjeev Sofat

A hybrid approach for preserving privacy for real estate data,

International Journal of Information and Computer Security,





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





Jaspal Kaur Saini, Divya Bansal,

A Comparative Study and Automated Detection of Illegal Weapon Procurement Over Dark Web,

Cybernetics and Systems,





Monika Singh, Amardeep Singh, Divya Bansal, Sanjeev Sofat

An Analytical Model for Identifying Suspected Users on Twitter

Cybernetics and Systems





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.





Shubhangi Rastogi, Divya Bansal,

Misinformation Analysis during Covid-19 Pandemic”

ICT Systems and Sustainability. Springer AISC/ LNNS, Singapore





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





DOI: 10.1080/01969722.2022.2059134

Shubhangi Rastogi, Divya Bansal

Disinformation detection on social media: An integrated approach

Multimed Tools Appl, Springer




May 12, 2022

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






List of Conference Publication Published in Proceedings under Project
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





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




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




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




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),






Output/Outcome of the Project
Output/Outcome of the project
  1. Created an extensive data repository of textual data from content of twitter, YouTube, online blogs, newspapers. Deployed crawlers for extracting tweets from twitter (schedulers & event based); Created a labelled dataset of tweets and online blogs/ news articles related to the conflict zones of Jammu and Kashmir.
  2. Developed data crawlers to extract data from social media (Twitter), fact checking websites (Snopes), and news websites (TOI, India Today, The Hindu etc.).
  3. Constructed different domain-specific corpus related to national security in order to develop automated models for fake news detection. Implemented pre-processing techniques to convert raw data extracted into structured form.
  4. Developed a framework based on interdisciplinary approach for the detection of:
    1. fake news on digital platforms.
    2. a sentiment classifier to measure the agitation on social media platform Twitter amid terrorist attacks.
    3. modules for detection and quantification of radicalization in Online User accounts.
    4. a novel deep learning-based model to detect anti-national code-mix textual content in Hindi & English languages on social media platform YouTube.