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

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.