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In this paper, we work on suspicious big text data analysis technique for prediction of terrorism activity like financial fraud, money laundering, recruitment, radicalization, fundraising, violent and illegal post and video sharing on darkweb environment also called as cosmic web due to hidden content attributes. The consequent activity prognosis (CAP) is required for minimizing the risk associated with cyber information and personal security compromise for collectively data analysis referred as big data. The cyberterrorist and criminal hackers generated denial of service attack (DoS), distributed DoS attack (DDoS) and ransom-related DoS attack (RDoS) attack thereby overloading the server and increasing and blocking the server execution. The cyber threats and activities could only be reducing the execution time of activities marked suspicious and not safe. The propose model is based on computational …