Text analysis framework for understanding cyber-crimes

Article history: Received 17 February 2017 Received in revised form 11 August 2017 Accepted 19 August 2017 The magnitude of impact of cyber-crimes is much greater as compared to other crimes and can be felt at personal, societal, national as well as global level. According to studies, developing countries are at a greater risk due to such crimes. Fight against cyber-crime requires a strategic and intelligent framework. This paper discusses text analysis framework using Natural Language Processing (NLP) and text mining techniques to extract crime related information which can be used for educating and spreading awareness and for further knowledge based analysis. News articles crawled from a leading newspaper website in India is used as the source of cybercrime data. Parts of Speech (POS) tagging is used to extract important terms/concepts related to cybercrimes. Term association analysis on the other hand is used to understand the relationship of extracted terms of the data.

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