Abstract
Cybercrime is referred to as aggressive, intentional act performed through electronic communications. In recent years, lack of awareness regarding technological advancements has paved the way for an intense increase in various types of aggressive cyber-attacks such as phishing, scamming, hacking etc. Under-reporting of cybercrimes serves as a major impediment in efficient and timely handling of cybercrimes, and hence can cause serious consequences. Manually staying informed regarding emerging cybersecurity threats is a time taking and laborious task, creating the need of developing robust systems that could efficiently report news related to cybercrimes. This requires development of information retrieval models to extract cybersecurity news belonging to different categories from various online resources. The focus of this research is to propose a model for detection of cyber offences reported on news articles and blogs. Further in order to analyze the authenticity of news obtained via news articles/blogs, a novel source verification model is proposed by investigating various authenticity parameters and assigning weightages to these parameters.