International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

An Optimization Technique for Mining Cybercriminal Network from Online Social Media

Author : Parvathy.G ¹ Bindhu J S ²

Date of Publication :7th February 2016

Abstract: Data mining is the process of collecting data from different context and summarizes them into useful information. Data mining can be used to determine the relationship between internal factors and external factors .It allows the users to analyze, categorize and determines the relationships inferred in them. Text mining usually referred to as text data mining can be used be used to extract information from text. Text mining can be used in information retrieval, pattern recognition and data mining techniques. The introduction of social media and social networks has not only changed the opportunities available for us but also we need to be beware about the threats. Recent researches show that the number of crimes are increasing through online social media and they may cause tremendous loss to organizations. Existing cyber technologies are not effective to protect organizations .Existing mining methods concentrate on lexicons in which they can identify only a limited number of relations. Here a genetic algorithm approach is introduced in which latent concepts can be extracted. Genetic Algorithm is a linear search which requires only little information from large search area.. Then these concepts are subjected to extract the semantics which infers the corresponding relationships. Genetic algorithm provides a better solution in which accuracy and time efficiency can be improved. The main contribution of the paper shows that they identify the corresponding cybercriminal networks.

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