User Information Mining And Analysis Oriented The Social Engineering Network Penetration

With the development of safety technology, the use of loopholes in system intrusion becomes increasingly difficult. A growing number of intruders make Social Engineering in network penetration more and more common by using the human factor to prepare for the attack, and to create a loophole in disguise. Social network's core idea is to find the negligent users or psychological weaknesses. For permeate social workers, complete and real personal information is the key determinant of successful penetration.The legitimate user profile information useful to establish a database goal, to improve the penetration query interface according to the needs of social workers. However, there are various difficulties in mining user information, including unstructured problems, difficulties and non-cross-site quantification problems. In this paper, these problems have been studied and the main contents are summarized as follows:(1) For the unstructured difficulties, web-based user information extraction crawler technology will be studied in this paper. We can design a well-functioning crawler system and thus effectively carry out the user information for the target website crawling work.(2) For the cross-site user information difficulties, we shall study the cross-site users matching problem. Here are two main steps: Disambiguation of the same name and different name resolution. This module is jointly implemented that precision matches are carried out for profile information which has a unique value like sex, age, while fuzzy matches are used for information with some restrictions like user names. Experimental results show that this method is effective and to some extent feasible.(3) Information for the user of the non-quantifiable brings more difficulty, text mining technology, in text data mining, research of user metric information for a large number of characteristic values of the acquired properties will have the same thought by clustering algorithm eigen values classified as a class, and provides visual interface.(4) Based on the perspective of the application of the text, in the structure, the degree of quantification, the basis of user information across the site, the relevant data for effective storage, and providing a good search interface for the user.The topic mainly starts from the above four questions, problems are solved one by one and some preliminary results can be obtained. With the continuous improvement of user information mining technology, it's believed that this will be more helpful to a various social applications and social computing related research.