Survey on Different Data Mining Techniques for E- Crimes VirtualCom-2016, International Virtual Conference on Computer Science, Engineering and Technology, 25-28 Dec 2016 Survey on Different Data Mining Techniques for E- Crimes Presented by: Nidhi Sethi, Dr. Pradeep Sharma, Dr. Bharat Mishra

ABSTRACT E crimes are the crimes performed with the help of computer. They are increasing in proportion with the technology usage of the common man. Detection of E crimes is incurring a very high cost to individual, organization and government as huge data collection and analysis is required to find them. A big challenge is faced by technocrats to detect E crimes efficiently from voluminous data. On the other hand data mining is powerful tool for extracting useful information from a huge data base. Thus this paper has merged these two fields in order to find a good solution to the problem. This paper will answer the question of how data mining techniques can be used to detect these unseen E crimes. It is also going to describe how Cybercrimes problems can be thought of as data mining problems

INTRODUCTION The E crime data is increasing day by day and becoming voluminous. E crime has become a global threat and to detect various E crimes from a large data set has become a universal challenge. Data mining plays an important role towards facing and solving this challenge of extraction of information from large E crimes collected data

Continued.. This paper is going to discuss the correlation of E crimes and data mining It is going to provide the framework for E crimes problems as data mining problems Initially we go through the concepts of various techniques then we are illustrating the concepts and challenges of E crimes; Also we are describing how data mining can be useful in solving these challenges with its vast set of methods Our contribution of the paper is to understand the application of different data mining techniques to detect various threats of E crimes.

Basic concepts in Data mining Meaning and definition: Data mining is a method of extraction of some patterns, correlations, associations of different entities from a large database. Various methods Association rule mining Clustering Classification and prediction Sequential pattern mining Outlier detection Web mining Entity extraction

Challenges of Cybercrimes Password Hacking Or Unauthorized Access Money Laundering, Stock Market Manipulations, Cyber Bullying Cyber Terrorism Credit Card Fraud Detection Printing And Publishing Pornographic Material Selling Of Illegal Material Narcotics, Cocaine, Weapons Creation Of Duplicate Currency Notes, Mark Sheets, Stamps Email spamming and email spoofing

Framework for Cybercrime as data mining problems

How data mining can be useful With time sequence mining one can find the time when the next E crime is going to occur. Sequence of E crime patterns in a specified time interval can be generated with it. Clustering can be used in detection of stock market price manipulation. Clustering is also very important in email and spamming. Region wise occurring computer crimes can also be grouped with the help of clustering Outlier analysis can be used to locate the hidden data associated with the various computer crimes

Continued… Outlier Analysis can also be applied in finding the frauds, which are generally .unusual transactions, appeared in financial transactions. Association rule mining in computer crime analysis is generally used to detect various crime patterns which are meaningful as well as useful. With ARM one can also .detect the rare crime patterns. Email spoofing or phishing can be detected with the help of an intelligent classifier of adversarial data mining. Entity Extraction finds the text from an unstructured or semi structured data

Continued… Entity Extraction helps in detection of cybercrimes especially cyber bullying and child predation as data collection for these are usually unstructured in nature. Classification and prediction techniques are generally used at early stages in E crimes detection process. Classification and prediction is very much useful in classifying the different categories and further sub categories of crimes. With help of Classification and prediction one can predict a certain group category involving in certain crimes

Conclusion This paper provides an overview of the necessity and utility of data mining in computer security especially in detection of cybercrimes. Data mining offers benefits to the organizations and individuals in extraction of meaningful crime data. This paper also discusses how different data mining techniques and algorithms can be used in solving different cyber problems. It also provides the outline of cybercrime problems that can be solved with data mining process. Thus this paper can be extended in future research of specific data mining technique detecting a particular type of computer crime.

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