Crime Analysis and Prediction Model Using Data Mining and Machine Learning Techniques: Comparative Analysis - Singh, Neetu; Ajariya, Tripti; Raghuvanshi, Shailesh; Singh, Neha (International Journal of Computer Sciences and Engineering, 2021)
Crime is the illegal task perform by human system for perform unauthorise3d access of various services without legal permission. in computer system there are many categories of crime related with cybercrime. the crime is basically relating to offence which is happen by illegal task and permission. N this computer system the many crime is describing various cybercrime. Like malware, hacking, cyber-attacks, cyber illegal access, IOT hacking, phishing scams, ransom ware, etc. These are described various types of cybercrime in computer technology. for determine the any one we have used various algorithm and simulation tool performance. Thyis is destroy our human society transaction system. It is also created by some human; many companies also do this illegal work for our business growth. This cyber various crime is also impact of our country growth and development also decreased. In this research work we have determinate cybercrime attacks detection and prediction model of determine the cyber- attacks using data mining and machine learning techniques. For implementation of this proposed work we are using WEKA simulation tool for execute data mining algorithms and Jupiter anaconda navigator simulate tool for machine learning algorithms for determinate accuracy of data mining and design production model using machine learning algorithms. The attacks categories by cybercrime are ddos attacks, U2r, R2L, probe, ICMP attacks, UDP attacks, TCP attacks, FAR high false alarm rate, Dos attacks, these are cyber-attacks detection by data mining and machine learning algorithms based determinate accuracy and efficiency of data mining algorithms and prediction model by machine learning algorithms.