A Comparative Study to analyze crime threats using data mining and machine learning approach

2021 ◽  
Author(s):  
Puninder Kaur ◽  
Geeta Rani ◽  
Taruna Sharma ◽  
Avinash Sharma
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Comparative Study ◽  
Learning Approach ◽  
Machine Learning Approach ◽  
Using Data

scholarly journals Malicious Threats Detection of Executable File

2020 ◽  
Vol 9 (3) ◽  
pp. 3257-3262
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Data File ◽  
Data Mining Algorithm ◽  
Instruction Set ◽  
Detection Algorithms ◽  
Client Machine ◽  
Machine Learning Approach ◽  
Executable File ◽  
Using Data

Malware is a general problems faced in the present day. Malware is a file that may be on the client machine. Malware can root an uncorrectable risk to the safety and protection of personal workstation clients as an expansion in the spiteful threats. In this paper explain a malware threats detection using data mining and machine learning. Malware detection algorithms with machine learning approach and data file. Also explained break executable files, create instruction set and take a look at different machine learning and data mining algorithm for feature extraction, reduction for detection of malware. In the system precisely distinguishes both new and known malware occurrences even though the double distinction among malware and real software is ordinarily little. There is a demand to present a skeleton which can come across latest, malicious executable files.

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