intelligent machine learning approach to detect malicious software in android as well in windows

intelligent machine learning approach to detect malicious software in android as well in windows

our objective is to detect malicious software and bugs and also to eliminate them in future using intelligent machine learning approach

Android

Description

Malware in android and windows can be detected using kernels in Linux environment and set of Application Program Interface (API) calls in case of android. There are three phases involved in this approach; the first phase contains files which have the extensions of .exe to be executed in parallel in Cuckoo Sandbox and eight virtual machines in virtual box, the second phase contains signature and behaviour based approach in detecting malware and final phase includes static and dynamic analysis to detect the malicious activity. The lists of tools required are debugger, system monitor, packet identifier, binary analysis and code analysis tools. Script language used is python, java, Perl, shell and the high level language like c, c++ can also be used to write code to detect malware. Though kaspersky virus removal tool, anti spyware, avast can be used to prevent malware, to prevent the future malwares and bugs our objectives plays a vital role for future purpose.

varshini r. added photos to project intelligent machine learning approach to detect malicious software in android as well in windows

Medium bf22a244 31e8 4d5f b008 d2bb416f40be

intelligent machine learning approach to detect malicious software in android as well in windows

Malware in android and windows can be detected using kernels in Linux environment and set of Application Program Interface (API) calls in case of android. There are three phases involved in this approach; the first phase contains files which have the extensions of .exe to be executed in parallel in Cuckoo Sandbox and eight virtual machines in virtual box, the second phase contains signature and behaviour based approach in detecting malware and final phase includes static and dynamic analysis to detect the malicious activity. The lists of tools required are debugger, system monitor, packet identifier, binary analysis and code analysis tools. Script language used is python, java, Perl, shell and the high level language like c, c++ can also be used to write code to detect malware. Though kaspersky virus removal tool, anti spyware, avast can be used to prevent malware, to prevent the future malwares and bugs our objectives plays a vital role for future purpose.

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varshini r. created project intelligent machine learning approach to detect malicious software in android as well in windows

Medium bf22a244 31e8 4d5f b008 d2bb416f40be

intelligent machine learning approach to detect malicious software in android as well in windows

Malware in android and windows can be detected using kernels in Linux environment and set of Application Program Interface (API) calls in case of android. There are three phases involved in this approach; the first phase contains files which have the extensions of .exe to be executed in parallel in Cuckoo Sandbox and eight virtual machines in virtual box, the second phase contains signature and behaviour based approach in detecting malware and final phase includes static and dynamic analysis to detect the malicious activity. The lists of tools required are debugger, system monitor, packet identifier, binary analysis and code analysis tools. Script language used is python, java, Perl, shell and the high level language like c, c++ can also be used to write code to detect malware. Though kaspersky virus removal tool, anti spyware, avast can be used to prevent malware, to prevent the future malwares and bugs our objectives plays a vital role for future purpose.

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