Malware detection

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Today's topic to share is all about malware detection so I would like to delve into my topic.

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Malware detection is phenomenon of identification and detection of malicious software which may harm computer systems, network and mobile devices. Malware may diverse forms which includes viruses, worms, trojans, spyware, adware, ransomware, and rootkits.

If I talk about types of malware detection then first of all these are viruses that replicate transfer to other files.Then other type is worms replicate itself which may spread to other systems after that.Trojans are another type which are disguising themselves as legitimate softwares.Afyer that spyware comes that are used for stealing sensitive data.If I talk about adwares then these are helpful in advertising un necessary displays.

There are some of the malware detection techniques in which first of all there is signature based detection which is used for identification of already known malware which utilize signature database.Behaviour base detection is used for monitoring behavior of system so that unknown malware may be detected.For identification of unusual systemic anomaly based detection is useful.There is heuristic baes detection which detect suspicious activity by utilizing rules are algorithms.

If I talk about machine learning in malware detection then machine learning are some algorithms used for malware detection.If I talk about supervised learning then it is trained at
databases which are labelled. If I talk about unsupervised learning then it is used for identification of pattern in back data which is un labeled.lf I talk about deep learning then it basically use neural network for detection of complex pattern.

There are different tools used for detection of malware in which first of all there is anti-virus software which is Norton.Secondly there is endpoint detection and response solutions which is carbon black as well as there are intrusion detection system, malware analysis sandbox as well as open source tools.

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If I talk about some of challenges in malware detection then these are malware dangers that are evolving with time. Another challenges zero day attack, advanced persistence dangers,Fireless malware and some of the evasion techniques which is code obfuscation.

If I talk about future of malware detection then it lies in development of artificial intelligence and machine learning advancement techniques as well integrity with other security technology. More than this if there would be development in cloud base detection and responses then it would be a plus point. If we analyse behaviour and danger hunting then it would be good for future of malware detection. Regarding automation of security processes should be careful about malware detection.

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