machine learning algorithm to detect a malware
Budget: £20 – £250 GBP
The task is to identify network features of a chosen malware from pcap files which will be extracted and placed into datasets for machine learning malware detection. These features have to be behavioural and informative features that clearly indicate the malwares presence on the network, such as the ones mentioned in this link: https://code.google.com/archive/p/netmate-flowcalc/wikis/Features.wiki
With the findings, generate a small report on how the malware operates in a network sense. All findings must be related to its network behaviour, excluding anything to do with how the malware behaves on the system. Identify at least 5 distinctive features that are common in PCAP files that are clear indicators of maliciousness of the malware. These features need to be extracted from wireshark so the features should be extracted from there.
I want the freelancer to extract the features to add to a dataset. This dataset will be experimented on with machine learning algorithms to design an IPS/IDS
With the findings, generate a small report on how the malware operates in a network sense. All findings must be related to its network behaviour, excluding anything to do with how the malware behaves on the system. Identify at least 5 distinctive features that are common in PCAP files that are clear indicators of maliciousness of the malware. These features need to be extracted from wireshark so the features should be extracted from there.
I want the freelancer to extract the features to add to a dataset. This dataset will be experimented on with machine learning algorithms to design an IPS/IDS