Keeping Track of Network Infrastructure Vulnerabilities Using a Network Forensic Approach

Currently, new network infrastructures must support new hybrid technologies related to AI, IoT, 5G, 6G, machine learning, and deep learning, which consume large bandwidths and require the development of sophisticated recursive algorithms that allow managing large volumes of data and guarantee an optimal level of security in the face of the mass operations that companies must carry out. Given these types of scenarios, automation would be the most viable way to manage most services that result from the hybrid interaction of these technologies. All this combination of technological artifacts combined with using clients generates the proliferation of adware, browser hijackers, and potentially unwanted programs such as malware, worms, Trojans, etc., which circulate through network structures. This article aims to propose a model with a forensic network approach that allows, from a collection of data, to locate and detect the malicious code incorporated in one or several data packets, which shows the vulnerabilities that the network architecture may have. Packet capture libraries (PCAP) will be used in a wireless network architecture, which will analyze packets with packet analysis and network tracing tools such as Wireshark. Implementation of the HTTP log viewer, Sawmill, and case study tools will also be used.