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Network Forensic on Web-based Applications using Network Forensic Development Life Cycle Method
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 47 |
| Year of Publication: 2022 |
| Authors: Sukmawati Lasaharu, Imam Riadi |
10.5120/ijca2022921869
|
Sukmawati Lasaharu, Imam Riadi . Network Forensic on Web-based Applications using Network Forensic Development Life Cycle Method. International Journal of Computer Applications. 183, 47 ( Jan 2022), 8-14. DOI=10.5120/ijca2022921869
Abstract
It is important to note computer network security. At any point, a web server can be attacked. There are many types of attacks that can be carried out by attackers. One type of attack that is often carried out is a Distributed Denisal of Service (DDOS) attack. Distributed Denial of Service (DDOS) attacks are one type of attack that attackers frequently use to increase traffic to the point where the server cannot handle client requests and may even cause the server to fail. To limit the likelihood of an attack, a network security system able to detect attacks is required. Snort is a software program that is capable of detecting an attack in real time by executing a rule that produces a log file containing information about network activity. Additionally, it is used to conduct network forensic analysis using the Network Forensics Development Life Cycle (NFDLC) method, which is a branch of digital forensic science concerned with the steps necessary to discover evidence of attacks originating from log files. The analysis method is comprised of the following stages: Initiations, Acquisition, Implementation, Operations, and Disposition. According to the findings of the research, Snort's Intrusion Detection System (IDS) is capable of detecting DDOS attacks on web servers. Based on the analysis of the log files using wireshark, there are 3 IP addresses, who tried to commit crimes against the web server. From the results of the DDOS attack analysis, it can be used as digital evidence from the results of network forensic investigations.
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