Publication Date: 2023/07/15
Abstract: This research focuses on proposing a network security algorithm for forensic management in Uganda government agencies. With the increasing dependence on technology, the risk of cyber-attacks and data breaches has become a major concern for government agencies, making it essential to develop effective security measures. The network security algorithm is based on machine learning, a method of data analysis that automates analytical model building to detect and prevent cyber- attacks, as well as to provide efficient forensic analysis of any security incidents that may occur. The algorithm was validated for accuracy, true positivity rate of traffic, and knowledge to capture network intruders. This was achieved using Python’s pycharm IDE environment and Google Collaborator to show how the normal and attacked traffic flow. A mixed-methods approach was used, including a survey of government agencies and interviews with cyber security experts in some agencies to gather information on the current security measures and identify areas that need improvement. The algorithm integrates various security technologies such as intrusion detection systems, and data encryption to provide a multi- layered defense system.
Keywords: Network Security, Algorithm, Forensics, PyCharm, DDOS, Government Agency
DOI: https://doi.org/10.5281/zenodo.8150039
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAY1028.pdf
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