Authors :
Ssonko Denison; Francis Lowu; Adam Alli. A
Volume/Issue :
Volume 8 - 2023, Issue 5 - May
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/yc43b97r
DOI :
https://doi.org/10.5281/zenodo.8150039
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
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
