TZSP

Abstract: The COVID-19 pandemic has forced many people to do work from home (WFH). In practice, networks used in homes generally do not apply security and lack awareness of possible cybersecurity threats. The development and use of security systems on home networks with inexpensive and practical solutions are highly demanded. Therefore, a device that can detect cybersecurity threats is needed to minimize the risks with practical solutions and affordable costs. This conducted research provides a design of a Snort-based Intrusion Detection System (IDS) device that was applied to the Raspberry Pi 3 Model B+. TaZmen Sniffer Protocol (TZSP) is also implemented to analyze network traffic and The SHA3 algorithm used to calculate periodical hash value. This paper implements five types of attacks, there are ICMP BlackNurse, SYN Flood, SMTP Brute Force, RDP Brute Force, and Web Phishing. In addition, this research using the 'htop' program to perform performance testing, and ’sha3sum' program to conduct the test vector algorithm. The system has 100% accuracy rate detecting the attacks and requires less than 50% CPU and 10% RAM. So that the system can be applied to home networks as a practical and affordable cost solution in order to implement cybercrime security.