ABSTRACT

With the development of the Internet of Things (IoT), smart home systems have become a popular choice for modern consumers. However, information security in this context is becoming an increasingly pressing issue to be considered. The design of an adaptive Intrusion Detection System (IDS) on a Raspberry Pi device can be implemented to strengthen the firewall system in a smart home. This IDS aims to detect security threats and cyber attacks that may occur on a smart home network. Unlike static detection methods that only rely on certain rules, this adaptive IDS uses a machine learning approach to automatically update and improve its capabilities according to newly emerging attack patterns. The use of Raspberry Pi as the main platform provides flexibility, cost efficiency, and ease of development. This system integrates various sensors and detection algorithms that are carefully selected to improve accuracy. In addition, this system also improves the detection responsibility for various types of attacks, from attacks on applications to attacks on network infrastructure. Through careful implementation and thorough testing, this IDS is able to provide effective protection for smart home systems from cyber attacks. Its adaptability advantages allow the system to continuously update itself and adapt to new threats, thereby improving overall security. Thus, the design of adaptive IDS on Raspberry Pi as a reinforcement of smart home firewall system is a proactive step in addressing the growing security challenges in a digitally connected smart home environment. This research provides a significant contribution in efforts to improve the security of IoT systems in general.

Keywords: Firewall, IDS, IoT, Raspberry, Smart Home.