Malware Clustering System using Moth-Flame Optimization as IoT Security Strengthening

Abstract

IoT has become a magnet in today’s cyber world. In the past, household devices were still operated manually, but now they can connect to the internet. The advantage is that house residents can easily monitor and control their devices. With so many IoT devices, it will be more attractive for hackers to take them. There are lots of valuable assets on IoT devices that must be secured. One of them is data from these IoT devices. IoT hardware limitations are the main problem when carrying out a comprehensive data security process. The high computational load to perform this task cannot be adequately accommodated by IoT devices. Through this paper, we propose a clustering system based on the moth flame optimization algorithm to ease the performance of IoT hardware in securing each data. This method is efficient enough to reduce the computational load handled by the RAM and IoT processor. It is open to further improvement to get an end-to-end IoT security system and low computing load.