出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The popularity of IoT smart things is rising, due to the automation theyprovide and its e ects on productivity. However, it has been proven that IoT devicesare vulnerable to both well established and new IoT-speci c attack vectors. In thispaper, we propose the Particle Deep Framework, a new network forensic frameworkfor IoT networks that utilised Particle Swarm Optimisation to tune the hyperparametersof a deep MLP model and improve its performance. The PDF is trainedand validated using Bot-IoT dataset, a contemporary network-trac dataset thatcombines normal IoT and non-IoT trac, with well known botnet-related attacks.Through experimentation, we show that the performance of a deep MLP model isvastly improved, achieving an accuracy of 99.9% and false alarm rate of close to 0%.
关键词：Network forensics; Particle swarm optimization; Deep Learning; IoT;Botnets
