Malware Containment via Firewall Placement in Large Scale Wireless IoT Networks

One of the biggest risks that wireless IoT networks encounter is malware or botnet epidemics. Malware can propagate from one device to another device that exists in its coverage range as long as there are no check points (firewalls) to protect that device. Firewalls can be hardware (special devices) or software licences that can be installed on a limited number of devices. Unfortunately, in both cases the number of firewalls that can be installed in any network is limited due to cost constraints. Therefore, it is mandatory to make efficient use of that available number of firewalls. In this paper we consider two optimization problems to optimize the firewall placement in a massive wireless IoT network. The objective of the first optimization problem is to reduce the number of firewalls required to divide the network into a given number of isolated clusters. The second problem aims at maximizing the number of isolated network clusters that can be achieved given an available number of firewalls. These two clustering problems are non-convex and are known to be NPhard. However, We provide efficient algorithms, with different variations, to solve the two problems, and we compare their performance to the well known K-Means clustering algorithm. Simulation results show that in both problems the average performance of the proposed algorithms outperforms performance of the the K-Means algorithm.