A New Approach to Weakening and Destruction of Malicious Internet Networks

Abstract

Models and algorithms for weakening and destruction of malicious complex internet networks are widely studied in AI in recent years. These algorithms must detect critical links and nodes in a dynamic network whose removals maximally destroy or spoil the network’s functions. In this paper we propose a new approach for solution of this problem. Instead of removal of corresponding key segments of networks we initiate intentional misrepresentation in important sites leading to wrong network evolution that in fact is equivalent to weakening/destruction of the network. Specifically, we cause and study artificial decentralization and artificial fragmentation in the network. For simulation of these phenomena, we apply and develop a network model based on nonuniform random recursive trees, so called one-max constant-probability network.