MAAT: Multi-Stage Attack Attribution in Enterprise Systems using Software Defined Networks

Abstract

Multi-layer distributed systems, such as those found in corporate systems, are often the target of multi- stage attacks. Such attacks utilize multiple victim machines, in a series, to compromise a target asset deep inside the corporate network. Under such attacks, it is difficult to identify the upstream attacker’s identity from a downstream victim machine because of the mixing of multiple network flows. This is known as the attribution problem in security domains. We present MAAT, a system that solves such attribution problems for multi-stage attacks. It does this by using moving target defense, ie, shuffling the assignment of clients to server replicas, which is achieved through software defined networking. As alerts are generated, MAAT maintains state about the level of risk for each network flow and progressively isolates the malicious flows. Using a simulation, we show that MAAT can identify single and multiple attackers in a variety of systems with different numbers of servers, layers, and clients.