Scaling IoT MUD Enforcement using Programmable Data Planes

TLDR: In this paper , the authors propose a scalable data plane primitive and a system on top of the primitive, which together enforce MUD profiles of thousands of IoT devices in a P4 programmable switch data plane.

Abstract: IoT-based intrusions and network attacks are becoming ever more concerning. As a mitigatory measure, the IETF standardized Manufacturer Usage Description (MUD) which allows IoT device vendors to specify the legitimate communication patterns (as a MUD profile) of an IoT device. A MUD profile allows the validation of the actual communication pattern of an IoT device with the intended behavior at runtime. However, as the number of IoT devices increases, validation at runtime has scalability challenges in terms of the number of switch resources (e.g., TCAM) required to maintain MUD profiles.In this work, we propose a scalable data plane primitive and a system on top of the primitive, which together enforce MUD profiles of thousands of IoT devices in a P4 programmable switch data plane. Our main idea is to avoid inefficiencies because of the repetition of header values while representing MUD profile-based ACL rules. Further, we exploit the characteristics of header values in ACL rules of real IoT devices and carefully partition the rules across multiple hash-based exact match-action tables in the switch data plane. Since hash-based data structures can be implemented using SRAM which is cheap and abundantly available (order of MBs) in commodity programmable switches, our approach scales well for a large IoT network.