Skip to main navigation Skip to search Skip to main content

Scaling IoT MUD Enforcement using Programmable Data Planes

  • S. A. Harish*
  • , Suvrima Datta
  • , Hemanth Kothapalli
  • , Praveen Tammana
  • , Achmad Basuki
  • , Kotaro Kataoka
  • , Selvakumar Manickam
  • , U. Venkanna
  • , Yung Wey Chong
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of IEEE/IFIP Network Operations and Management Symposium 2023, NOMS 2023
EditorsKemal Akkaya, Olivier Festor, Carol Fung, Mohammad Ashiqur Rahman, Lisandro Zambenedetti Granville, Carlos Raniery Paula dos Santos
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665477161
DOIs
Publication statusPublished - 2023
Event36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023 - Miami, United States
Duration: 8 May 202312 May 2023

Publication series

NameProceedings of IEEE/IFIP Network Operations and Management Symposium 2023, NOMS 2023

Conference

Conference36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023
Country/TerritoryUnited States
CityMiami
Period8/05/2312/05/23

Fingerprint

Dive into the research topics of 'Scaling IoT MUD Enforcement using Programmable Data Planes'. Together they form a unique fingerprint.

Cite this