I defended my thesis, Practical Black-Box Analysis for Network Functions and Services, in September 2020 and have joined the Network Infrastructure at Google.

I received my Ph.D. in Electrical and Computer Engineering at Carnegie Mellon University (CMU), advised by Vyas Sekar, and was part of CyLab, CMU’s Security and Privacy Institute. Before starting at CMU in 2014, I earned bachelor’s degree in Electrical Engineering from the University of Waterloo, Canada.

My research interests lie in the intersection of computer networking and network security. My Ph.D. work spanned network modeling, network verification, and uncovering security vulnerabilities in network protocols and devices. My dissertation looked at enabling black-box analysis of network devices and protocols. My dissertation vision was to equip operators and defenders with tools for precisely analyzing and securing networks containing these devices.

My research work has been recognized with the NSA Best Scientific Cybersecurity Paper Award and the CSAW Applied Security Research Prize. I am also the an invited participant at the 2019 EECS Rising Stars workshop.


Dec 2020 : Invited to serve as a program committee member of ACM CCS 2021. Submit your work!

Oct 2020 : We released the website and opensourced the code for our AmpMap project!

Sep 2020 : I have successfully defended my thesis!

Aug 2020 : AmpMap Paper got accepted to USENIX Security 2021. See you in Vancouver next year!

Nov 2019 : Participated the Rising Stars in EECS and gave a talk on Black-Box Approach to Network Security

Sep 2019 : Our Vision Paper accepted to HotNets 19

Aug 2019 : NetSMC paper accepted to NSDI 20

July 2019 : Honored to be selected as one of the 2019 Rising Stars in EECS [Link]

Mar 2019 : Presented Alembic in NSDI 19 [Link]


Conference and Workshop Papers

  1. Accurately Measuring Global Risk of Amplification Attacks using AmpMap
    Soo-Jin Moon, Yucheng Yin, Rahul Anand Sharma, Yifei Yuan, Jonathan M. Spring, Vyas Sekar
    To appear in USENIX Security, 2021
    [Paper] [Website][Code]

  2. NetSMC: A Custom Symbolic Model Checker for Stateful Network Verification
    Yifei Yuan, Soo-Jin Moon, Sahil Uppal, Limin Jia, Vyas Sekar
    In Proc. USENIX NSDI, 2020
    [Paper] [Talk Video]

  3. Towards Oblivious Network Analysis using Generative Adversarial Networks
    Zinan Lin, Soo-Jin Moon, Carolina M. Zarate, Ritika Mulagalapalli, Sekar Kulandaivel, Giulia Fanti, Vyas Sekar
    In Proc. HotNets, 2019

  4. Alembic: Automated Model Inference for Stateful Network Functions
    Soo-Jin Moon, Jeffrey Helt, Yifei Yuan, Yves Bieri, Sujata Banerjee, Vyas Sekar, Wenfei Wu, Mihalis Yannakakis, Ying Zhang
    In Proc. USENIX NSDI, 2019
    [Paper] [Slides][Talk Video]

  5. Nomad: Mitigating Arbitrary Cloud Side Channels via Provider-Assisted Migration
    Soo-Jin Moon, Vyas Sekar, Michael K. Reiter
    In Proc. ACM CCS, 2015
    [Paper] [Slides] NSA Best Scientific Cybersecurity Paper Award, 2016 [Link]
    CSAW Best Paper Award (2nd place), 2015 [Link]

Technical Reports

  1. Automatic Discovery of Evasion Attacks Against Stateful Firewalls
    Soo-Jin Moon, Yves Bieri, Ruben Martins, Vyas Sekar
    Technical Report, CMU-CyLab-21-001 2021 [Paper]

  2. Accurately Measuring Global Risk of Amplification Attacks using AmpMap
    Soo-Jin Moon, Yucheng Yin, Rahul Sharma, Yifei Yuan, Jonathan M. Spring, Vyas Sekar
    Technical Report, CMU-CyLab-19-004 2020 [Paper]