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    AVOID: Automatic Verification Of Internet Data-paths

    paper:2024_avoid_milcom

    Links to Access
    caida.org/catalog/papers/2024_..._avoid_milcom/avoid_milcom.pdfPDFpublic

    Department of Defense (DOD) use of commercial networks entails unprecedented reliance on untrusted third-party communications infrastructure, and the associated risk of exposing DOD communications to an adversary. Traversing adversary-controlled infrastructure allows DOD’s adversaries to recognize, disrupt, or extract intelligence even from encrypted communications. The resulting arms race of obfuscation vs intelligence techniques is inherently limited: with each new obfuscation, DOD can never know if it fools the adversary, or if the adversary is lulling DOD into a false sense of security.

    We believe the next great capability leap for operating through commercial networks will likely come from sophisticated analytics that provide situational awareness of the threats within the communications infrastructure, and implementations that dynamically route communications along benign paths. These systems will restructure communication paths to avoid adversary-controlled infrastructure in cellular and Internet networks, complementing existing DOD defenses and keeping communications unobservable by the adversary.

    Our demonstration will show results of our vision for this emerging conceptual framework, that we call AVOID. We will demonstrate a phone app that can identify potentially malicious base stations in cellular networks, and automatically connect to benign base stations. We will also demonstrate that the same phone—combined with a topology-aware overlay— can avoid adversary-controlled infrastructure in ISP networks outside the wireless network.

    Date Published

    2024-10

    Authors

    Alexander Marder1

    Jon Larrea2

    kc claffy3

    Erik Kline4

    Kyle Jamieson5

    Bradley Huffaker3

    Lincoln Thurlow4

    Matthew Luckie3

    Publisher

    IEEE Military Communications Conference (MILCOM)

    Organization Affiliated With

    1 John Hopkins University

    2 Revelare Networks

    3 CAIDA, San Diego Supercomputer Center, University of California San Diego

    4 USC/ISI

    5 Princeton University

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