Srivatsan Sridhar (Stanford University), Onur Ascigil (Lancaster University), Navin Keizer (University College London), François Genon (UCLouvain), Sébastien Pierre (UCLouvain), Yiannis Psaras (Protocol Labs), Etienne Riviere (UCLouvain), Michał Król (City, University of London)

The InterPlanetary File System (IPFS) is currently the largest decentralized storage solution in operation, with thousands of active participants and millions of daily content transfers. IPFS is used as remote data storage for numerous blockchain-based smart contracts, Non-Fungible Tokens (NFT), and decentralized applications.

We present a content censorship attack that can be executed with minimal effort and cost, and that prevents the retrieval of any chosen content in the IPFS network. The attack exploits a conceptual issue in a core component of IPFS, the Kademlia Distributed Hash Table (DHT), which is used to resolve content IDs to peer addresses. We provide efficient detection and mitigation mechanisms for this vulnerability. Our mechanisms achieve a 99.6% detection rate and mitigate 100% of the detected attacks with minimal signaling and computational overhead. We followed responsible disclosure procedures, and our countermeasures are scheduled for deployment in the future versions of IPFS.

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COSPAS Search and Rescue Satellite Uplink: A MAC-Based Security...

Syed Khandker (New York University Abu Dhabi), Krzysztof Jurczok (Amateur Radio Operator), Christina Pöpper (New York University Abu Dhabi)

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Heterogeneous Graph Pre-training Based Model for Secure and Efficient...

Xurui Li (Fudan University), Xin Shan (Bank of Shanghai), Wenhao Yin (Shanghai Saic Finance Co., Ltd)

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On Precisely Detecting Censorship Circumvention in Real-World Networks

Ryan Wails (Georgetown University, U.S. Naval Research Laboratory), George Arnold Sullivan (University of California, San Diego), Micah Sherr (Georgetown University), Rob Jansen (U.S. Naval Research Laboratory)

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Towards Automated Regulation Analysis for Effective Privacy Compliance

Sunil Manandhar (IBM T.J. Watson Research Center), Kapil Singh (IBM T.J. Watson Research Center), Adwait Nadkarni (William & Mary)

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