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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LiDAR Spoofing Meets the New-Gen: Capability Improvements, Broken Assumptions,...

Takami Sato (University of California, Irvine), Yuki Hayakawa (Keio University), Ryo Suzuki (Keio University), Yohsuke Shiiki (Keio University), Kentaro Yoshioka (Keio University), Qi Alfred Chen (University of California, Irvine)

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The Dark Side of E-Commerce: Dropshipping Abuse as a...

Arjun Arunasalam (Purdue University), Andrew Chu (University of Chicago), Muslum Ozgur Ozmen (Purdue University), Habiba Farrukh (University of California, Irvine), Z. Berkay Celik (Purdue University)

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LibAFL QEMU: A Library for Fuzzing-oriented Emulation

Romain Malmain (EURECOM), Andrea Fioraldi (EURECOM), Aurelien Francillon (EURECOM)

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Make your IoT environments robust against adversarial machine learning...

Hamed Haddadpajouh (University of Guelph), Ali Dehghantanha (University of Guelph)

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