Abstract: Count-Min Sketch (CMS) and HeavyKeeper (HK) are two realizations of a compact frequency estimator (CFE). These are a class of probabilistic data structures that maintain a compact summary of (typically) high-volume streaming data, and provide approximately correct estimates of the number of times any particular element has appeared. CFEs are often the base structure
Abstract: With the recent hype around the Metaverse and NFTs, Web3 is getting more and more popular. The goal of Web3 is to decentralize the web via decentralized applications. Wallets play a crucial role as they act as an interface between these applications and the user. Wallets such as MetaMask are being used by millions
Abstract: Chain-key Bitcoin (ckBTC) is a Bitcoin “layer 2” built on top of the Internet Computer blockchain (IC). It enables both individuals as well as IC smart contracts to transact the deposited Bitcoin cheaply and with a much higher throughput compared to the Bitcoin network. Crucially, ckBTC has no additional trust assumptions other than those
Abstract: Since the introduction of Intel SGX nearly a decade ago, the Confidential Computing industry has been growing significantly. In this talk, we’ll look at how secure architectures are being deployed and used today: what underlying primitives are available from hardware vendors, what infrastructure providers are making available, and how to write software using all
Abstract: Mozilla curates a set of root certificate authorities to validate hostnames for TLS in the Firefox browser. Many other software projects, such as Tor Browser and ca-certificates simply follow Mozilla’s list; other entities, such as Apple and Microsoft, make their own decisions for inclusion with considerations for Mozilla’s decisions and the associated public discussion. In March 2023, Mozilla
Abstract: Privacy-preserving machine learning has the potential to balance individuals’ privacy rights and companies’ economic goals. However, such technologies must inspire trust and communicate how they can match the expectations of the subjects of the data. In this talk, I present the breadth of privacy vectors for machine learning and the implications of my work on user perspectives of the
Abstract: Fully Homomorphic Encryption (FHE) is seeing increasing real-world deployment to protect data in use by allowing computation over encrypted data. However, the same malleability that enables homomorphic computations also raises integrity issues, which have so far been mostly overlooked for practical deployments. While FHE’s lack of integrity has obvious implications for correctness, it also has
Abstract: The quantification of privacy risks associated with algorithms is a core issue in data privacy, which holds immense significance for privacy experts, practitioners, and regulators. I will introduce a systematic approach to assessing the privacy risks of machine learning algorithms. I will highlight our efforts towards establishing standardized privacy auditing procedures and privacy meter
Abstract: Modern data centers have grown beyond CPU nodes to provide domain-specific accelerators such as GPUs and FPGAs to their customers. Customers are concerned about protecting their data and are willing to accept certain performance degradation for trusted execution environments (TEEs) like Intel SGX or AMD SEV. However, they face a trade-off between using accelerators
Abstract: In times of armed conflict, the emblems of the red cross, red crescent, and red crystal are used to mark physical infrastructure. This enables military units to identify assets as protected under international humanitarian law to avoid attacks on them. In this talk, we present how we extend such protection to digital, network-connected infrastructure