arXiv subjects

Christian Killer

Publications and source records attributed to Christian Killer.

5 recordsLinked to original sources

arXiv2025

Acurast: Decentralized Serverless Cloud

Centralized trust is ubiquitous in today's interconnected world, from computational resources to data storage and its underlying infrastructure. The monopolization of cloud computing resembles a feudalistic system, causing a loss of privacy and data ownership. Cloud Computing and the Internet in general face widely recognized challenges, such as (1) the centralization of trust in auxiliary systems (e.g., centralized cloud providers), (2) the seamless and permissionless interoperability of fragmented ecosystems and (2) the effectiveness, verifiability, and confidentiality of the computation. Acurast is a decentralized serverless cloud that addresses all these shortcomings, following the call for a global-scale cloud founded on the principles of the open-source movement. In Acurast, a purpose-built orchestrator, a reputation engine, and an attestation service are enshrined in the consensus layer. Developers can off-load their computations and verify executions cryptographically. Furthermore, Acurast offers a modular execution layer, taking advantage of secure hardware and trusted execution environments, removing the trust required in third parties, and reducing them to cryptographic hardness assumptions. With this modular architecture, Acurast serves as a decentralized and serverless cloud, allowing confidential and verifiable compute backed by the hardware of security and performance mobile devices.

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arXiv2024

Asset-centric Threat Modeling for AI-based Systems

Threat modeling is a popular method to securely develop systems by achieving awareness of potential areas of future damage caused by adversaries. However, threat modeling for systems relying on Artificial Intelligence is still not well explored. While conventional threat modeling methods and tools did not address AI-related threats, research on this amalgamation still lacks solutions capable of guiding and automating the process, as well as providing evidence that the methods hold up in practice. Consequently, this paper presents ThreatFinderAI, an approach and tool providing guidance and automation to model AI-related assets, threats, countermeasures, and quantify residual risks. To evaluate the practicality of the approach, participants were tasked to recreate a threat model developed by cybersecurity experts of an AI-based healthcare platform. Secondly, the approach was used to identify and discuss strategic risks in an LLM-based application through a case study. Overall, the solution's usability was well-perceived and effectively supports threat identification and risk discussion.

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arXiv2024

SoK: Decentralized Finance (DeFi) -- Fundamentals, Taxonomy and Risks

Decentralized Finance (DeFi) refers to financial services that are not necessarily related to crypto-currencies. By employing blockchain for security and integrity, DeFi creates new possibilities that attract retail and institution users, including central banks. Given its novel applications and sophisticated designs, the distinction between DeFi services and understanding the risk involved is often complex. This work systematically presents the major categories of DeFi protocols that cover over 90\% of total value locked (TVL) in DeFi. It establishes a structured methodology to differentiate between DeFi protocols based on their design and architecture. Every DeFi protocol is classified into one of three groups: liquidity pools, pegged and synthetic tokens, and aggregator protocols, followed by risk analysis. In particular, we classify stablecoins, liquid staking tokens, and bridged (wrapped) assets as pegged tokens resembling similar risks. The full risk exposure of DeFi users is derived not only from the DeFi protocol design but also from how it is used and with which tokens.

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arXiv2024

Performance Analysis of Decentralized Physical Infrastructure Networks and Centralized Clouds

The advent of Decentralized Physical Infrastructure Networks (DePIN) represents a shift in the digital infrastructure of today's Internet. While Centralized Service Providers (CSP) monopolize cloud computing, DePINs aim to enhance data sovereignty and confidentiality and increase resilience against a single point of failure. Due to the novelty of the emerging field of DePIN, this work focuses on the potential of DePINs to disrupt traditional centralized architectures by taking advantage of the Internet of Things (IoT) devices and crypto-economic design in combination with blockchains. This combination yields Acurast, a more distributed, resilient, and user-centric physical infrastructure deployment. Through comparative analysis with centralized systems, particularly in serverless computing contexts, this work seeks to lay the first steps in scientifically evaluating DePINs and quantitatively comparing them in terms of efficiency and effectiveness in real-world applications. The findings suggest DePINs' potential to (i) reduce trust assumptions and physically decentralized infrastructure, (ii) increase efficiency and performance simultaneously while improving the computation's (iii) confidentiality and verifiability.

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arXiv2020

Proverum: A Hybrid Public Verifiability and Decentralized Identity Management

Trust in electoral processes is fundamental for democracies. Further, the identity management of citizen data is crucial, because final tallies cannot be guaranteed without the assurance that every final vote was cast by an eligible voter. In order to establish a basis for a hybrid public verifiability of voting, this work (1) introduces Proverum, an approach combining a private environment based on private permissioned Distributed Ledgers with a public environment based on public Blockchains, (2) describes the application of the Proverum architecture to the Swiss Remote Postal Voting system, mitigating threats present in the current system, and (3) addresses successfully the decentralized identity management in a federalistic state.

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