arXiv subjects

Ceren Kocaoğullar

Publications and source records attributed to Ceren Kocaoğullar.

4 recordsLinked to original sources

arXiv2025

Careful Whisper: Attestation for peer-to-peer Confidential Computing networks

Trusted Execution Environments (TEEs) are designed to protect the privacy and integrity of data in use. They enable secure data processing and sharing in peer-to-peer networks, such as vehicular ad hoc networks of autonomous vehicles, without compromising confidentiality. In these networks, nodes must establish mutual trust to collaborate securely. TEEs can achieve this through remote attestation, where a prover presents evidence of its trustworthiness to a verifier, which then decides whether or not to trust the prover. However, a naive peer-to-peer attestation approach, where every TEE directly attests every other TEE, results in quadratic communication overhead. This is inefficient in dynamic environments, where nodes frequently join and leave the network. To address this, we present Careful Whisper, a gossip-based protocol that disseminates trust efficiently, reducing attestation overhead to linear complexity under ideal conditions. It enables interoperability by enabling transitive trust across heterogeneous networks, and supports trust establishment with offline nodes via relayed attestations. Using a custom discrete-event simulator, we show that Careful Whisper propagates trust both faster and more widely than naive approaches across various network topologies. Our results demonstrate that our protocol is resource efficient, sending ~21.5 KiB and requiring 0.158 seconds per round in a 200-node network, and that our protocol is resilient to attestation failures across various network topologies.

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arXiv2024

A Confidential Computing Transparency Framework for a Comprehensive Trust Chain

Confidential Computing enhances privacy of data in-use through hardware-based Trusted Execution Environments (TEEs) that use attestation to verify their integrity, authenticity, and certain runtime properties, along with those of the binaries they execute. However, TEEs require user trust, as attestation alone cannot guarantee the absence of vulnerabilities or backdoors. Enhanced transparency can mitigate the reliance on naive trust. Some organisations currently employ various transparency measures, including open-source firmware, publishing technical documentation, or undergoing external audits, but these require investments with unclear returns. This may discourage the adoption of transparency, leaving users with limited visibility into system privacy measures. Additionally, the lack of standardisation complicates meaningful comparisons between implementations. To address these challenges, we propose a three-level conceptual framework providing organisations with a practical pathway to incrementally improve Confidential Computing transparency. To evaluate whether our transparency framework contributes to an increase in end-user trust, we conducted an empirical study with over 800 non-expert participants. The results indicate that greater transparency improves user comfort, with participants willing to share various types of personal data across different levels of transparency. The study also reveals misconceptions about transparency, highlighting the need for clear communication and user education.

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arXiv2023

Pudding: Private User Discovery in Anonymity Networks

Anonymity networks allow messaging with metadata privacy, providing better privacy than popular encrypted messaging applications. However, contacting a user on an anonymity network currently requires knowing their public key or similar high-entropy information, as these systems lack a privacy-preserving mechanism for contacting a user via a short, human-readable username. Previous research suggests that this is a barrier to widespread adoption. In this paper we propose Pudding, a novel private user discovery protocol that allows a user to be contacted on an anonymity network knowing only their email address. Our protocol hides contact relationships between users, prevents impersonation, and conceals which usernames are registered on the network. Pudding is Byzantine fault tolerant, remaining available and secure as long as less than one third of servers are crashed, unavailable, or malicious. It can be deployed on Loopix and Nym without changes to the underlying anonymity network protocol, and it supports mobile devices with intermittent network connectivity. We demonstrate the practicality of Pudding with a prototype using the Nym anonymity network. We also formally define the security and privacy goals of our protocol and conduct a thorough analysis to assess its compliance with these definitions.

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arXiv2021

Towards Private On-Chain Algorithmic Trading

While quantitative automation related to trading crypto-assets such as ERC-20 tokens has become relatively commonplace, with services such as 3Commas and Shrimpy offering user-friendly web-driven services for even the average crypto trader, we have not yet seen the emergence of on-chain trading as a phenomenon. We hypothesize that just like decentralized exchanges (DEXes) that by now are by some measures more popular than traditional exchanges, process in the space of decentralized finance (DeFi) may enable attractive online trading automation options. In this paper we present ChainBot, an approach for creating algorithmic trading bots with the help of blockchain technology. We show how to partition the computation into on- and off-chain components in a way that provides a measure of end-to-end integrity, while preserving the algorithmic "secret sauce". Our system is enabled with a careful use of algorithm partitioning, zero-knowledge proofs and smart contracts. We also show that with layer-2 (L2) technologies, trades can be kept private, which means that algorithmic parameters are difficult to recover by a chain observer. Our approach offers more transparent access to liquidity and better censorship-resistance compared to traditional off-chain trading approaches. We develop a sample ChainBot and train it on historical data, resulting in returns that are up to 2.4x the buy-and-hold strategy, which we use as our baseline. Our measurements show that across 1000 runs, the end-to-end average execution time for our system is 48.4 seconds. We demonstrate that the frequency of trading does not significantly affect the rate of return and Sharpe ratio, which indicates that we do not have to trade at every block, thereby significantly saving in terms of gas fees. In our implementation, a user who invests \$1,000 would earn \$105, and spend \$3 on gas; assuming a user pool of 1,000 subscribers.

cs.CR↗