A temporal correlation attack is a type of privacy attack where an adversary analyzes the timing relationships between events to deduce sensitive information. By observing the temporal patterns of transactions or communications, an attacker can link seemingly unrelated activities or identify the true source or destination of data. This attack does not require content inspection but relies solely on metadata and timing. It exploits the sequential nature of data flows.
Context
In blockchain systems, temporal correlation attacks pose a threat to user privacy, particularly for networks aiming for transactional anonymity. News reports might discuss how such attacks can be used to deanonymize users by correlating the timing of on-chain transactions with off-chain events or network traffic. Mitigating these attacks often involves introducing artificial delays or mixing mechanisms to obscure timing patterns.
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