Abstract. Online tracking of users is used for benign goals, such as detecting fraudulent logins, but also to invade user privacy. We posit that for non-oppressed users, tracking within one website does not have a substantial negative impact on privacy, while it enables legitimate benefits. In contrast, cross-domain tracking negatively impacts user privacy, while being of little benefit to the user. Existing methods to counter fingerprint-based tracking treat cross-domain tracking and regular tracking the same. This often results in hampering or disabling desired functionality, such as embedded videos. By distinguishing between regular and cross-domain tracking, more desired functionality can be preserved. We have developed a prototype tool, FPBlock, that counters cross-domain fingerprint-based tracking while still allowing regular tracking. FP-Block ensures that any embedded party will see a different, unrelatable fingerprint for each site on which it is embedded. Thus, the user's fingerprint can no longer be tracked across the web, while desired functionality is better preserved compared to existing methods.
Decentralized exchanges (DEXs) allow parties to participate in financial markets while retaining full custody of their funds. However, the transparency of blockchain-based DEX in combination with the latency for transactions to be processed, makes market-manipulation feasible. For instance, adversaries could perform front-running -the practice of exploiting (typically non-public) information that may change the price of an asset for financial gain.In this work we formalize, analytically exposit and empirically evaluate an augmented variant of frontrunning: sandwich attacks, which involve front-and back-running victim transactions on a blockchain-based DEX. We quantify the probability of an adversarial trader being able to undertake the attack, based on the relative positioning of a transaction within a blockchain block. We find that a single adversarial trader can earn a daily revenue of over several thousand USD when performing sandwich attacks on one particular DEX -Uniswap, an exchange with over 5M USD daily trading volume by June 2020. In addition to a single-adversary game, we simulate the outcome of sandwich attacks under multiple competing adversaries, to account for the real-world trading environment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.