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Leading language model (LM) providers like OpenAI and Anthropic allow customers to fine-tune frontier LMs for specific use cases. To prevent abuse, these providers apply filters to block fine-tuning on overtly harmful data. In this setting,…
Wash trading in decentralized markets remains a significant concern magnified by the pseudonymous and public nature of blockchains. In this paper we introduce an innovative methodology designed to detect wash trading activities beyond…
This paper considers two investors who perform mean-variance portfolio selection with asymmetric information: one knows the true stock dynamics, while the other has to infer the true dynamics from observed stock evolution. Their portfolio…
The transaction ordering dependency of the smart contracts building decentralized exchanges (DEXes) allow for predatory trading strategies. In particular, front-running attacks present a constant risk for traders on DEXes. Whereas legal…
Financial markets populated by human traders often exhibit "market impact", where the traders' quote-prices move in the direction of anticipated change, before any transaction has taken place, as an immediate reaction to the arrival of a…
Predatory pricing -- where a firm strategically lowers prices to undermine competitors -- is a contentious topic in dynamic oligopoly theory, with scholars debating practical relevance and the existence of predatory equilibria. Although…
This paper presents ESCAPE, an informed moving target defense mechanism for cloud containers. ESCAPE models the interaction between attackers and their target containers as a "predator searching for a prey" search game. Live migration of…
With the digitalization of the financial market, dealers are increasingly handling market-making activities by algorithms. Recent antitrust literature raises concerns on collusion caused by artificial intelligence. This paper studies the…
We study a security threat to adversarial multi-armed bandits, in which an attacker perturbs the loss or reward signal to control the behavior of the victim bandit player. We show that the attacker is able to mislead any no-regret…
Advanced Persistent Threats (APTs) represent sophisticated cyberattacks characterized by their ability to remain undetected within the victim system for extended periods, aiming to exfiltrate sensitive data or disrupt operations. Existing…
Cryptocurrency miners have great latitude in deciding which transactions they accept, including their own, and the order in which they accept them. Ethereum miners in particular use this flexibility to collect MEV-Miner Extractable Value-by…
The interactions between a large population of high-frequency traders (HFTs) and a large trader (LT) who executes a certain amount of assets at discrete time points are studied. HFTs are faster in the sense that they trade continuously and…
Transparency and security are both central to Responsible AI, but they may conflict in adversarial settings. We investigate the strategic effect of transparency for agents through the lens of transferable adversarial example attacks. In…
Recent advances in adversarial machine learning have shown that defenses considered to be robust are actually susceptible to adversarial attacks which are specifically customized to target their weaknesses. These defenses include Barrage of…
We investigate the adversarial bandit problem with multiple plays under semi-bandit feedback. We introduce a highly efficient algorithm that asymptotically achieves the performance of the best switching $m$-arm strategy with minimax optimal…
Ethereum prospered the inception of a plethora of smart contract applications, ranging from gambling games to decentralized finance. However, Ethereum is also considered a highly adversarial environment, where vulnerable smart contracts…
The advent of Ethereum 2.0 has introduced significant changes, particularly the shift to Proof-of-Stake consensus. This change presents new opportunities and challenges for arbitrage. Amidst these changes, we introduce BriDe Arbitrager, a…
We propose a model for games in which the players have shared access to a blockchain that allows them to deploy smart contracts to act on their behalf. This changes fundamental game-theoretic assumptions about rationality since a contract…
Maximal Extractable Value (MEV) refers to a class of attacks to decentralized applications where the adversary profits by manipulating the ordering, inclusion, or exclusion of transactions in a blockchain. Decentralized Finance (DeFi)…
Auto-deleveraging (ADL) mechanisms are a critical yet understudied component of risk management on cryptocurrency futures exchanges. When available margin and other loss-absorbing resources are insufficient to cover losses following large…