Data poisoning attacks in contextual bandits
WebSep 26, 2024 · Data Poisoning Attacks in Contextual Bandits: 9th International Conference, GameSec 2024, Seattle, WA, USA, October 29–31, 2024, Proceedings … WebMay 16, 2024 · Stochastic multi-armed bandits form a class of online learning problems that have important applications in online recommendation systems, adaptive medical treatment, and many others. Even though potential attacks against these learning algorithms may hijack their behavior, causing catastrophic loss in real-world applications, little is known ...
Data poisoning attacks in contextual bandits
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WebData Poisoning, Backdoor Attacks, and Defenses Micah Goldblum*1, Dimitris Tsipras2, ... Contextual bandits, often used in adaptive medical treatment, can be manipulated by … WebMay 16, 2024 · Data Poisoning Attacks on Stochastic Bandits. Fang Liu, Ness Shroff. Stochastic multi-armed bandits form a class of online learning problems that have …
WebUpload an image to customize your repository’s social media preview. Images should be at least 640×320px (1280×640px for best display). WebDec 1, 2024 · By using a novel contextual multi-armed bandit-based algorithm to balance the accuracy and efficiency, we propose a context-based online big-data-oriented …
Webcontextual bandit. We also investigate the feasibility and the side effects of such attacks, and identify future directions for defense. Experiments on both synthetic and real-world … WebAug 17, 2024 · We study offline data poisoning attacks in contextual bandits, a class of reinforcement learning problems with important applications in online recommendation …
WebFeb 10, 2024 · In this paper, we study several attack scenarios and show that a malicious agent can force a linear contextual bandit algorithm to pull any desired arm T - o (T) …
WebAug 27, 2024 · For example, you can use a contextual bandit to select which news article to show first on the main page of your website to optimize click through rate. The context is information about the user: where they come from, previously visited pages of the site, device information, geolocation, etc. An action is a choice of what news article to display. how many seasons are in canadaWebIn this paper, we study the action poisoning attack against linear contextual bandit in both white-box and black-box settings. In the white-box setting, we assume that the attacker knows the coefficient vectors associated with arms. Thus, at each round, the attacker knows the mean rewards of all arms. While it is often unrealistic to exactly know how did carnegie use vertical integrationWebDepending on the target of the poisoning attacks, the poisoning attacks against contextual linear bandits can be categorized into four types: reward poisoning attack, action poisoning attack, context poisoning attack and the mix of them. In this paper, we aim to investigate the impact of action poisoning attacks on contextual bandit models. how many seasons are in bonesWebWe study offline data poisoning attacks in contextual bandits, a class of reinforcement learning problems with important applications in online recommendation and adaptive medical treatment, among others. We provide a general attack framework … how many seasons are in deadman wonderlandWebData poisoning attacks in contextual bandits. In Conference on Decision and Game Theory for Security (GameSec), 2024. Google Scholar Cross Ref; Ng, Andrew Y., Harada, Daishi, and Russell, Stuart J. Policy invariance under reward transformations: Theory and application to reward shaping. how many seasons are in days of our livesWebWe study offline data poisoning attacks in contextual bandits, a class of reinforcement learning problems with important applications in online recommendation and adaptive … how many seasons are in chuckyWebFeb 10, 2024 · Adversarial Attacks on Linear Contextual Bandits. Contextual bandit algorithms are applied in a wide range of domains, from advertising to recommender … how many seasons are in danmachi