This paper presents a survey of attack and defense techniques for reputation systems. Reputation systems are designed to provide a metric encapsulating reputation for a given domain for each identity within the system. These systems aim to generate accurate assessments despite various factors, including large community sizes and potentially adversarial environments. The paper focuses on attacks and defense mechanisms in reputation systems, presenting an analysis framework that allows for the general decomposition of existing reputation systems. Attacks are classified based on the system components and design choices targeted by attacks. Defense mechanisms employed by existing reputation systems are surveyed, and several landmark systems in the peer-to-peer domain are analyzed, characterizing their strengths and weaknesses. The paper contributes to understanding which design components of reputation systems are most vulnerable, what the most appropriate defense mechanisms are, and how these defense mechanisms can be integrated into existing or future reputation systems to make them resilient to attacks. The paper discusses the fundamental dimensions of reputation systems: formulation, calculation, and dissemination. Formulation refers to the mathematical underpinnings of the reputation metric and the sources of input to that formulation. Calculation refers to the algorithm used to compute the reputation metric based on constraints. Dissemination refers to the mechanism that allows system participants to obtain the reputation metrics. The paper also discusses the different types of attacks on reputation systems, including self-promoting, whitewashing, slandering, orchestrated, and denial of service attacks. These attacks target different components of the reputation system, such as the formulation, calculation, and dissemination dimensions. The paper also discusses defense strategies against these attacks, including techniques to prevent false feedback, detect colluders, and ensure the resilience of the reputation system. The paper concludes with a discussion of the challenges and future directions for research in reputation systems.This paper presents a survey of attack and defense techniques for reputation systems. Reputation systems are designed to provide a metric encapsulating reputation for a given domain for each identity within the system. These systems aim to generate accurate assessments despite various factors, including large community sizes and potentially adversarial environments. The paper focuses on attacks and defense mechanisms in reputation systems, presenting an analysis framework that allows for the general decomposition of existing reputation systems. Attacks are classified based on the system components and design choices targeted by attacks. Defense mechanisms employed by existing reputation systems are surveyed, and several landmark systems in the peer-to-peer domain are analyzed, characterizing their strengths and weaknesses. The paper contributes to understanding which design components of reputation systems are most vulnerable, what the most appropriate defense mechanisms are, and how these defense mechanisms can be integrated into existing or future reputation systems to make them resilient to attacks. The paper discusses the fundamental dimensions of reputation systems: formulation, calculation, and dissemination. Formulation refers to the mathematical underpinnings of the reputation metric and the sources of input to that formulation. Calculation refers to the algorithm used to compute the reputation metric based on constraints. Dissemination refers to the mechanism that allows system participants to obtain the reputation metrics. The paper also discusses the different types of attacks on reputation systems, including self-promoting, whitewashing, slandering, orchestrated, and denial of service attacks. These attacks target different components of the reputation system, such as the formulation, calculation, and dissemination dimensions. The paper also discusses defense strategies against these attacks, including techniques to prevent false feedback, detect colluders, and ensure the resilience of the reputation system. The paper concludes with a discussion of the challenges and future directions for research in reputation systems.