SocialTrust Colluding Attack on E-commerce Platforms

To detect colluding users in OSNs for a system implementing reputation system. SocialTrust modifies the weight of ratings based on the social distance and interest relationship between peers, which increases the ability of the reputation system to fight against colluding. They also claim that their mechanism can be used in any reputation system for P2P networks.

This attack type involves a group of individuals creating fake accounts and artificially boosting each other's ratings or reviews to manipulate the trustworthiness of their profiles. By artificially inflating their ratings through conspiracy, they can deceive other users into trusting them more than they deserve, potentially leading to fraudulent transactions or other malicious activities. For a clear understanding, three individuals, A, B, and C, conspire to carry out a SocialTrust attack. They create multiple fake accounts on the platform and give each other high ratings and positive reviews, falsely inflating their trustworthiness scores.

Individual A lists a product for sale on the platform and receives high ratings and reviews from individuals B and C, making their profile appear trustworthy. Buyers on the platform see these positive ratings and reviews and are more likely to trust individual A and make a purchase.

However, once the buyer purchases, Individual A never delivers the product and disappears with the buyer's money. The buyers trusted Individual A based on the fake reviews and ratings provided by Individuals B and C, who colluded with Individual A to deceive other users on the platform. This can lead to significant financial losses for the unsuspecting buyers.

This colluding attack on SocialTrust undermines the platform's integrity and deceives users into trusting malicious actors, leading to potential financial losses and significant harm to the community. It calls for collective action to prevent such incidents.

SocialTrust colluding attacks on e-commerce platforms may not be publicly colluding attacks, or similar fraudulent activities have been reported on various platforms, prompting the platforms to take measures to prevent and combat such behavior. This highlights the importance of proactive steps to prevent such attacks.

Some well-known e-commerce platforms where colluding attacks or fraudulent activities have occurred in the past include:

1.eBay: There have been instances of sellers colluding to boost their ratings and artificially deceive buyers on the platform.

2. Amazon: There have been reports of fake reviews and ratings on the platform that were used to manipulate product rankings and deceive customers.

EBay and Amazon have implemented measures to detect and prevent such fraudulent activities, including algorithms to identify suspicious behavior, strict guidelines for reviews and ratings, and mechanisms for users to report suspicious or fraudulent activities. 

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