A security approach based on honeypots: Protecting Online Social network from malicious profiles
Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi and, Habiba Chaoui

TL;DR
This paper proposes a security method using social honeypots to detect and analyze malicious profiles in online social networks, enhancing protection against cyber threats and identity breaches.
Contribution
It introduces a novel approach employing social honeypots to identify malicious users and develop classifiers for profile filtering and monitoring.
Findings
Honeypots successfully captured malicious profiles
Characteristics of malicious profiles were analyzed
Classifiers were created to filter malicious users
Abstract
In the recent years, the fast development and the exponential utilization of social networks have prompted an expansion of social Computing. In social networks users are interconnected by edges or links, where Facebook, twitter, LinkedIn are most popular social networks websites. Due to the growing popularity of these sites they serve as a target for cyber criminality and attacks. It is mostly based on how users are using these sites like Twitter and others. Attackers can easily access and gather personal and sensitive users information. Users are less aware and least concerned about the security setting. And they easily become victim of identity breach. To detect malicious users or fake profiles different techniques have been proposed like our approach which is based on the use of social honeypots to discover malicious profiles in it. Inspired by security researchers who used…
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