Enhancing and identifying cloning attacks in online social networks

Shan, Zifei; Cao, Haowen; Lv, Jason; Yan, Cong; Liu, Annie

doi:10.1145/2448556.2448615

Cited by 15 publications

(6 citation statements)

References 16 publications

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“…They designed and implemented a prototype which can be employed to investigate whether or not users have fallen victim to clone attacks. In 2013, Shan et al [126] presented the CloneSpotter which can be deployed into the OSN infrastructure and can detect cloning attacks by using users' data records, such as a user's login IP records that are available to the OSN operator.…”

Section: Academic Solutionsmentioning

confidence: 99%

Online Social Networks: Threats and Solutions

Fire¹,

Goldschmidt

Elovici³

2014

IEEE Commun. Surv. Tutorials

270

126

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Many online social network (OSN) users are unaware of the numerous security risks that exist in these networks, including privacy violations, identity theft, and sexual harassment, just to name a few. According to recent studies, OSN users readily expose personal and private details about themselves, such as relationship status, date of birth, school name, email address, phone number, and even home address. This information, if put into the wrong hands, can be used to harm users both in the virtual world and in the real world. These risks become even more severe when the users are children. In this paper we present a thorough review of the different security and privacy risks which threaten the well-being of OSN users in general, and children in particular. In addition, we present an overview of existing solutions that can provide better protection, security, and privacy for OSN users. We also offer simple-to-implement recommendations for OSN users which can improve their security and privacy when using these platforms. Furthermore, we suggest future research directions.Comment: Draft Versio

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Section: Academic Solutionsmentioning

confidence: 99%

Online Social Networks: Threats and Solutions

Fire¹,

Goldschmidt

Elovici³

2014

IEEE Commun. Surv. Tutorials

270

126

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“…For instance, a specific tool was developed in order to determine whether the profiles of social network users have been subject to cloning attack [47]. An approach called CloneSpotter was proposed in order to detect the cloning attack on social network profiles [48]. This approach is based on the analysis of registration data of users available for social network operators.…”

Section: Protection Methods Against Threats In Social Networkmentioning

confidence: 99%

Security Issues in Social Networks

Shikhaliyev¹

2016

JPIS

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Nowadays, a large number of social networks exist in the Internet. These social networks are very popular and play a prominent role in people's life. Alongside, the social networks have also caused the occurrence of new threats in the field of information security. Such threats are related to the distribution of malicious software and spams, attacks on social engineering and social network accounts, tracking, fraud and etc. This article is dedicated to the analysis of existing threats in social networks and the protection issues against them.

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“…Most profile cloning studies utilized the user profiles [91,95,169]. To identify cloned profiles, they calculated profile similarities using various methods based on user profile attributes.…”

Section: A User Profile-based Deception Detection Mechanismsmentioning

confidence: 99%

“…The binary classifier was based on both the profile attributes similarity and friend list similarity. Shan et al [169] simulated profile cloning attacks by snowball sampling and iteration attack and then detected the attackers by a detector called 'ChoneSpotter.' The context-free detection algorithm includes the profile information and friendship connections.…”

Section: A User Profile-based Deception Detection Mechanismsmentioning

confidence: 99%

Online Social Deception and Its Countermeasures: A Survey

et al. 2021

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We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. As a consequence, online social deception (OSD) in SNSs has emerged as a serious threat in cyberspace, particularly for users vulnerable to such cyberattacks. Cyber attackers have exploited the sophisticated features of SNSs to carry out harmful OSD activities, such as financial fraud, privacy threat, or sexual/labor exploitation. Therefore, it is critical to understand OSD and develop effective countermeasures against OSD for building trustworthy SNSs. In this paper, we conduct an extensive survey, covering (i) the multidisciplinary concept of social deception; (ii) types of OSD attacks and their unique characteristics compared to other social network attacks and cybercrimes; (iii) comprehensive defense mechanisms embracing prevention, detection, and response (or mitigation) against OSD attacks along with their pros and cons; (iv) datasets/metrics used for validation and verification; and (v) legal and ethical concerns related to OSD research. Based on this survey, we provide insights into the effectiveness of countermeasures and the lessons learned from the existing literature. We conclude our survey with in-depth discussions on the limitations of the state-of-the-art and suggest future research directions in OSD research.

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Enhancing and identifying cloning attacks in online social networks

Cited by 15 publications

References 16 publications

Online Social Networks: Threats and Solutions

Online Social Networks: Threats and Solutions

Security Issues in Social Networks

Online Social Deception and Its Countermeasures: A Survey

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