A survey on vulnerable attacks in online social networks

Nalinipriya, G.; Asswini, M.

doi:10.1109/iciict.2015.7396102

Cited by 14 publications

(5 citation statements)

References 16 publications

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“…In Sybil attacks, the attackers or intruders use fake identities to degrade the performance of crowdsourcing systems. The conventional Sybil detection approaches use additional features, community detection, and metadata [46,47]. However, Sybil detection methods proposed for crowdsourcing primarily use the workers' clustering and gold tasks [43,48,49].…”

Section: Adversarial Attacks In Crowdsourcingmentioning

confidence: 99%

Classifying Workers for Mitigating Adversarial Attacks in Crowdsourcing

First,

Second

2023

Preprint

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Crowdsourcing is adopted as a fast and cost-effective system for human computation and acquiring data for training models in machine learning. Although crowdsourcing has broad applicability, it still has the following challenges. Normally, workers have access to crowdsourcing platforms with simple authentication mechanisms. As a result, malicious workers may get into the system and submit unreliable answers rendering the platform fraudulent. Moreover, when workers perform tasks, their lack of expertise and the difficulty of tasks affects the accuracy. Truth inference benefits the data quality and worker reliability. A truth inference algorithm estimates workers' trustworthiness and correctness of the answers from their responses. Besides, it helps in filtering out low-quality answers. However, due to adversarial attacks by malicious workers, ground truth inference algorithms perform poorly. This research considers how to defend against adversarial attacks on crowdsourcing platforms and improve the truth inference process. The proposed method estimates the trust and reliability scores of the workers and classifies them as normal and malicious workers. Based on this classification , tasks are assigned to the workers. Moreover, these predicted scores are used for inferring the correct answers, thereby improving the ground truth inference. Experiments consistently show that the proposed truth inference method is tolerant to adversarial attacks with competent accuracy.

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Section: Adversarial Attacks In Crowdsourcingmentioning

confidence: 99%

Classifying Workers for Mitigating Adversarial Attacks in Crowdsourcing

First,

Second

2023

Preprint

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“…Reports have shown that shared information on OSNs can reveal contents that are meant to be private and sensitive enough not to be published since malicious users can use them to invade individual's privacy [21][22][23]. Both security and privacy concerns have been highlighted as a major challenge with OSNs in the literature since they are built on the centralized architectural philosophy [24][25]. Efforts are rife in literature with the aim of logically decentralizing the functionalities of OSNs and mitigate privacy issues.…”

Section: State-of-the-art In Online Social Network Sensitive Data Promentioning

confidence: 99%

Towards an Architecture-based Ensemble Methods for Online Social Network Sensitive Data Privacy Protection

Idepefo

Akhigbe

Aderibigbe

et al. 2021

Int. J. Recent Contrib. Eng. Sci. IT

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Abstract - In 2014, the world woke up to a giant data breach that leveraged users’ personal information that was taken from one of the world’s biggest social network platform. Based on the literature, this was possible because of the Centralised Architectural-based Approach to protecting the privacy of users’ online data. Although the literature is inundated with decentralized approaches, there is none to the best of our knowledge that uses an ensemble of methods and draws on a consensus mechanism to address the challenges caused by the Centralised Architectural-based Approach. This paper presents a decentralized approach that adopts and adapts an ensemble of methods. These methods include cryptographic, hashing, and the plenum byzantine fault tolerance algorithms that present a consensus platform, protocol, and mechanism to use the technology of blockchain in a novel manner as a significant contribution. This paper adopts the descriptive approach in its presentation as the usable implementation of the presented proposal is near completion with issues of computational overhead addressed based on preliminary results that show promise of being able to support agreement up to ≈ 75% in terms of making changes by participants in the chain.

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“…has seen the emergence of personal data markets [50] where these personal data may be used directly by the providers or sold to third parties to be used for personalized advertising, increased band awareness, emotional manipulation [51,52] as well as online activity surveillance [53][54][55]. Network-related vulnerabilities such as Sybil attacks [56], social spamming [57] and general cyberattacks on online services [58] may also occur.…”

Section: Security and Privacy Concernsmentioning

confidence: 99%

Peer-to-Peer-Based Social Networks: A Comprehensive Survey

Masinde

Graffi

2020

SN COMPUT. SCI.

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The use of online social networks, such as Facebook and Twitter, has grown at a phenomenal rate. These platforms offer services that support interactions via messaging, chatting or audio/video conferencing, and also sharing of content. Most, if not all, of these platforms use centralized computing systems; therefore, the control and management of the systems lies entirely in the hands of one provider, who must be trusted to treat the data and communication traces securely. As a zero-trust alternative, peer-to-peer (P2P) technologies promise to support end-to-end communication, uncompromising access control, anonymity and resilience against censorship and massive data leaks through misused trust. The goals of this survey are threefold. First, the survey elaborates the properties of P2P-based online social networks and defines the requirements for such (zero-trust) platforms. Second, it gives an exposition of the building blocks for P2P frameworks that allow the creation of such sophisticated and demanding applications, such as user/identity management, reliable data storage, secure communication, access control and general-purpose extensibility, which are not properly addressed in other P2P surveys. As a third point, it gives a comprehensive analysis of proposed P2P-based online social network applications, frameworks and architectures by exploring the technical details, inter-dependencies and maturity of these solutions.

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A survey on vulnerable attacks in online social networks

Cited by 14 publications

References 16 publications

Classifying Workers for Mitigating Adversarial Attacks in Crowdsourcing

Classifying Workers for Mitigating Adversarial Attacks in Crowdsourcing

Towards an Architecture-based Ensemble Methods for Online Social Network Sensitive Data Privacy Protection

Peer-to-Peer-Based Social Networks: A Comprehensive Survey

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