Collusion-resistant Worker Selection in Social Crowdsensing Systems

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Niazi Torshiz Masood; Amintoosi Haleh

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Journal Paper

Paper Information

Journal: JOURNAL OF COMPUTER AND KNOWLEDGE ENGINEERING Year:2018 | Volume:1 | Issue:1 Page(s): 9-20

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Title

Collusion-resistant Worker Selection in Social Crowdsensing Systems

Author(s)

Niazi Torshiz Masood | Amintoosi Haleh | Issue Writer Certificate

Keywords

worker selection

collusion

data quality

Abstract

The main idea behind social crowdsensing is to leverage social friends as crowdworkers to participate in crowdsensing tasks. A main challenge, however, is the identification and recruitment of well-suited workers. This becomes especially more challenging for large-scale online social networks with potential sparseness of the friendship network which may result in recruiting participants who are not in direct friendship relations with the requester. Such recruitment may increase the possibility of collusion among participants, thus threatening the application security and affecting data quality. In this paper, we propose a collusionresistant worker selection method which aims to prevent the selection of colluders as suitable participants. For each participant who is considered to be selected as suitable, the proposed method is aimed to prevent any possible collusion. To do so, it determines whether the selection of a new participant may result in the formation of a colluding group among the selected participants. This has been achieved through leveraging the Frequent Itemset Mining technique and defining a set of collusion behavioral indicators. Simulation results demonstrate the efficacy of our proposed collusion prevention method in terms of selecting efficient collusion indicators and detecting the colluding groups.

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APA: Copy

Niazi Torshiz, Masood, & Amintoosi, Haleh. (2018). Collusion-resistant Worker Selection in Social Crowdsensing Systems. JOURNAL OF COMPUTER AND KNOWLEDGE ENGINEERING, 1(1), 9-20. SID. https://sid.ir/paper/353628/en

Vancouver: Copy

Niazi Torshiz Masood, Amintoosi Haleh. Collusion-resistant Worker Selection in Social Crowdsensing Systems. JOURNAL OF COMPUTER AND KNOWLEDGE ENGINEERING[Internet]. 2018;1(1):9-20. Available from: https://sid.ir/paper/353628/en

IEEE: Copy

Masood Niazi Torshiz, and Haleh Amintoosi, “Collusion-resistant Worker Selection in Social Crowdsensing Systems,” JOURNAL OF COMPUTER AND KNOWLEDGE ENGINEERING, vol. 1, no. 1, pp. 9–20, 2018, [Online]. Available: https://sid.ir/paper/353628/en

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