Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives

Yassine Himeur; Shahab Saquib Sohail; Faycal Bensaali; Abbes Amira; Mamoun Alazab

doi:10.1016/j.cose.2022.102746

Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives

Yassine Himeur, Shahab Saquib Sohail, Faycal Bensaali, Abbes Amira, Mamoun Alazab

Research output: Contribution to journal › Review article › peer-review

81 Citations (Scopus)

Abstract

With the widespread use of Internet of things (IoT), mobile phones, connected devices and artificial intelligence (AI), recommender systems (RSs) have become a booming technology because of their capability to analyze big data and shape users’ habits through well-designed, contextual, and engaging recommendations. Novel generations of RSs have been developed based on the latest AI and machine learning (ML) technologies such as big data RSs, ML-based RSs, explainable RSs, fusion-based RSs, etc. However, the characteristics of modern RSs raise new security and privacy issues because of the sensitivity of users’ data and its vulnerability to being illegally accessed. Moreover, there is a lack of thorough reviews that explain the current privacy and security challenges in RSs and where the actual research is heading. To overcome these issues, this paper sheds light on the existing security and privacy concerns in modern RSs. It provides a comprehensive survey of recent research efforts on security and privacy preservation in RSs. Typically, the security and privacy aspects in advanced RSs and the latest contributions are first discussed based on a well-defined taxonomy. Next, the applications of secure and privacy-preserving RSs are studied. Moving forward, a critical analysis is conducted to (i) highlight the merits and drawbacks of existing frameworks and (ii) draw the essential findings. Lastly, future directions that attract significant research and development attention are explained.

Original language	English
Article number	102746
Pages (from-to)	1-28
Number of pages	28
Journal	Computers and Security
Volume	118
DOIs	https://doi.org/10.1016/j.cose.2022.102746
Publication status	Published - Jul 2022

Bibliographical note

Funding Information:
This paper was made possible by National Priorities Research Program (NPRP ) grant no. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Publisher Copyright:
© 2022

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10.1016/j.cose.2022.102746

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title = "Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives",

abstract = "With the widespread use of Internet of things (IoT), mobile phones, connected devices and artificial intelligence (AI), recommender systems (RSs) have become a booming technology because of their capability to analyze big data and shape users{\textquoteright} habits through well-designed, contextual, and engaging recommendations. Novel generations of RSs have been developed based on the latest AI and machine learning (ML) technologies such as big data RSs, ML-based RSs, explainable RSs, fusion-based RSs, etc. However, the characteristics of modern RSs raise new security and privacy issues because of the sensitivity of users{\textquoteright} data and its vulnerability to being illegally accessed. Moreover, there is a lack of thorough reviews that explain the current privacy and security challenges in RSs and where the actual research is heading. To overcome these issues, this paper sheds light on the existing security and privacy concerns in modern RSs. It provides a comprehensive survey of recent research efforts on security and privacy preservation in RSs. Typically, the security and privacy aspects in advanced RSs and the latest contributions are first discussed based on a well-defined taxonomy. Next, the applications of secure and privacy-preserving RSs are studied. Moving forward, a critical analysis is conducted to (i) highlight the merits and drawbacks of existing frameworks and (ii) draw the essential findings. Lastly, future directions that attract significant research and development attention are explained.",

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AU - Amira, Abbes

AU - Alazab, Mamoun

N1 - Funding Information: This paper was made possible by National Priorities Research Program (NPRP ) grant no. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Publisher Copyright: © 2022

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Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives

Abstract

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