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      A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

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          Abstract

          This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            Evaluating collaborative filtering recommender systems

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              A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                03 August 2021
                August 2021
                : 21
                : 15
                : 5248
                Affiliations
                [1 ]ITTI Sp. z o.o., Rubież 46, 61-612 Poznań, Poland; mpawlicki@ 123456itti.com.pl (M.P.); rkozik@ 123456itti.com.pl (R.K.)
                [2 ]Institute of Telecommunications and Computer Sciences, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland; Ryszard.Choras@ 123456utp.edu.pl
                Author notes
                [* ]Correspondence: apawlicka@ 123456itti.com.pl
                Author information
                https://orcid.org/0000-0003-4380-014X
                Article
                sensors-21-05248
                10.3390/s21155248
                8347790
                34372489
                a312779a-6c7a-4004-a677-fcc1f5fb131d
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 04 July 2021
                : 29 July 2021
                Categories
                Review

                Biomedical engineering
                recommender systems,collaborative filtering,cybersecurity
                Biomedical engineering
                recommender systems, collaborative filtering, cybersecurity

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