1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
2. Όλο το Αποθετήριο
3. Ερευνητικές ομάδες

Τύπος:	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Identifying privacy related requirements for the design of self-adaptive privacy protections schemes in social networks
Συγγραφέας:	[EL] Κίτσιου, Αγγελική[EN] Kitsiou, Angeliki [EL] Τζωρτζάκη, Ελένη[EN] Tzortzaki, Eleni [EL] Καλλονιάτης, Χρήστος[EN] Kalloniatis, Christos [EL] Γκρίτζαλης, Στέφανος[EN] Gritzalis, Stefanos
Ημερομηνία:	21/01/2021
Περίληψη:	Social Networks (SNs) bring new types of privacy risks threats for users; which developers should be aware of when designing respective services. Aiming at safeguarding users’ privacy more effectively within SNs, self-adaptive privacy preserving schemes have been developed, considered the importance of users’ social and technological context and specific privacy criteria that should be satisfied. However, under the current self-adaptive privacy approaches, the examination of users’ social landscape interrelated with their privacy perceptions and practices, is not thoroughly considered, especially as far as users’ social attributes concern. This study, aimed at elaborating this examination in depth, in order as to identify the users’ social characteristics and privacy perceptions that can affect self-adaptive privacy design, as well as to indicate self-adaptive privacy related requirements that should be satisfied for users’ protection in SNs. The study was based on an interdisciplinary research instrument, adopting constructs and metrics from both sociological and privacy literature. The results of the survey lead to a pilot taxonomic analysis for self-adaptive privacy within SNs and to the proposal of specific privacy related requirements that should be considered for this domain. For further establishing of our interdisciplinary approach, a case study scenario was formulated, which underlines the importance of the identified self-adaptive privacy related requirements. In this regard, the study provides further insight for the development of the behavioral models that will enhance the optimal design of self-adaptive privacy preserving schemes in SNs, as well as designers to support the principle of PbD from a technical perspective.
Γλώσσα:	Αγγλικά
Σελίδες:	24
DOI:	10.3390/fi13020023
EISSN:	1999-5903
Θεματική κατηγορία:	[EL] Μηχανική και Τεχνολογίες, άλλοι τομείς[EN] Engineering and Technologies, miscellaneous
Λέξεις-κλειδιά:	privacy; social networks; self-adaptive privacy; privacy related requirements; users’ social landscape
Κάτοχος πνευματικών δικαιωμάτων:	© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Όροι και προϋποθέσεις δικαιωμάτων:	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/).
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://www.mdpi.com/1999-5903/13/2/23
Ηλεκτρονική διεύθυνση περιοδικού:	https://www.mdpi.com/journal/futureinternet
Τίτλος πηγής δημοσίευσης:	Future Internet
Τεύχος:	2
Τόμος:	13
Σελίδες τεκμηρίου (στην πηγή):	Article no 23
Σημειώσεις:	This research is co-financed by Greece and the European Union (European Social FundESF) through the Operational Programme “Human Resources Development, Education and Lifelong Learning 2014–2020” in the context of the project “Adaptive Privacy-aware Cloud-based Systems: Socio-technical requirements” (MIS:5047231)”.
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες