Samenvatting
Context: The demand for protection and security of physical spaces and urban areas increased with the escalation of terroristic attacks in recent years. We envision with the proposed cyber–physical systems and spaces, a city that would indeed become a smarter urbanistic object, proactively providing alerts and being protective against any threat. Objectives: This survey intend to provide a systematic multivocal literature survey comprised of an updated, comprehensive and timely overview of state of the art in counter-terrorism cyber–physical systems, hence aimed at the protection of cyber–physical spaces. Hence, provide guidelines to law enforcement agencies and practitioners providing a description of technologies and best practices for the protection of public spaces. Methods: We analyzed 112 papers collected from different online sources, both from the academic field and from websites and blogs ranging from 2004 till mid-2022. Results: (a) There is no one single bullet-proof solution available for the protection of public spaces. (b) From our analysis we found three major active fields for the protection of public spaces: Information Technologies, Architectural approaches, Organizational field. (c) While the academic suggest best practices and methodologies for the protection of urban areas, the market did not provide any type of implementation of such suggested approaches, which shows a lack of fertilization between academia and industry. Conclusion: The overall analysis has led us to state that there is no one single solution available, conversely, multiple methods and techniques can be put in place to guarantee safety and security in public spaces. The techniques range from architectural design to rethink the design of public spaces keeping security into account in continuity, to emerging technologies such as AI and predictive surveillance.
Originele taal-2 | Engels |
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Artikelnummer | 107260 |
Aantal pagina's | 20 |
Tijdschrift | Information and Software Technology |
Volume | 161 |
DOI's | |
Status | Gepubliceerd - sep. 2023 |
Bibliografische nota
Funding Information:The work is supported by the EU H2020 framework programme, grant “ANITA” under Grant No.: 787061 and grant “ PRoTECT ” under Grant No. : 815356 . The work of Francesco Leotta and Massimo Mecella is partially supported by projects SERICS (PE00000014) and FAIR (PE0000013) under the NRRP MUR program funded by the EU - NextGenerationEU . Moreover, the authors thank the students Kaspar Raijmann, Vincent Fokker, and Thomas Meulenbroek from The Jheronimus Academy of Data Science (Netherlands) for the effort and support in analyzing, reading, and coding some of the documents and papers for this Systematic Literature Review.