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  4. Designing secure AI-based systems: a multi-vocal literature review
 
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Designing secure AI-based systems: a multi-vocal literature review

Publikationstyp
Conference Paper
Date Issued
2024-10
Sprache
English
Author(s)
Schneider, Simon Malte  
Software Security E-22  
Saha, Ananya  
Mezzi, Emanuele
Tuma, Katja  
Scandariato, Riccardo  
Software Security E-22  
TORE-URI
https://hdl.handle.net/11420/52452
Start Page
13
End Page
19
Citation
IEEE Secure Development Conference, SecDev 2024
Contribution to Conference
IEEE Secure Development Conference, SecDev 2024  
Publisher DOI
10.1109/SecDev61143.2024.00007
Scopus ID
2-s2.0-85210597108
Publisher
IEEE
ISBN
979-8-3503-4248-2
AI-based systems leverage recent advances in the field of AI/ML by combining traditional software systems with AI components. Applications are increasingly being developed in this way. Software engineers can usually rely on a plethora of supporting information on how to use and implement any given technology. For AI-based systems, however, such information is scarce. Specifically, guidance on how to securely design the architecture is not available to the extent as for other systems.We present 16 architectural security guidelines for the design of AI-based systems that were curated via a multi-vocal literature review. The guidelines could support practitioners with actionable advice on the secure development of AI-based systems. Further, we mapped the guidelines to typical components of AI-based systems and observed a high coverage where 6 out of 8 generic components have at least one guideline associated to them.
Subjects
AI | guidelines | security | software architecture
DDC Class
004: Computer Sciences
Funding(s)
Cybersecurity for AI-Augmented Systems  
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