Identifying security-related requirements in regulatory documents based on cross-project classification

Mohamad, Mazen; Steghöfer, Jan-Philipp; Åström, Alexander; Scandariato, Riccardo

doi:10.1145/3558489.3559074

Cited by 3 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Security Requirement Elicitationmentioning

confidence: 99%

“…Conversely, Articles [125] and [26] explore the role of ML in the e cient synthesis and documentation of security requirements. Article [125] introduces a classi er that streamlines the extraction and categorization of security-related requirements from extensive regulatory documents, signi cantly reducing the manual effort required for compliance in regulated sectors such as the automotive industry. Article [26] presents a hybrid approach combining ML and a rule-based expert system to predict security functional requirements and evaluation assurance levels for ICT products based on the Common Criteria (CC) framework.…”

Section: Security Requirement Elicitationmentioning

confidence: 99%

See 1 more Smart Citation

Artificial intelligence for system security assurance: A systematic literature review

Wen,

Shukla,

Katt

2024

Preprint

View full text Add to dashboard Cite

System Security Assurance (SSA) has emerged as a critical methodology for organizations to verify the trustworthiness of their systems by evaluating security measures against industry standards, legal requirements, and best practices to identify any weakness and demonstrate compliance. In recent years, the role of Artificial Intelligence (AI) in enhancing cybersecurity has received increased attention, with an increasing number of literature reviews highlighting its diverse applications. However, there remains a significant gap in comprehensive reviews that specifically address the integration of AI within SSA frameworks. This systematic literature review seeks to fill this research gap by assessing the current state of AI in SSA, identifying key areas where AI contributes to improve SSA processes, highlighting the limitations of current methodologies, and providing the guidance for future advancements in the field of AI-driven SSA.

show abstract

Section: Security Requirement Elicitationmentioning

confidence: 99%

Section: Security Requirement Elicitationmentioning

confidence: 99%