A classification approach for software requirements towards maintainable security

Kadebu, Prudence; Sikka, Sunil; Tyagi, R. K.; Chiurunge, Panashe

doi:10.1016/j.sciaf.2022.e01496

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Enhancing underscores the intention to improve and uplift the existing state of knowledge, focusing on the young learners classified as elementary students (Anderson et al, 2021;Oke & Fernandes, 2020;Tao & Gao, 2022). The term knowledge pertains to the awareness and comprehension these students possess, specifically in the realm of web security fundamentals, which encompasses the foundational concepts essential for safeguarding information and navigating the internet securely (Gandikota et al, 2023;Kadebu et al, 2023;Yasin et al, 2024). Counseling suggests an interactive and guidance-oriented approach to education, emphasizing the role of insightful sessions aimed at imparting knowledge and promoting a deeper understanding of web security fundamentals among elementary students (Hulsman & Van Der Vloodt, 2015;Oti & Pitt, 2021;Roshid & Ibna Seraj, 2023).…”

Section: A Introductionmentioning

confidence: 99%

Enhancing Elementary Student’s Knowledge Through Web Security Fundamentals Counseling

Sanmorino,

Gustriansyah,

Puspasari

2024

JMM

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This Community Service Program (PkM) focuses on delivering fundamental web security concepts tailored to the age-specific needs of young learners. Collaborative efforts among teachers, and parents, ensure a cohesive implementation of web security measures within the school environment. This PkM activity aims to enhance elementary school student's knowledge about the importance of web security. The method used is by giving lectures and interactive discussions to PkM participants. The total number of participants involved in this PkM is around 25 people, consisting of teachers and students. Evaluation of this PkM activities based on questionnaire feedback from PkM participants. According to feedback from participants, there has been a noticeable improvement in understanding the significance of web security. Before engaging in PkM activities, only approximately 5 percent of students possessed knowledge regarding the importance of web security. However, post-PkM activities, approximately 90 percent of students affirmed their awareness of the significance of web security.

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Section: A Introductionmentioning

confidence: 99%

Enhancing Elementary Student’s Knowledge Through Web Security Fundamentals Counseling

Sanmorino,

Gustriansyah,

Puspasari

2024

JMM

View full text Add to dashboard Cite

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Classifying software security requirements into confidentiality, integrity, and availability using machine learning approaches

Bagies

2024

PeerJ Computer Science

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Security requirements are considered one of the most important non-functional requirements of software. The CIA (confidentiality, integrity, and availability) triad forms the basis for the development of security systems. Each dimension is expressed as having many security requirements that should be designed, implemented, and tested. However, requirements are written in a natural language and may suffer from ambiguity and inconsistency, which makes it harder to distinguish between different security dimensions. Recognizing the security dimensions in a requirements document should facilitate tracing the requirements and ensuring that a dimension has been implemented in a software system. This process should be automated to reduce time and effort for software engineers. In this paper, we propose to classify the security requirements into CIA triads using Term frequency-inverse document frequency and sentence-transformer embedding as two different technologies for feature extraction. For both techniques, we developed five models by using five well-known machine learning algorithms: (1) support vector machine (SVM), (2) K-nearest neighbors (KNN), (3) Random Forest (RF), (4) gradient boosting (GB), and (5) Bernoulli Naive Bayes (BNB). Also, we developed a web interface that facilitates real-time analysis and classifies security requirements into CIA triads. Our results revealed that SVM with the sentence-transformer technique outperformed all classifiers by 87% accuracy in predicting a type of security dimension.

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A classification approach for software requirements towards maintainable security

Cited by 2 publications

References 19 publications

Enhancing Elementary Student’s Knowledge Through Web Security Fundamentals Counseling

Enhancing Elementary Student’s Knowledge Through Web Security Fundamentals Counseling

Classifying software security requirements into confidentiality, integrity, and availability using machine learning approaches

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