No Silver Bullet: Towards Demonstrating Secure Software Development for Danish Small and Medium Enterprises in a Business-to-Business Model
March 06, 2025 Β· Declared Dead Β· π International Conference on Human Factors in Computing Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Raha Asadi, Bodil Biering, Vincent van Dijk, Oksana Kulyk, Elda Paja
arXiv ID
2503.04293
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CR,
cs.SE
Citations
0
Venue
International Conference on Human Factors in Computing Systems
Last Checked
4 months ago
Abstract
Software developing small and medium enterprises (SMEs) play a crucial role as suppliers to larger corporations and public administration. It is therefore necessary for them to be able to demonstrate that their products meet certain security criteria, both to gain trust of their customers and to comply to standards that demand such a demonstration. In this study we have investigated ways for SMEs to demonstrate their security when operating in a business-to-business model, conducting semi-structured interviews (N=16) with practitioners from different SMEs in Denmark and validating our findings in a follow-up workshop (N=6). Our findings indicate five distinctive security demonstration approaches, namely: Certifications, Reports, Questionnaires, Interactive Sessions and Social Proof. We discuss the challenges, benefits, and recommendations related to these approaches, concluding that none of them is a one-size-fits all solution and that more research into relative advantages of these approaches and their combinations is needed.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted