Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Cryptography and Security

arXiv:2211.03498 (cs)
[Submitted on 7 Nov 2022]

Title:Developers' Privacy Education: A game framework to stimulate secure coding behaviour

Authors:Abdulrahman Hassan Alhazmi, Mumtaz Abdul Hameed, Nalin Asanka Gamagedara Arachchilage
View PDF
Abstract:Software privacy provides the ability to limit data access to unauthorized parties. Privacy is achieved through different means, such as implementing GDPR into software applications. However, previous research revealed that the lack of poor coding behaviour leads to privacy breaches such as personal data breaching. Therefore, this research proposes a novel game framework as a training intervention enabling developers to implement privacy-preserving software systems. The proposed framework was empirically investigated through a survey study (with some exit questions), which revealed the elements that should be addressed in the game design framework. The developed game framework enhances developers' secure coding behaviour to improve the privacy of the software they develop.
Comments: 10
Subjects: Cryptography and Security (cs.CR)
Cite as: arXiv:2211.03498 [cs.CR]
  (or arXiv:2211.03498v1 [cs.CR] for this version)
  https://doi.org/10.48550/arXiv.2211.03498
Journal reference: The 2022 IEEE International Conference on Privacy Computing (IEEE PriComp 2022)

Submission history

From: Nalin Asanka Gamagedara Arachchilage [view email]
[v1] Mon, 7 Nov 2022 12:39:25 UTC (821 KB)
Full-text links:

Access Paper:

  • View PDF
  • Other Formats
license icon view license
Current browse context:
cs.CR
< prev   |   next >
new | recent | 2022-11
Change to browse by:
cs

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)