Cybersecurity Education to Create Awareness in Artificial Intelligence Applications for Developers and End Users

Dawson, Maurice; Szakonyi, Annamaria

doi:10.2478/bsaft-2020-0012

Abstract

This new era brings new promises of technology that will bring economic and societal benefits. Artificial Intelligence is to be the disruptor for work and even military technological applications. However, developers and end-users will play keys roles in how this technology is developed and ultimately used. Among these two groups, there are cybersecurity concerns that need to be considered. In this paper, the researchers address the process of secure development and testing. Also, for the end-user appropriate methods, procedures, and recommendations are defined that can mitigate the overall use of this technology within an enterprise.

References

Alani, M. M. (2017). Android users privacy awareness survey. International Journal of Interactive Mobile Technologies (IJIM), Vol. 11, Issue 3, 130-144.10.3991/ijim.v11i3.6605
Search in Google Scholar Back to article
Alhazmi, O. H., Malaiya, Y. K., & Ray, I. (2007). Measuring, analyzing and predicting security vulnerabilities in software systems. Computers & security, Vol. 26, Issue 3, 219-228.10.1016/j.cose.2006.10.002
Search in Google Scholar Back to article
Breitinger, F., Tully-Doyle, R., & Hassenfeldt, C. (2020). A survey on smartphone user’s security choices, awareness and education. Computers & Security, Vol. 88.10.1016/j.cose.2019.101647
Search in Google Scholar Back to article
Dawson, M. (2018). Applying a holistic cybersecurity framework for global IT organizations. Business Information Review, Vol. 35, Issue 2, 60-67.10.1177/0266382118773624
Search in Google Scholar Back to article
Dawson, M., Burrell, D.N., Rahim, E., & Brewster, S. (2010). Integrating software assurance into the software development life cycle (SDLC). Journal of Information Systems Technology and Planning, Vol. 3, Issue 6, 49-53.
Search in Google Scholar Back to article
Do, T. M. T., & Gatica-Perez, D. (2010). By their apps you shall understand them: mining large-scale patterns of mobile phone usage. Proceedings of the 9^th International Conference on Mobile and Ubiquitous Multimedia, 1-10.10.1145/1899475.1899502
Search in Google Scholar Back to article
Federal Trade Commission v. CompuCredit Corporation and Jefferson Capital Systems, LLC. (2008). Complaint for Permanent Injunction and Other Equitable Relief, available at: https://www.ftc.gov/sites/default/files/documents/cases/2008/06/080610compucreditcmplt.pdf, accessed on 20 June 2020.
Search in Google Scholar Back to article
Jeslet, D. S., Sivaraman, G., Uma, M., Thangadurai, K., & Punithavalli, M. (2010). Survey on awareness and security issues in password management strategies. International Journal of Computer Science and Network Security, Vol. 10, Issue 4, 19-23.
Search in Google Scholar Back to article
Kumar, G., & Bhatia, P. K. (2014). Comparative analysis of software engineering models from traditional to modern methodologies. 4^th International Conference on Advanced Computing & Communication Technologies, 189-196.10.1109/ACCT.2014.73
Search in Google Scholar Back to article
Levin, S., & Woolf, N. (2016). Tesla driver killed while using autopilot was watching Harry Potter, witness says, available at: https://www.theguardian.com/technology/2016/jul/01/tesla-driver-killed-autopilot-self-driving-car-harry-potter, accessed on 20 June 2020.
Search in Google Scholar Back to article
Paul, M. (2015). Official (ISC)2 Guide to the CSSLP. CRC Press.10.1201/b10978
Search in Google Scholar Back to article
Potter, B., & McGraw, G. (2004). Software security testing. IEEE Security & Privacy, Vol. 2, Issue 5, 81-85.10.1109/MSP.2004.84
Search in Google Scholar Back to article
Steinebach, M., & Waidner, M. (2018). Artificial Intelligence in IT Security. Whither Artificial Intelligence, 31-36.10.1109/IC-AIAI.2018.8674444
Search in Google Scholar Back to article
Tam, L., Glassman, M., & Vandenwauver, M. (2010). The psychology of password management: a tradeoff between security and convenience. Behaviour & Information Technology, Vol. 29, Issue 3, 233-244.10.1080/01449290903121386
Search in Google Scholar Back to article
Toubiana, V., Narayanan, A., Boneh, D., Nissenbaum, H., & Barocas, S. (2010). Adnostic: Privacy preserving targeted advertising. Proceedings Network and Distributed System Symposium.
Search in Google Scholar Back to article
Trieu, K., & Yang, Y. (2018). Artificial Intelligence-Based Password Brute Force Attacks. MWAIS Proceedings, Vol. 39.
Search in Google Scholar Back to article
Yampolskiy, R. V., & Spellchecker, M. S. (2016). Artificial intelligence safety and cybersecurity: A timeline of AI failures, available at: https://arxiv.org/ftp/arxiv/papers/1610/1610.07997.pdf, accessed on 20 June 2020.
Search in Google Scholar Back to article

Cybersecurity Education to Create Awareness in Artificial Intelligence Applications for Developers and End Users

Abstract

Paradigm

My account