REHYB@STELAR: The Future of Privacy – Predictions and Challenges 

04.09.2023. In the rapidly evolving digital age, dealing with advancements in technology especially in the health sector, and personal data privacy is becoming increasingly complicated. As encryption technologies and data protection technologies and decentralized data systems advance, this can give users more control over their information. At the same time however, the different and often incompatible data protection regulations, the potential misuse of biometric and other personal data, and the challenges of maintaining public trust need to be addressed. 

Quantum computing, with its potential to make traditional encryption methods obsolete, makes the development of quantum-resistant algorithms to keep data secure very important [1]. Systems based on technologies such as the blockchain are revolutionizing the way we approach data by allowing users to have more granular control over their information [2]

Edge computing, a model where data processing happens closer to the data source like a local computer or IoT device, is also emerging. Because it reduces the need to transfer data across networks, it offers enhanced privacy and reduced latency3. In addition, AI tools offer real-time monitoring and protection of user data. These tools, powered by machine learning, are important in identifying breaches or unauthorized access, thus increasing security measures4. Moreover, the concept of personal data marketplaces is beginning to be introduced. Envisioned as platforms where individuals can control and potentially monetize their data, these marketplaces could democratize the benefits of data ownership, turning the tables on traditional models where primarily corporations get all the benefits5

However, these developments come with additional challenges that need to be addressed. The swift rise of AI, into our daily lives, has made the challenge of utility versus privacy even more prevalent. AI usually requires vast amounts of data, thus increasing the privacy problem. Additionally, in our increasingly global digital ecosystem, companies need to face the complexities of different data privacy regulations, like the GDPR in Europe [6] and the CCPA in California [7], that sometimes are incompatible with each other. 

Third party trackers are another threat to personal data privacy that needs to be addressed [8]. It has been shown that even if an individual does not have a profile on certain platforms, shadow profiles continue to compromise online anonymity [9]. Biometric data which can range from facial recognition to gait analysis, are constantly collected and increase the potential privacy implications to users due to misuse or unwarranted access [10]. Because of all these issues, public’s trust in tech entities is being diminished, given the constant news of data breaches [11]

Adding to all this, the constant need to regularly update current security protocols further complicates the landscape. Despite all the technological advances that are being made towards strengthening data privacy and security, the methods of potential adversaries are evolving as well. At the same time, the potential for invasive surveillance, empowered by cutting-edge tools in the hands of governments and private institutions, places personal privacy and freedoms at risk [12]

New technologies can make our lives much more comfortable and easier, however the increasing need of more and more invasive personal data means that they need to be introduced to the public after careful consideration of the implications towards user privacy. Laws and regulations need to be swift in adapting to these new technologies and standards need to be developed which will assist technology providers in their efforts to respect user privacy. 

[1] Bernstein, D.J. and Lange, T., 2017. Post-quantum cryptography. Nature, 549(7671), pp.188-194.

[2] Tapscott, D. and Tapscott, A., 2016. Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world. Penguin.

[3] Yi, S., Hao, Z., Qin, Z. and Li, Q., 2015, November. Fog computing: Platform and applications. In 2015 Third IEEE workshop on hot topics in web systems and technologies (HotWeb) (pp. 73-78). IEEE.

[4] Jordan, M.I. and Mitchell, T.M., 2015. Machine learning: Trends, perspectives, and prospects. Science, 349(6245), pp.255-260.

[5] Oh, H., Park, S., Lee, G.M., Heo, H. and Choi, J.K., 2019. Personal data trading scheme for data brokers in IoT data marketplaces. IEEE Access, 7, pp.40120-40132.



[8] Mayer, J.R. and Mitchell, J.C., 2012, May. Third-party web tracking: Policy and technology. In 2012 IEEE symposium on security and privacy (pp. 413-427). IEEE.

[9] Garcia, D., 2017. Leaking privacy and shadow profiles in online social networks. Science advances, 3(8), p.e1701172.

[10] Jain, A.K., Ross, A. and Prabhakar, S., 2004. An introduction to biometric recognition. IEEE Transactions on circuits and systems for video technology, 14(1), pp.4-20.

[11] Seh, A.H., Zarour, M., Alenezi, M., Sarkar, A.K., Agrawal, A., Kumar, R. and Ahmad Khan, R., 2020, May. Healthcare data breaches: insights and implications. In Healthcare (Vol. 8, No. 2, p. 133). MDPI.

[12] Greenwald, G., 2014. No place to hide: Edward Snowden, the NSA, and the US surveillance state. Macmillan.