Yale University announced Monday it will be a key partner in the Secure and Trustworthy Cyberspace program, led by the National Science Foundation to research privacy and cybersecurity.
At the moment, the $25.4 million project will include:
- Formation of the CDCC – The Center for Distributed Confidential Computing
- Enabling a secure software supply chain
- Securing accessibility to marginalized communities
Aside from Yale, the project will include the University of Florida, North Carolina State University, and Indiana University, as well as other universities including Purdue, Penn State, Carnegie Mellon, Ohio State, Duke, and Spelman College.
The primary goal is to explore the source of the problem with cybersecurity and privacy and to create viable solutions.
As predicted by the original NSF project, the program will have both technical and social aspects. Marginalized communities, especially those with less access to education and economic opportunities, would have a different set of problems when it comes to privacy and cybersecurity than those with better institutional protection.
Addressing Critical Problems in Cybersecurity and Privacy
Using the NSF grants, the educational institutions involved must explore and investigate various issues affecting the cybersecurity and privacy of internet users, primarily in the United States. However, these may also apply to users abroad.
Cybersecurity in this regard is the most pressing issue because it is badly affecting both the economic potential and individual liberties. Lapses in cybersecurity caused by insufficient information about the subject and the tools to protect sensitive data are also one of the main issues for privacy.
However, some issues affect privacy specifically and may not be a product of malicious software or illegal activities. Those issues, especially in marginalized communities that come from tech companies and even governments poised at collecting personal data are also inside the scope of the research and solution-making.
Center for Distributed Confidential Computing
Within the first major project funded by the NSF grant and led by Indiana University, the project plans to use trusted execution environment (TEE)s, made possible by modern chips. These environments would be safe from any malicious interference. They might also be the key to ensuring privacy and cybersecurity.
Fan Zhang, an assistant professor of computer science at Yale, proposed that such solutions can have life-saving effects, including those in the medical field. He gave an example of using AI for disease prognosis, which is currently seldom used because it is difficult to confirm the provided data.
But, with a solution from the imagined CDCC, this might change. Secure and diversified systems would be available to compute big data analytics and provide advancements known not to have been tampered with.
In essence, all the uses for a secure and confidential computing network can’t be imagined without the near-feasible solution. But, once the confidential option exists, it is more than likely that various industries, including medicine, construction, food and water production, and others will benefit from the advancements.
Cybersecurity Goals Far Into the Future
The issues of cybersecurity and privacy have led the White House offering assistance to educate more cybersecurity talent. However, the goal of the projects included by this grant is not to solve the existing cybersecurity-related issues. Rather, they aspire to form long-term solutions to deal with cybersecurity issues unfolding in the future.
With projects like the CDCC, it is apparent that some solutions would be immediate. This will mostly be towards other projects already run by the education institutions involved in the area of AI development.
AI has come a long way and can currently help with a variety of tasks that were in the domain of science fiction in the past. Interestingly, some results point out that science fiction was correct in both the imagination and the cautionary tale. In fact, AI can easily lose its accuracy due to bogus information and people having fun with it online.
With secured connections and uncompromised communication, it might be possible to allow AI to access big data and learn without the risk of stumbling on corrupted information. In this case, the corrupted information may be a technical issue, or straight lies made up by people.
Secure Software Supply Chain
The supply chain has been on everyone’s lips in the last two years because of many recent global issues. But supply chain issues that exist in the digital sphere have not received the same attention. Luckily, it is one of the areas the project grant aims to address. The North Carolina State University is leading this collaborative research focusing on open-source digital supply chain security. The study aims to envision solutions that would prevent malicious entities from contaminating open-source software during the distribution stages.
Therefore, researchers will collaborate with consumers, governments, and industry leaders from diverse fields and backgrounds. Together, they will formulate solutions aimed at protecting software as well as the consumers and developers in that chain.
Addressing the Issue of Marginalized and Vulnerable Demographics
Acknowledging that most cybersecurity issues may be somewhat identical across all users, it is still apparent that some users have a harder time dealing with cybersecurity and privacy issues. Besides, those vulnerable users also have less access to cybersecurity tools and institutions that might secure their privacy.
In the project led by the University of Florida and assisted by computer and social scientists from the University of Washington and Indiana University, the goal is to address the specific concerns that are affecting marginalized communities and increasing their individual and collective risk of harm.
Primarily, this includes vulnerable socio-economic demographics. However, it also applies to ethnic and linguistic minorities that, for a variety of reasons, have less access to cybersecurity tools and information compared to the average user.
The goal of the project is to find unique solutions that would support these communities and individuals. Ideally, it will remove the obstacles created by the frequent unintentional amerocentric bias presented by many researchers and developers.