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A New Implementation Of Federated Learning For Privacy And Security Enhancement, Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian
A New Implementation Of Federated Learning For Privacy And Security Enhancement, Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian
Department of Electrical and Computer Engineering: Faculty Publications
Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learning setting. An FL system is comprised of a central parameter server and multiple local clients. It keeps data at local clients and learns a centralized model by sharing the model parameters learned locally. No local data needs to be shared, and privacy can be well protected. Nevertheless, since it is the model instead of the raw data that is shared, the system can be exposed to the poisoning model attacks launched by …
Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel
Designing Respectful Tech: What Is Your Relationship With Technology?, Noreen Y. Whysel
Publications and Research
According to research at the Me2B Alliance, people feel they have a relationship with technology. It’s emotional. It’s embodied. And it’s very personal. We are studying digital relationships to answer questions like “Do people have a relationship with technology?” “What does that relationship feel like?” And “Do people understand the commitments that they are making when they explore, enter into and dissolve these relationships?” There are parallels between messy human relationships and the kinds of relationships that people develop with technology. As with human relationships, we move through states of discovery, commitment and breakup with digital applications as well. Technology …
Dismantling The “Black Opticon”: Privacy, Race Equity, And Online Data-Protection Reform, Anita L. Allen
Dismantling The “Black Opticon”: Privacy, Race Equity, And Online Data-Protection Reform, Anita L. Allen
All Faculty Scholarship
African Americans online face three distinguishable but related categories of vulnerability to bias and discrimination that I dub the “Black Opticon”: discriminatory oversurveillance, discriminatory exclusion, and discriminatory predation. Escaping the Black Opticon is unlikely without acknowledgement of privacy’s unequal distribution and privacy law’s outmoded and unduly race-neutral façade. African Americans could benefit from race-conscious efforts to shape a more equitable digital public sphere through improved laws and legal institutions. This Essay critically elaborates the Black Opticon triad and considers whether the Virginia Consumer Data Protection Act (2021), the federal Data Protection Act (2021), and new resources for the Federal Trade …