There is growing use of technology-enabled contact tracing, the process of identifying potentially infected COVID-19 patients by notifying all recent contacts of an infected person. Governments, technology companies, and research groups alike have been working towards releasing smartphone apps, using wifi-connected devices, and distributing wearable technology to automatically track "close contacts" and identify prior contacts in the event an individual tests positive. However, there has been significant public discussion about the tensions between effective technology-based contact tracing and the privacy of individuals. To inform this discussion, we present the results of seven months of online surveys focused on contact tracing and privacy, each with 100 participants. Our first surveys were on April 1 and 3, before the first peak of the virus in the US, and we continued to conduct the surveys weekly for 10 weeks (through June), and then fortnightly through November, adding topical questions to reflect current discussions about contact tracing and COVID-19. Our results present the diversity of public opinion and can inform policy makers, technologists, researchers, and public health experts on whether and how to leverage technology to reduce the spread of COVID-19, while considering potential privacy concerns. 

Biotechnology and DNA sequencing have become commonplace in their integration into a multitude of fields. Forensics has employed DNA sequencing in order to identify crime scene victims. Direct to consumer (DTC) DNA testing has allowed consumers to determine nuances regarding their ancestry and health. Medicine has employed sequencing and wet lab systems in order to further drug development and create targeted treatments. Previous literature has shown the potential for DNA sequencing and biotechnology systems to host unique cybersecurity vulnerabilities rooting in their functionalities. For example, researchers have shown the potential for misuse in the genetic genealogy database GedMatch. Often used by law enforcement, databases such as GedMatch allow individuals to perform relationship and family tracking, using DNA sequencing results to match potential relatives. Researchers have shown that this database and its underlying algorithms could be capitalized on by an adversary to spoof their own identity or create false relationships. In coming years, we expect genetic inference models such as ancestry analysis and DNA Phenotyping, the extrapolation of an individual’s physical features based on their genetic information, to become commonplace in the aforementioned fields amongst others. Given the potency for issues that researchers have found in other models, we look to advance the body of knowledge surrounding the validity and robustness of these genetic inference models being used. We perform an overview of a series of models that determine traits such as ancestry and physical features of individuals from DNA and explore how these models could be exploited or tricked into returning incorrect results. Finally, we discuss the implications of these vulnerabilities, both for the biotechnology space and cyber-physical systems as a whole.