David Naylor

I'm a fifth year Ph.D. student in the Computer Science Department at Carnegie Mellon University, and I'm interested in computer networking and security. My advisor is Peter Steenkiste.


I received degrees in computer science and mathematics from The University of Iowa, where I worked with the UI Computational Epidemiology Group.


Click here for my CV.




GHC 7509

School of Computer Science

Carnegie Mellon University





Ubiquitous Encryption

Preparing for an HTTPS-only Web.

Multi-Context TLS (mcTLS)

Multi-Context TLS allows endpoints to explicitly add trusted middleboxes to encrypted sessions. It provides fine-grained access control, so middlebox access can be restricted to read-only or limited to only part of the data stream.




HTTPS Dashboard


Monitoring the usage of HTTPS on the Web.


Check it out →


The Cost of the "S" in HTTPS

A collection of measurements showing the deployment and costs of HTTPS. Costs include handshake latency and loss of middlebox services like caching and compression.



HTTP/2 Dashboard


Monitoring the adoption and performance of HTTP/2 on the Web.


Check it out →

eXpressive Internet Architecture

An Evolvable, Expressive, and Secure Future Internet Architecture

My current work is on the eXpressive Internet Architecture (XIA), one of five future Internet architecture projects sponsored by the NSF.



Accountability and Privacy

The Accountable and Private Internet Architecture (APIP) is designed to balance accountability and privacy. Senders are able to hide their addresses from the network by delegating responsibility for their packets to a trusted third party, which vouches for its clients' traffic unless a flow has been reported as malicious.




Demo at GEC15

In October 2012, we demoed XIA running on the GENI network at the 15th GENI Engineering Conference:





Watch the video


See the slides

Sensing Social Networks

Measuring Healthcare Worker Contact Patterns

Through my work with CompEpi, I helped deploy a sensor network in the intensive care unit at the University of Iowa Hospitals and Clinics. We gathered anonymized data telling us when healthcare workers were in contact with one another, when they were in contact with patients, and when they washed their hands. This data helped us answer questions about hand hygiene policy compliance and explore how communicable diseases might spread through the unit.

Scrub Scrub Revolution

Handwashing Technique for Healthcare Workers

Our sensor network project helped us monitor when healthcare workers washed their hands, but equally important is how. The World Health Organization has published recommendations for proper handwashing technique; these guidelines include a set of recommended scrubbing motions. I implemented a training “game” in which users scrub along with an expert while wearing accelerometers on their wrists, allowing the sytem to provide feedback on their scrubbing technique.