SecDev is a venue for presenting ideas, research, and experience about how to develop secure systems.
SecDev is distinguished by its focus on how to “build security in” (and not simply to discover the absence of security). Its goal is to encourage and disseminate ideas for secure system development among both academia and industry. Developers have valuable experiences and ideas that can inform academic research, and researchers have concepts, studies, and even code and tools that could benefit developers. We anticipate that attendees from academic conferences like IEEE S&P, USENIX Security, PLDI, FSE, ISSTA, SOUPS, and many others could contribute ideas to SecDev, as could attendees of industrial conferences like AppSec, RSA, Black Hat, and Shmoocon.
|Papers||Paper and tutorial submission (extended):||11:59 PM, March 12, 2018 PST|
|Paper and tutorial notification:||May 15, 2018|
|Practitioner’s Session Abstract submission:||July 20, 2018||Practitioner’s Session Notification:||August 10, 2018|
|Camera-ready versions due:||TBA|
|Posters||Poster submission deadline:||August 25, 2018|
|Poster notification:||August 30, 2018|
|Student Travel Grants||Applications Due:||TBA|
|Registration||Early Bird Rate Ends:||August 17, 2018|
|Hotel||Discounted Rates End:||TBA|
|Reservation Deadline:||August 29, 2018, 5pm EST|
Professor, University of California, Berkeley
Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley. Her research interest lies in deep learning, security, and blockchain. She has studied diverse security and privacy issues in computer systems and networks, including areas ranging from software security, networking security, distributed systems security, applied cryptography, blockchain and smart contracts, to the intersection of machine learning and security. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, the George Tallman Ladd Research Award, the Okawa Foundation Research Award, the Li Ka Shing Foundation Women in Science Distinguished Lecture Series Award, the Faculty Research Award from IBM, Google and other major tech companies, and Best Paper Awards from top conferences in Computer Security and Deep Learning. She obtained her Ph.D. degree from UC Berkeley. Prior to joining UC Berkeley as a faculty, she was a faculty at Carnegie Mellon University from 2002 to 2007.