Security & privacy

Raluca Ada Popa receives ACM Grace Murray Hopper Award

05/11/22 — EECS associate professor wins $35,000 prize as outstanding young computer professional for her design of secure distributed systems, protecting confidentiality against attackers while maintaining full functionality

NSSC Executive Director Bethany Goldblum and NSSC Fellow Adriana Sweet writing on a glass board.

Berkeley-led consortium awarded $25M to advance nuclear security

02/16/21 — This is the consortium's third five-year, $25 million grant, allowing it to continue its mission of educating nuclear scientists and advancing nuclear technologies.

Photo illustration of Donald Trump and Joe Biden

Farid: Online disinfo now targeting COVID-19, Black Lives Matter

06/26/20 Futurism — Digital forensics expert and EECS professor Hany Farid lays out the greatest digital threats facing the country, and how to combat them

Photo illustration of student with smartphone and computer code

Reinventing cybersecurity

04/14/20 — Researchers are advancing blockchain and encryption methods to protect personal data and make sharing it more secure.

Two engineering faculty named Sloan Research Fellows

02/12/20 — Sanjam Garg, an assistant professor of electrical engineering and computer sciences (EECS), and Aditya Parameswaran, who has a joint appointment in EECS and the School of Information, were among nine Berkeley faculty members to win the prestigious research honor.

French ambassador says global institutions needed to confront technology challenges

01/16/20 — Philippe Étienne said the quickening pace of technological change requires nations to immediately build “shared governance” of the internet through both existing and perhaps new global institutions.

UC Berkeley professor influences Facebook’s efforts to combat deepfakes

01/14/20 — The social media giant hired Hany Farid to help it detect fake videos, but Farid says company's new policy is problematic.

Building a world where data privacy exists

11/18/19 New York Times — Electrical engineering and computer sciences professor Dawn Song, a leading expert in computer security and trustworthy artificial intelligence, is building a platform in which people control their own data online and are compensated for its use by corporations.

Silicon Valley combating deepfake videos that could upend an election

11/05/19 Los Angeles Times — Leaders in artificial intelligence are unveiling a tool to push back against deepfake videos, built in part on scanning software that UC Berkeley has been developing in partnership with the U.S. military.

Photo illustration of Barack Obama, Mark Zuckerberg and Elizabeth Warren

Moments of untruth

10/25/19 — Computer science researchers are using groundbreaking machine learning technologies to expose deepfake videos, manipulated images and other types of digital deception.

AI researchers race to detect ‘deepfake’ videos: ‘We are outgunned’

06/13/19 Washington Post — EECS graduate student Shruti Agarwal and incoming professor Hany Farid argue that powerful new AI software has effectively democratized the creation of convincing “deepfake” videos, making it easier than ever to fabricate someone appearing to say or do something they didn't really do.

Berkeley links up with Facebook, but wants to see tech giant’s accountability

05/17/19 — Stung by bad press and government investigations, Facebook is investing $7.5 million in a partnership with three universities - UC Berkeley, Cornell and Maryland - to develop new methods to improve detection of fake content, fake news and misinformation campaigns. At Berkeley, the work will be led by EECS professors Hany Farid and Alexei Efros.

Graphic of health tools on portable device

Protecting health data privacy

05/01/19 — Artificial intelligence can identify individuals by correlating step data from activity trackers and smartphones with demographic data.

Dawn Song speaking at the EmTech Digital conference

How malevolent machine learning could derail AI

03/26/19 MIT Technology Review — Berkeley Engineering AI security expert Dawn Song warns that “adversarial machine learning” could be used to reverse-engineer systems - including those used in defense.

Activism 2.0: Coding against sex trafficking

01/30/19 — UC Berkeley's ongoing video series on the intersection of social activism and technology profiles recent CS doctoral graduate Rebecca Sorla Portnoff, who uses her computer security know-how to help catch sex traffickers.

Artificial intelligence opens health data privacy to attack

12/21/18 — Current privacy laws and regulations are nowhere near sufficient to keep an individual's health data private in the face of advances in artificial intelligence, according to a new study from IEOR professor Anil Aswani and his team.

Berkeley researchers to help develop trustworthy machine learning systems

10/24/18 — Berkeley engineers, led by computer sciences professor Dawn Song, are part of the new Center for Trustworthy Machine Learning funded by the National Science Foundation. The NSF center, led by Pennsylvania State University and announced today, will focus on developing secure systems in the era of machine learning models. The center will receive $10 million over five years.

The latest course catalog trend? Blockchain 101

09/19/18 Wired — From a course teaching students to think like blockchain entrepreneurs to "collider sprints" at the Sutardja Center's Blockchain Lab, Berkeley is at the forefront of universities incorporating this multidisciplinary technology into the curriculum.

Calling out fake photos on the web

08/21/18 Wired — Fake photos are the bane of internet junkies. SurfSafe, a browser plugin from RoBhat Labs (computer science undergrads Ash Bhat and Rohan Phadte), can warn users that they're viewing a Photoshopped fake in real time - like an antivirus for photos.

Map plotting location history of Google account user

‘Location history’ off? Google’s still tracking you

08/17/18 AP News — Computer science graduate student K. Shankari tipped the Associated Press off to the persistence of Google's movement tracking, even for users who explicitly tell the company not to do so.