Seminar: Protecting Cyber Security and Privacy via Unobtrusive Sensing

 

  

Chen Wang

LSU Division of Computer Science and Engineering

Tuesday March 11, 2022

1:00 pm

Location: Patrick F. Taylor Hall Room 3107

Abstract

Authentication secures the gate to the cyber world, which is the first line of defense to protect cyber security and privacy. However, existing user authentications require active human participation to provide identity information, while users are not always available to do so in many practical scenarios. For example, to unlock a smartphone, you need to input a passcode/PIN, scan your face ID or issue a voice command. When the unlocked device is shared with friends or family members, your privacies in the album, emails, social network Apps and calendar reminders are out of your control. Even if the phone is locked and left on a table, a notification message, which is designed to show up on the screen automatically, may leak your privacy to someone nearby. In addition to the above-mentioned obtrusiveness, the replication of authentication information is another long-standing issue. For example, your face, iris, and fingerprint can be physically forged based on 3D printing, while your password/PIN and voice can be leaked to eavesdropping and shoulder surfing.

In this talk, I will introduce effortless user authentications to address the above security issues. Based on unobtrusive sensing techniques, a user can be verified automatically to receive identity-based services. For example, your smartphone would only display sensitive content after verifying who is gripping the phone. We further develop biometric encoding and cross-domain sensing to counteract replay attacks. We extend such enhanced security to cyber-physical systems while providing the last line of defense. And lastly, we will visit the evil side of pervasive sensing and introduce the newly identified security threats.  

 

 

Bio

Chen Wang is currently an Assistant Professor at Louisiana State University. He received his Ph.D. degree at Rutgers University in 2019. His research interests include cyber security and privacy, cyber-physical security, smart health care, mobile sensing and computing. His work has been published in multiple high-impact conferences, including IEEE S&P, ACM Mobicom, ACM CCS, ACM CHI, and IEEE Infocom. He is the recipient of five Best Paper Awards from IEEE INFOCOM WKSHPS 2021, EAI HealthyIoT 2019, IEEE CNS 2018, ACM ASIACCS 2016 and IEEE CNS 2014. His research studies have been reported by over 150 media outlets, including IEEE Spectrum, NSF Science 360, CBS TV, BBC News, NBC, IEEE Engineering 360, Fortune, ABC News, and MIT Technology Review.