TY - GEN
T1 - Hidden Reality
T2 - 32nd USENIX Security Symposium, USENIX Security 2023
AU - Gopal, Sindhu Reddy Kalathur
AU - Shukla, Diksha
AU - Wheelock, James David
AU - Saxena, Nitesh
N1 - Publisher Copyright:
© 2023 32nd USENIX Security Symposium, USENIX Security 2023. All rights reserved.
PY - 2023
Y1 - 2023
N2 - Text entry is an inevitable task while using Virtual Reality (VR) devices in a wide range of applications such as remote learning, gaming, and virtual meeting. VR users enter passwords/pins to log in to their user accounts in various applications and type regular text to compose emails or browse the internet. The typing activity on VR devices is believed to be resistant to direct observation attacks as the virtual screen in an immersive environment is not directly visible to others present in physical proximity. This paper presents a video-based side-channel attack, Hidden Reality (HR), that shows - although the virtual screen in VR devices is not in direct sight of adversaries, the indirect observations might get exploited to steal the user's private information. The Hidden Reality (HR) attack utilizes video clips of the user's hand gestures while they type on the virtual screen to decipher the typed text in various key entry scenarios on VR devices including typed pins and passwords. Experimental analysis performed on a large corpus of 368 video clips show that the Hidden Reality model can successfully decipher an average of over 75% of the text inputs. The high success rate of our attack model led us to conduct a user study to understand the user's behavior and perception of security in virtual reality. The analysis showed that over 95% of users were not aware of any security threats on VR devices and believed the immersive environments to be secure from digital attacks. Our attack model challenges users' false sense of security in immersive environments and emphasizes the need for more stringent security solutions in VR space.
AB - Text entry is an inevitable task while using Virtual Reality (VR) devices in a wide range of applications such as remote learning, gaming, and virtual meeting. VR users enter passwords/pins to log in to their user accounts in various applications and type regular text to compose emails or browse the internet. The typing activity on VR devices is believed to be resistant to direct observation attacks as the virtual screen in an immersive environment is not directly visible to others present in physical proximity. This paper presents a video-based side-channel attack, Hidden Reality (HR), that shows - although the virtual screen in VR devices is not in direct sight of adversaries, the indirect observations might get exploited to steal the user's private information. The Hidden Reality (HR) attack utilizes video clips of the user's hand gestures while they type on the virtual screen to decipher the typed text in various key entry scenarios on VR devices including typed pins and passwords. Experimental analysis performed on a large corpus of 368 video clips show that the Hidden Reality model can successfully decipher an average of over 75% of the text inputs. The high success rate of our attack model led us to conduct a user study to understand the user's behavior and perception of security in virtual reality. The analysis showed that over 95% of users were not aware of any security threats on VR devices and believed the immersive environments to be secure from digital attacks. Our attack model challenges users' false sense of security in immersive environments and emphasizes the need for more stringent security solutions in VR space.
UR - https://www.scopus.com/pages/publications/85171201089
M3 - Conference contribution
AN - SCOPUS:85171201089
T3 - 32nd USENIX Security Symposium, USENIX Security 2023
SP - 859
EP - 876
BT - 32nd USENIX Security Symposium, USENIX Security 2023
PB - USENIX Association
Y2 - 9 August 2023 through 11 August 2023
ER -