Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique called 3D Pattern. Our 3D Pattern technique takes advantage of a new input paradigm called pre-touch, which could soon allow smartphones to sense a user's finger position at some distance from the screen. We implement the technique and evaluate it in a pilot study (n=6) by comparing it to PIN and pattern locks. Our results show that although our prototype takes about 8 seconds to authenticate, it is immune to smudge attacks and promises to be more resistant to shoulder surfing.
Shoulder surfing is a widely known attack in which the adversary tries to infer the victim's authentication secret by looking over his or her shoulder. There is a significant body of research into mitigating the impact of shoulder-surfing attacks. An in-depth survey conducted by @cite_8 considered the threat not only in the context of authentication, but also in the context of routine smartphone usage. The survey showed that 130 out of 174 participants indicated that shoulder-surfing attacks occurred on public transportation. Victims most commonly defended against such an attack by modifying their posture or cancelling the authentication. Furthermore, a study conducted by @cite_18 found the perceived risk of shoulder surfing to be high in only 11 of 3410 situations. This demonstrates that people are not actively defending themselves against shoulder surfing, and more work is needed to improve the shoulder-surfing resistance of authentication techniques.
@cite_18 @cite_8
2611149039 93892664 2139094422 2795614125
Research has brought forth a variety of authentication systems to mitigate observation attacks. However, there is little work about shoulder surfing situations in the real world. We present the results of a user survey (N=174) in which we investigate actual stories about shoulder surfing on mobile devices from both users and observers. Our analysis indicates that shoulder surfing mainly occurs in an opportunistic, non-malicious way. It usually does not have serious consequences, but evokes negative feelings for both parties, resulting in a variety of coping strategies. Observed data was personal in most cases and ranged from information about interests and hobbies to login data and intimate details about third persons and relationships. Thus, our work contributes evidence for shoulder surfing in the real world and informs implications for the design of privacy protection mechanisms. Traditional password based authentication scheme is vulnerable to shoulder surfing attack. So if an attacker sees a legitimate user to enter password then it is possible for the attacker to use that credentials later to illegally login into the system and may do some malicious activities. Many methodologies exist to prevent such attack. These methods are either partially observable or fully observable to the attacker. In this paper we have focused on detection of shoulder surfing attack rather than prevention. We have introduced the concept of tag digit to create a trap known as honeypot. Using the proposed methodology if the shoulder surfers try to login using others’ credentials then there is a high chance that they will be caught red handed. Comparative analysis shows that unlike the existing preventive schemes, the proposed methodology does not require much computation from users end. Thus from security and usability perspective the proposed scheme is quite robust and powerful. Shoulder-surfing -- using direct observation techniques, such as looking over someone's shoulder, to get passwords, PINs and other sensitive personal information -- is a problem that has been difficult to overcome. When a user enters information using a keyboard, mouse, touch screen or any traditional input device, a malicious observer may be able to acquire the user's password credentials. We present EyePassword, a system that mitigates the issues of shoulder surfing via a novel approach to user input. With EyePassword, a user enters sensitive input (password, PIN, etc.) by selecting from an on-screen keyboard using only the orientation of their pupils (i.e. the position of their gaze on screen), making eavesdropping by a malicious observer largely impractical. We present a number of design choices and discuss their effect on usability and security. We conducted user studies to evaluate the speed, accuracy and user acceptance of our approach. Our results demonstrate that gaze-based password entry requires marginal additional time over using a keyboard, error rates are similar to those of using a keyboard and subjects preferred the gaze-based password entry approach over traditional methods. We evaluate the efficacy of shoulder surfing defenses for PIN-based authentication systems. We find tilting the device away from the observer, a widely adopted defense strategy, provides limited protection. We also evaluate a recently proposed defense incorporating an "invisible pressure component" into PIN entry. Contrary to earlier claims, our results show this provides little defense against malicious insider attacks. Observations during the study uncover successful attacker strategies for reconstructing a victim's PIN when faced with a tilt defense. Our evaluations identify common misconceptions regarding shoulder surfing defenses, and highlight the need to educate users on how to safeguard their credentials from these attacks.