EyeSpot: leveraging gaze to protect private text content on mobile devices from shoulder surfing

As mobile devices allow access to an increasing amount of private data, using them in public can potentially leak sensitive information through shoulder surfing. This includes personal private data (e.g., in chat conversations) and business-related content (e.g., in emails). Leaking the former might infringe on users’ privacy, while leaking the latter is considered a breach of the EU’s General Data Protection Regulation as of May 2018. This creates a need for systems that protect sensitive data in public. We introduce EyeSpot, a technique that displays content through a spot that follows the user’s gaze while hiding the rest of the screen from an observer’s view through overlaid masks. We explore different configurations for EyeSpot in a user study in terms of users’ reading speed, text comprehension, and perceived workload. While our system is a proof of concept, we identify crystallized masks as a promising design candidate for further evaluation with regard to the security of the system in a shoulder surfing scenario

Passquerade: Improving Error Correction of Text Passwords on Mobile Devices by using Graphic Filters for Password Masking

Entering text passwords on mobile devices is a significant challenge. Current systems either display passwords in plain text: making them visible to bystanders, or replace characters with asterisks shortly after they are typed: making editing them harder. This work presents a novel approach to mask text passwords by distorting them using graphical filters. Distorted passwords are difficult to observe by attackers because they cannot mentally reverse the distortions. Yet passwords remain readable by their owners because humans can recognize visually distorted versions of content they saw before. We present results of an online questionnaire and a user study where we compared Color-halftone, Crystallize, Blurring, and Mosaic filters to Plain text and Asterisks when 1) entering, 2) editing, and 3) shoulder surfing one-word passwords, random character passwords, and passphrases. Rigorous analysis shows that Color-halftone and Crystallize filters significantly improve editing speed, editing accuracy and observation resistance compared to current approaches

Balancing Image Privacy and Usability with Thumbnail-Preserving Encryption

In this paper, we motivate the need for image encryption techniques that preserve certain visual features in images and hide all other information, to balance privacy and usability in the context of cloud-based image storage services. In particular, we introduce the concept of ideal or exact Thumbnail-Preserving Encryption (TPE), a special case of format-preserving encryption, and present a concrete construction. In TPE, a ciphertext is itself an image that has the same thumbnail as the plaintext (unencrypted) image, but that provably leaks nothing about the plaintext beyond its thumbnail. We provide a formal security analysis for the construction, and a prototype implementation to demonstrate compatibility with existing services. We also study the ability of users to distinguish between thumbnail images preserved by TPE. Our findings indicate that TPE is an efficient and promising approach to balance usability and privacy concerns for images. Our code and a demo are available at http://photoencryption.org

A STUDY OF GRAPHICAL ALTERNATIVES FOR USER AUTHENTICATION

Merged with duplicate record 10026.1/1124 on 27.02.2017 by CS (TIS)Merged with duplicate record 10026.1/1124 Submitted by Collection Services ([email protected]) on 2012-08-07T10:49:43Z No. of bitstreams: 1 JALI MZ_2011.pdf: 7019966 bytes, checksum: e2aca7edf5e11df083ec430aedac512f (MD5) Approved for entry into archive by Collection Services([email protected]) on 2012-08-07T10:50:20Z (GMT) No. of bitstreams: 1 JALI MZ_2011.pdf: 7019966 bytes, checksum: e2aca7edf5e11df083ec430aedac512f (MD5) Made available in DSpace on 2012-08-07T10:50:20Z (GMT). No. of bitstreams: 1 JALI MZ_2011.pdf: 7019966 bytes, checksum: e2aca7edf5e11df083ec430aedac512f (MD5) Previous issue date: 2011Authenticating users by means of passwords is still the dominant form of authentication despite its recognised weaknesses. To solve this, authenticating users with images or pictures (i.e. graphical passwords) is proposed as one possible alternative as it is claimed that pictures are easy to remember, easy to use and has considerable security. Reviewing literature from the last twenty years found that few graphical password schemes have successfully been applied as the primary user authentication mechanism, with many studies reporting that their proposed scheme was better than their predecessors and they normally compared their scheme with the traditional password-based. In addition, opportunities for further research in areas such as image selection, image storage and retrieval, memorability (i.e. the user’s ability to remember passwords), predictability, applicability to multiple platforms, as well as users’ familiarity are still widely possible. Motivated by the above findings and hoping to reduce the aforementioned issues, this thesis reports upon a series of graphical password studies by comparing existing methods, developing a novel alternative scheme, and introducing guidance for users before they start selecting their password. Specifically, two studies comparing graphical password methods were conducted with the specific aims to evaluate users’ familiarity and perception towards graphical methods and to examine the performance of graphical methods in the web environment. To investigate the feasibility of combining two graphical methods, a novel graphical method known as EGAS (Enhanced Graphical Authentication System) was developed and tested in terms of its ease of use, ideal secret combination, ideal login strategies, effect of using smaller tolerances (i.e. areas where the click is still accepted) as well as users’ familiarity. In addition, graphical password guidelines (GPG) were introduced and deployed within the EGAS prototype, in order to evaluate their potential to assist users in creating appropriate password choices. From these studies, the thesis provides an alternative classification for graphical password methods by looking at the users’ tasks when authenticating into the system; namely click-based, choice-based, draw-based and hybrid. Findings from comparative studies revealed that although a number of participants stated that they were aware of the existence of graphical passwords, they actually had little understanding of the methods involved. Moreover, the methods of selecting a series of images (i.e. choice-based) and clicking on the image (i.e. click-based) are actually possible to be used for web-based authentication due to both of them reporting complementary results. With respect to EGAS, the studies have shown that combining two graphical methods is possible and does not introduce negative effects upon the resulting usability. User familiarity with the EGAS software prototype was also improved as they used the software for periods of time, with improvement shown in login time, accuracy and login failures. With the above findings, the research proposes that users’ familiarity is one of the key elements in deploying any graphical method, and appropriate HCI guidelines should be considered and employed during development of the scheme. Additionally, employing the guidelines within the graphical method and not treating them as a separate entity in user authentication is also recommended. Other than that, elements such as reducing predictability, testing with multiple usage scenarios and platforms, as well as flexibility with respect to tolerance should be the focus for future research

A User Authentication System Using Schema of Visual Memory(Network Security, <Special Issue>Research on Computer Security Characterized in the Context of Social Responsibilities)

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