Improving the Usability of Graphical Authentication Systems Using Subject-Based Images

Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IMPACT FACTOR: 7.056 IJCSMC, Vol. 13, Issue. 8, August 2024, pg.107 – 117 Improving the Usability of Graphical Authentication Systems Using Subject-Based Images Hassan Umar Suru Department of Computer Science, Kebbi State University of Science and Technology, Aliero Email: hu.suru@ksusta.edu.ng; suruhassan@yahoo.com DOI: https://doi.org/10.47760/ijcsmc.2024.v13i08.012 Abstract – Recognition based graphical authentication systems rely on a system user’s ability to recognize previously chosen images and use those images to gain access into a computing systems, devices or application. Recognition based systems that utilise several types of images have been developed and studied. The déjà vu scheme depends on the use of abstract (meaningless) images. Images in the déjà vu scheme have no exact meaning. This scheme has also been actively studied. This article presents a between user study conducted on two recognition-based schemes using system prototypes. The Abstract Based Graphical Authentication (ABGA) was designed to simulate the déjà vu scheme. The performance of this system was compared with the performance of a novel system developed for this research. The novel system, called Subject Based Graphical Authentication (SBGA), in which the system used images from the various disciplines of the research participants. The researcher conducted a lab-based study with 100 participants, 50 participants for each of the prototypes. The study investigated the impact of using subject based images to enhance the usability and security of recognition-based graphical passwords. Two graphical models were thus developed and presented to the 100 participants, which comprised of staff and students from the departments of Computer Science, Mathematics, and Engineering. In the experiments, participants selected their graphical passwords from sets of images representing their various disciplines. The researcher observed that the memorability rate for graphical passwords consisting of subject based images aligned with participants' disciplines surpassed the rate for passwords with purely abstract images. The results indicated 81.7% successful login rate and 18.3% failure rate for Subject Based Graphical Authentication (SBGA). In contrast, Abstract Based Graphical Authentication (ABGP) exhibited a 51.5% successful login rate and a 48.7% failure rate. The findings provide significant insights for graphical password designers and developers seeking to enhance system memorability. Balancing image familiarity with security considerations can lead to more user-friendly and effective recognition-based authentication systems. This study provides valuable insights into the benefits of incorporating familiar images in recognition-based graphical passwords, showcasing a significant improvement in memorability and user authentication success. The findings underscore the importance of considering the user’s familiarity with portfolio images in the design of graphical authentication systems. Keywords – Graphical, Authentication, Authentication, Authentication Systems, Usability, Subject based. © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 107 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 I. INTRODUCTION Authentication, the process of permitting access to authorized users while preventing unauthorized access, stands as a crucial aspect of computer security (Shammee et al., 2020). For decades, user authentication has been at the forefront of computing security, especially with the continuous growth of technology raising concerns about security threats from attackers, hackers, crackers, scammers, and spammers (Pirim et al., 2008). Authentication, therefore, plays a pivotal role in both research and practical applications of security (Gao et al., 2009; Velásquez et al., 2018). The most widely adopted method for remote user authentication is passwords, where a password, defined as a secret word or string of characters, serves to prove identity and grant access to resources (Das et al., 2004). Despite its popularity due to high usability and costeffectiveness compared to alternatives like graphic and biometric authentication, text-based authentication has drawbacks. Users often resort to inse cure practices, such as reusing single passwords across multiple accounts for ease of remembrance, compromising security (Devika & Backiyalakshmi, 2014). In response to the limitations of traditional text-based passwords, graphical password techniques have emerged. Leveraging images, which are inherently more memorable than text, these techniques aim to enhance the security and usability of authentication (Yahia et al., 2021). Graphical passwords, also known as graphical authentication systems, replace characters or numbers with images during user authentication (Suru & Murano, 2019). These techniques can be broadly categorized into Recognition-based, Pure Recall-Based, Cued Recall-Based, and Hybrid Techniques (Perrig et al., 1999). As digital systems continue to evolve, the necessity for authentication methods that balance security and user-friendliness becomes increasingly apparent. This research titled "Improving the Usability of Graphical Authentication Systems Using Subject-Based Images" focused on understanding the effect of utilizing subject based images in enhancing the memorability of graphical passwords, particularly within users' academic disciplines. The study employs a combination of quantitative measures (success rates, login time) and qualitative data gathered from user feedback and perceptions. By exploring the relationship between image familiarity and the memorability of graphical authentication methods, the research aims to provide valuable insights into user preferences and experiences. Preliminary findings suggest that graphical passwords associated with familiar images exhibit higher memorability, indicating a user preference for authentication systems that leverage familiar visual cues. The study not only offers practical recommendations for the implementation of graphical password systems, but also highlights the importance of user-centered design principles. Acknowledging limitations, including sample bias and the short-term nature of the study, the research suggests avenues for future exploration to address these constraints. In conclusion, this research contributes essential insights to the field of graphical authentication, emphasizing the significance of the familiarity of portfolio images to systems’ users in enhancing memorability and user preferences in the ever-evolving digital landscape. II. RELATED WORK 2.1 Graphical-Based Authentication Techniques The evolution of authentication methods has led to the emergence of graphical password techniques, offering a solution to the limitations inherent in traditional text-based approaches, given the inherently higher recall value of images compared to text (Yahia et al., 2021). The Graphical-Based Authentication Technique involves users creating a password by selecting an image during the registration process, which is subsequently stored in a database. When the user opts for the authentication process, these pre-selected images are retrieved and presented. Within this technique, © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 108 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 users then choose a specific image from a collection and designate multiple points of interest (POI) regions within the selected image. Each POI is characterized by a circle (center and radius). For each designated POI, the user associates a word or phrase, which is then combined with the specific points of interest. Notably, the user has the flexibility to either enforce a specific order for selecting POIs, resulting in a stronger password, or render the order insignificant. The classification of graphical password techniques reveals four distinct categories: Recognitionbased techniques, Pure Recall-Based techniques, Cued Recall-Based, and Hybrid approaches (Perrig et al., 1999). This categorization underscores the diverse strategies employed within graphical authentication, showcasing the breadth of methods available for securing digital access. This foundational understanding of graphical-based authentication techniques serves as a crucial background for exploring their effectiveness and user preferences, aligning with the research goal of investigating the effect of using subject based images on the memorability of recognition-based graphical authentication systems. By recognizing the diverse categories of graphical techniques, the research aims to discern patterns in user behavior and preferences, particularly in the context of subject based and abstract images. 2.2 PURE RECALL-BASED GRAPHICAL PASSWORDS Pure recall-based systems, also known as draw metric systems, necessitate users to memorize and replicate secret drawings created during the registration process (Robert et al., 2012). These systems, devoid of memory cues, typically generate and recall passwords based on users' ability to recreate their initial drawings accurately. Numerous graphical password algorithms have adopted pure recallbased methods, often building upon or enhancing the pioneering Draw-A-Secret (DAS) scheme. DAS, proposed by Jermyn et al., allows users to create a free-form drawing on a 5x5 grid during registration, with the same drawing reproduced during authentication for access to secure resources. Remarkably, the DAS system is alphabet-independent, accessible to users of any language for various applications (Dunphy & Yan, 2007). The technique provides users the freedom to draw passwords of any length without the need for image transfers over networks, reducing traffic loads and server-side graphical database storage. The password space of grid-based schemes surpasses that of traditional textual passwords. However, vulnerabilities include susceptibility to guessing and shoulder-surfing attacks. Thorpe and van Oorschot (2004) conducted a comprehensive analysis of the memorable password space of the DAS scheme. Introducing the concept of graphical dictionaries, they explored the potential for brute-force attacks and identified security concerns. Their findings revealed that longer DAS passwords, especially those of length 8 or larger on a 5x5 grid, exhibited reduced susceptibility to dictionary attacks compared to textual passwords. Additionally, the study uncovered that the space of mirror symmetric graphical passwords in DAS was significantly smaller than the full password space, potentially compromising security. To address this, the researchers suggested using longer passwords to mitigate the security risk associated with symmetric passwords.urther research by Thorpe and van Oorschot delved into the impact of password length and stroke count on the complexity of the DAS scheme. Their study highlighted that stroke count significantly influences the DAS password space, with fewer strokes leading to a substantial decrease in password space for a fixed length. To enhance security, the researchers proposed a "Grid Selection" technique, allowing users to select a drawing grid, a specific rectangular region, from an initially large grid during authentication. This proposed method aimed to augment the DAS password space substantially. In contrast, signature techniques, proposed by Syukri et al. (1998), involve users drawing their signatures during registration and verification stages. The system extracts the signature area during registration and employs geometric average means and dynamic database updates for verification. However, drawbacks include susceptibility to signature forgery, as drawing with a mouse may be unfamiliar and challenging for some users. Point of Departure with Research Goal: This literature provides a foundation for understanding the intricacies of pure recall-based graphical passwords, particularly the vulnerabilities and proposed enhancements. The research goal, investigating the effect of using subject based images on the memorability of recognition-based graphical authentication, aligns with this understanding by focusing on user preferences and experiences, shedding light on the effectiveness of these techniques in real-world scenarios. © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 109 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 2.3 Cued-Recall Systems Cued-recall systems represent a distinct category where users are prompted to remember and pinpoint specific locations within an image (Robert et al., 2012). This design aims to alleviate the memory burden on users by presenting a more manageable memory task compared to pure recall. Unlike pure recall, where users must reproduce an entire image, cued-recall tasks involve remembering specific details or regions within an image. Research suggests that individuals possess accurate and detailed visual memories of objects they previously focused on in visual scenes. This implies that users might be capable of accurately recalling specific parts of an image if those parts were the focus of their attention. In an effective cued-recall system, the cue should be beneficial solely to legitimate users, offering assistance in recalling the password, while remaining elusive to attackers attempting to guess the password. Point of Departure with Research Goal: The exploration of cued-recall systems aligns with the research goal of understanding the effect of using subject based images on the memorability of recognition-based graphical authentication. Cued-recall systems, by design, offer a compromise between pure recall and recognition, potentially enhancing user experience and security. Investigating the effectiveness of cued-recall systems, particularly in the context of user preferences for subject based images, contributes valuable insights to the overarching research goal. 2.4 Recognition-Based Technique Recognition-based graphical authentication systems rely on the user's ability to recognize images selected earlier from a substantial collection of images (Suru & Murano, 2019). In this approach, during each authentication attempt, users are presented with numerous images, and they are expected to correctly identify and select the images representing their chosen password. Figure 1.: Déjà vu (Touraj, 2015) Various recognition-based schemes have been developed and evaluated in this context. Dunphy and Yan (2007) introduced a graphical authentication scheme based on the Hash Visualization Technique proposed by Perrig et al. (1999). In this system, users are prompted to select a specific number of images from a set of randomly generated pictures. Subsequently, during authentication, users need to identify and choose the pre-selected images. Results from evaluations demonstrated a success rate of 90% for participants using this technique, surpassing the 70% success rate achieved with text-based passwords. However, a drawback is the necessity for the server to store the seeds of the portfolio images for each user in plain text, introducing potential security concerns. Additionally, the process can be perceived as tedious and time-consuming. From a security standpoint, recognition-based systems may not be direct replacements for text passwords, as their password spaces are comparable in cardinality to 4 or 5-digit PINs, © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 110 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 assuming a reasonable set of images for usability purposes. Proposed recognition-based systems incorporate various image types, including faces, random art, everyday objects, and icons. Renaud delves into specific security and usability considerations, offering design guidelines to enhance the usability of recognition-based systems. Figure 2.: Passfaces Scheme (Davis 2014) Point of Departure with current study, the Recognition-based techniques play a crucial role in the exploration of the the effect of using subject based images on the memorability of recognitionbased graphical authentication. By understanding the strengths and weaknesses of recognition-based systems, especially in the context of users' preferences for familiar images, the research aims to contribute insights into the practicality and effectiveness of these techniques in real-world scenarios. III. MATERIALS AND METHODS 1. 2. 3. 4. The research goal was to investigate the effect of using subject based images on the usability and security of recognition-based graphical authentication system. Focused on understanding the effect of using subject based images in enhancing the memorability of graphical authentication systems, particularly within users' academic disciplines. The study employs a combination of quantitative measures (success rates, login time) and qualitative data (user satisfaction) gathered from user feedback and perceptions through research questionnaires. To achieve the research objectives, lab-based studies were conducted to answer the following research questions in order to provide a deeper understanding of the user behavior, as well as to collect benchmarks and ideas for the development of future authentication systems: How does the memorability of graphical passwords based on subject based images compare to those based on abstract images? Will there be a significant difference in password creation time by users using subject based images compared to abstract images? What is the login failure rate for users attempting authentication with subject image-based passwords versus abstract image-based passwords? How do users perceive and prefer graphical passwords based on subject based or familiar images compared to those based on abstract images? Two graphical models were developed: the first model contains images from three disciplines of mathematics, computer science, and engineering as shown in fig. 3, fig. 4 and fig. 5. The © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 111 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 second model contains abstract images. A total of 50 participants were recruited from both staff and students, selected from the departments of computer science, mathematics, and engineering. All participants were introduced to the new system and its intended purpose. Before starting, participants answered demographic questions, including gender, age, and the number of familiar (chosen) images from their selected images after registration. User authentication behaviors and preferences are recorded and analyzed using basic statistical data analysis tools. Figure 3: Image Selection from Discipline of Mathematics Figure 4: Image Selection from Discipline of Computer Science © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 112 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 Figure 5: Image Selection from Discipline of Engineering 3.1 USABILITY METRICS Poet, (2012) suggests the means by which data can be efficiently captured for data analysis in the usability evaluation of graphical authentication systems. This research used this model in the implementation and evaluating user behaviors. Dependent variable 1. Effectiveness 2. Efficiency 3. User satisfaction Table 1: The Usability Metrics Behaviors to be measured Ease to remember Ease to remember Authentication time + Enrolment time Ease to recall Ease to find the authenticator image during authentication Preference of the user Method of measurement Questionnaire System log System log Questionnaire Questionnaire Questionnaire 3.2 EXPERIMENT PROCEDURE In the initial authentication session, each participant is tasked with generating a graphical password using one of the developed models. Subsequently, the participant logs into the system using the newly created password. The researcher requires only data pertaining to the success of user authentication across various authentication sessions. The participant is subsequently requested to return for a succeeding authentication session at a later date. Each participant undergoes a total of four login sessions. The initial login session occurs on the day the password is created, followed by the second session taking place two days after the first. The third login session is conducted one week after the second session, and finally, the fourth login session is completed two weeks after the third session. This gradual increase in time intervals is implemented to help understand the effects of time to long-term memory. © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 113 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 IV. RESULT AND DISCUSSION 4.1 LOGIN SUCCESS RATES Purpose: To measure how successfully participants can create and remember graphical passwords. The statistical analysis provides strong evidence that Subject-Based Graphical Authentication (SBGA) yields significantly higher login success rates compared to Abstract-Based Graphical Authentication (ABGA). This suggests that incorporating familiar images into the graphical authentication process enhances the chances of successful logins. Table 2: Login Success Rates Login Success Rates Model Type Means SBGA 86.7 ABGA 53.5 SD 2.99 8.35 P-V 0.001338 Figure 6: Login Success Rates Table 2 shows that the mean login success rate for SBGA (86.7) is notably higher than that for ABGA (53.5). This suggests that, on average, users in the SBGA group had a higher success rate in login compared to users in the ABGA group. The standard deviation gives an indication of the variability in the data. The lower standard deviation for SBGA (SD = 2.99) suggests that the login success rates in this group are less variable around the mean compared to the ABGA group (SD = 8.35). The pvalue of 0.001338 is less than the conventional significance level of 0.05. This indicates that there is a statistically significant difference in login success difference between SBGA and ABGA 4.2 PASSWORD CREATION TIME The statistical analysis indicates a significant difference in the time taken to create passwords between Subject Based Graphical Authentication (SBGA) and Abstract-Based Graphical Authentication (ABGA). On average, users in the SBGA group spent less time creating passwords compared to the ABGA group. Table 3: Password Creation Time Password Creation Time Model Type Means SD p-Value SBGA 6.125 1.312335 0.010323 ABGA 7.875 1.154701 © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 114 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 Figure 7: Password Creation Time On average, participants in the SBGA group as shown in Table 2 shows that it took less time (6.125 seconds) to create a password compared to participants in the ABGA group (7.875 seconds). This indicates a notable difference in the time required to create passwords between the two groups. The standard deviation for the SBGA group (1.312335) and ABGA group (1.154701) provides information about the variability in the time taken. The lower standard deviation for SBGA suggests less variability in the time taken to create passwords compared to ABGA. The pvalue of 0.010323 is less than the conventional significance level of 0.05. This suggests that there is a statistically significant difference in the time taken to create passwords between SBGA and ABGA. 4.3 NUMBER OF AUTHENTICATION ATTEMPTS The statistical analysis from Table 3 reveals a statistically significant difference in the mean number of authentication attempts between users in the ABGA and SBGA groups. On average, users in the SBGA group required fewer authentication attempts compared to the ABGA group. Table 4: Authentication Attempts Number of Authentication Attempts Model Type SBGA ABGA mean 1.25 2.50 sd 1.142609 1.258306 p-value 0.042948 On average, participants in the SBGA group required fewer authentication attempts (1.25) compared to participants in the ABGA group (2.50). This suggests a statistically significant difference in the efficiency of authentication between the two groups. The standard deviation for the SBGA group (1.1426091) and ABGA group (1.258306) provides information about the variability in the number of authentication attempts. The lower standard deviation for SBGA suggests less variability in the number of attempts compared to ABGA. The p-value of 0.042948 is less than the conventional significance level of 0.05. This indicates that there is a statistically significant difference in the number of authentication attempts between SBGA and ABGA. The findings as shown in Table 3 suggest that Subject-Based Graphical Authentication (SBGA) may offer a more efficient authentication process, as reflected in the significantly lower number of attempts required. This could have positive implications for user experience and system efficiency. © 2024, IJCSMC All Rights Reserved, ZAIN Publications, Fridhemsgatan 62, 112 46, Stockholm, Sweden 115 Hassan Umar Suru, International Journal of Computer Science and Mobile Computing, Vol.13 Issue.8, August- 2024, pg. 107-117 4.5 LOGIN FAILURE RATES Table 5: Login Failure Rates LOGIN FAILURE RATES Password Type Means SD P-value SBGA 13.3 0.5 0.000478 ABGA 46.7 3.8 The mean login failure rate for the Subject Based Graphical Authentication (SBGA) group is 13.3. The mean login failure rate for the Abstract Based Graphical Authentication (ABGA) is 46.7. The standard deviation for the SBGA group (0.5) and ABGA (3.8) provides information about the variability in the login failure rates. The lower standard deviation for SBGA suggests less variability in the failure rates compared to ABGA. The p-value of 0.000478 is less than the conventional significance level of 0.05. This indicates that there is a statistically significant difference in the login failure rates between SBGA and ABGA. V. CONCLUSION AND FUTURE WORK In exploring "Improving the Usability of Graphical Authentication Systems Using Subject Based Images" the study has uncovered valuable insights into the usability aspects of graphical password systems. The findings shed light on the significance of image familiarity in the user authentication process. The results indicate that graphical passwords created from familiar images demonstrate a higher level of memorability compared to those based on abstract images. Users, when given the choice, exhibited a preference for graphical passwords associated with images from their familiar surroundings, such as academic disciplines. This aligns with the idea that leveraging familiar imagery contributes positively to the user experience and may enhance the overall usability of recognition-based graphical authentication systems. While the study provides practical recommendations for system developers to consider incorporating familiar images into graphical password designs, certain limitations are acknowledged. These include the potential for sample bias, the short-term nature of the study, and the influence of learning effects. Future research endeavors should address these limitations by conducting longitudinal studies with diverse user populations to provide a more comprehensive understanding of the long-term impact of image familiarity on memorability. The study underscores the importance of user-centered design principles in the development of graphical authentication systems. By recognizing the role of image familiarity in enhancing memorability, system designers can work towards creating more user-friendly and effective authentication methods. 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