ShouldAR: Detecting Shoulder Surfing Attacks Using Multimodal Eye Tracking and Augmented Reality

비밀번호를 입력하는 과정에서 가장 큰 보안 위협은 비밀번호를 훔쳐보는 것이다. 비밀번호 훔쳐보기는 비밀번호를 입력하는 과정을 옆에서 지켜보고 비밀번호를 획득하려고 하는 행위로서 비밀번호를 획득하는 가장 전통적인 방법이며 강력한 보안 위협이다. 본 논문에서는 인지심리학에 기초한 비밀번호 훔쳐보기로부터 안전한 기술인 역동 인증 체계(DAS)라 불리는 비밀번호 입력 기술을 제안하였다. 그리고 제안한 역동 인증 체계의 비밀번호 훔쳐보기에 대한 안전성을 직관적인 관점, 훔쳐보기 실험, 이론적인 분석으로 구분하여 검증하였다. 비밀번호 훔쳐보기로부터 안정성이 입증된 역동 인증 체계를 내장시킨 비밀번호 입력기를 설계하여 구현하였다. 구현한 비밀번호 입력기는 일반 패스워드 입력방식 보다 훔쳐보기 공격자의 비밀번호 획득 확률을 현저하게 낮출 수 있으므로 은행에서 운영하는 금융자동화기기에 적용 및 운영되기에 적합한 것으로 평가를 받아 금융기관에서 도입하여 활용되고 있다. When entering the PIN(personal identification number), the greatest security threat is shoulder surfing attack. Shoulder surfing attack is watching the PIN being entered from over the shoulder to obtain the number, and it is the most common and at the same time the most powerful security threat of stealing the PIN. In this paper, a psychology based PINpad technology referred to as DAS(Dynamic Authentication System) that safeguards from shoulder surfing attack was proposed. Also, safety of the proposed DAS from shoulder surfing attack was tested and verified through intuitive viewpoint, shoulder surfing test, and theoretical analysis. Then, a PINpad with an internal DAS that was certified for its safety from shoulder surfing attack was designed and produced. Because the designed PINpad significantly decreases the chances for shoulder surfing attackers being able to steal the PIN when compared to the ordinary PINpad, it was determined to be suitable for use at ATM(automated teller machine)s operated by banks and therefore has been introduced and is being used by many financial institutions.

Authentication based on biometric provides various advantages in ATMs (Automated Teller Machine) systems. The weakness of existing authentication scheme in ATM is the usage of PIN (Personal Identification Number) numbers as password. Because PIN numbers are easily traceable and misused. In order to achieve security and to overcome these illegal activities, our proposed system is developed to provide better security to the ATMs. Here, the PIN numbers are replaced with biometric security. The main objective of the work is to eliminate the use of ATM cards completely and to ensure better security. In this proposal, we provide the idea of using Aadhaar number as user ID and fingerprint as password. After biometric verification, the user will be allowed to proceed with the transaction. In case of three successive wrong attempts, the account will be blocked.

Providing security to bank customers is the prime responsibility of banking institutions. These institutions upgrade their services to provide convenience-based banking exposure. Automatic Teller Machines (ATMs) assist the bank's customers to operate independently. ATMs verify the authenticity of the user through a 4-digit personal identification number (PIN) only. The State Bank of India (SBI) has initiated a double security check system to minimize the probabilities of banking frauds through ATMs. SBI customers must provide a one-time password (OTP) along with a PIN to complete the cash withdrawal transaction through the SBI ATM. The objective of the study is to analyze the impact of financial security enhancement in ATMs cash transactions through one-time password on the probabilities of banking frauds through ATMs. The study has used primary data collected through a questionnaire from 422 respondents. The study resulted that one-time password has enhanced the financial security function of ATMs and now the probabilities of ATM frauds has been reduced substantially.

In recent years, Automated Teller Machines (ATMs) are witnessed as the most widely used gadgets which required personal identification numbers (PINs) for authentication along with ATM cards. But PINs are suspected of many threats like a man-in-the-middle attack, spoofing, and eavesdropping, etc., which can affect secure and private information. In this paper, we present a novel secure authentication system for ATMs. In this paper, we replace ATM card with facial expression authentication and makes ATMs intelligent enough to recognize users and give them access to their accounts. Replacement of cards will solve the current problem of skimming data from cards with the use of skimmers.

Extended-Reality Technologies: An Overview of Emerging Applications in Medical Education and Clinical Care.

ObjectiveApps promoting patient self-management may improve health outcomes. However, methods to secure stored information on mobile devices may adversely affect usability. We tested the reliability and usability of common user authentication techniques in younger and older adults.MethodologyUsability testing was conducted in two age groups, 18 to 30 years and 50 years and older. After completing a demographic questionnaire, each participant tested four authentication options in random order: four-digit personal identification number (PIN), graphical password (GRAPHICAL), Android pattern-lock (PATTERN), and a swipe-style Android fingerprint scanner (FINGERPRINT). Participants rated each option using the Systems Usability Scale (SUS).ResultsA total of 59 older and 43 younger participants completed the study. Overall, PATTERN was the fastest option (3.44s), and PIN had the fewest errors per attempt (0.02). Participants were able to login using PIN, PATTERN, and GRAPHICAL at least 98% of the time. FINGERPRINT was the slowest (26.97s), had an average of 1.46 errors per attempt, and had a successful login rate of 85%. Overall, PIN and PATTERN had higher SUS scores than FINGERPRINT and GRAPHICAL. Compared to younger participants, older participants were also less likely to find PATTERN to be tiring, annoying or time consuming and less likely to consider PIN to be time consuming. Younger participants were more likely to rate GRAPHICAL as annoying, time consuming and tiring than older participants.ConclusionsOn mobile devices, PIN and pattern-lock outperformed graphical passwords and swipe-style fingerprints. All participants took longer to authenticate using the swipe-style fingerprint compared to other options. Older participants also took two to three seconds longer to authenticate using the PIN, pattern and graphical passwords though this did not appear to affect perceived usability.

PurposeWith its potential to significantly improve the tourism sector, augmented reality (AR), an emerging technology, is a growing force in the field. It has attracted significant academic attention and expanded publishing options over the past 20 years. However, so far, no review has provided a comprehensive overview of AR-related research in tourism. This work uses the VOS Viewer and Bibliometrix R-package software to present a bibliometric review of the scientific literature in the area of AR-related tourism research in order to fill this gap.Design/methodology/approachThe theme of AR in tourism was searched in the Scopus database. The original search yielded 327 papers in total, which were then filtered based on the parameters. A total of 190 relevant documents were generated by the refining process. For the publications pertaining to AR in tourism, the most cited papers, prominent authors, productive journals and countries, co-authorship among countries, trending topics, thematic map, co-occurrence analysis of keywords and bibliographic coupling of documents were all looked into.FindingsThis report shows a recent rise in research on AR in the tourism industry. The top 10 studies in the topic had a combined total of 1749 citations, while the authors found three papers with more than 200 Scopus citations. Till the date of extraction, 555 writers have contributed to the field of AR in tourism, with Tom Dieck M.C., Chung N. and Jung T. receiving the most citations. According to co-authorship analysis, the UK collaborates with other countries the most. Thematic map has thrown insight into the niche themes and emerging themes in the field. Coupling analysis has revealed four major research streams in the field of AR in tourism.Research limitations/implicationsThis study can be considered as a first study to utilize a bibliometric method to address this research gap, identifying the top documents, journals and, most importantly, the future research areas identified through the thematic map analysis of keywords and bibliographic coupling.Practical implicationsHistorical growth within this discipline was made clear by an in-depth analysis of the studied themes in this area. Hence, the discovery of relatively new subjects offers scholars the chance to plan their research in this area and thereby enhance the literature. The study is also beneficial for practitioners in the tourism industry.Originality/valueThis work examined previously published publications on AR in tourism using a bibliometric analytic technique. Additionally, it contributes to the current knowledge accumulation in learning about the applicability of AR in tourism and enlightens tourism scholars on the structure of the field.

With the increase of automated teller machine (ATM) frauds, new authentication mechanisms are developed to overcome security problems of personal identification numbers (PIN). Those mechanisms are usually judged on speed, security, and memorability in comparison with traditional PIN entry systems. It remains unclear, however, what appropriate values for PIN-based ATM authentication actually are. We conducted a field study and two smaller follow-up studies on real-world ATM use, in order to provide both a better understanding of PIN-based ATM authentication, and on how alternative authentication methods can be compared and evaluated. Our results show that there is a big influence of contextual factors on security and performance in PIN-based ATM use. Such factors include distractions, physical hindrance, trust relationships, and memorability. From these findings, we draw several implications for the design of alternative ATM authentication systems, such as resilience to distraction and social compatibility.

People enjoy the convenience of on-line services, but online environments may bring many risks. We propose a virtual password concept involving a small amount of human computing to secure users’ passwords in on-line environments. We adopt user determined randomized linear generation functions to secure users’ passwords based on the fact that a server has more information than any adversary does. We analyze how the proposed scheme defends against phishing, key logger, and shoulder-surfing attacks. To the best of our knowledge, our virtual password mechanism is the first one which is able to defend against all three attacks together. In this work, we discussed how to prevent users’ passwords from being stolen by adversaries. We proposed a virtual password concept involving a small amount of human computing to secure users’ passwords in on-line environments. We also implemented the system to do some tests and survey feedback indicates the feasibility of such a system. In this paper, we discuss how to prevent users’ passwords from being stolen by adversaries in online environments and automated teller machines. We propose differentiated virtual password mechanisms in which a user has the freedom to choose a virtual password scheme ranging from weak security to strong security, where a virtual password requires a small amount of human computing to secure users’ passwords. Among the schemes, we have a default method (i.e., traditional password scheme), system recommended functions, user-specified functions, user-specified programs, and so on. A function/program is used to implement the virtual password concept with a tradeoff of security for complexity requiring a small amount of human computing

An automated teller machine (ATM) is an electronic device that allows customers of a financial institution to access their account and to perform financial transactions such as checking their account balance and withdrawing cash without the need for a bank teller. The customer is issued with a plastic card with a magnetic stripe (or a chip) that contains a card number and security information that uniquely identifies the customer. The customer inserts the card into the machine and enters the personal identification number (PIN), which must match the PIN stored in the card. There are several million ATMs in use around the world.

Access management of IoT devices is extremely important, and a secure login authentication scheme can effectively protect users’ privacy. However, traditional authentication schemes are threatened by shoulder-surfing attacks, and biometric-based schemes, such as fingerprint recognition and face recognition, that are commonly used today can also be cracked. Researchers have proposed some schemes for current attacks, but they are limited by usability. For example, the login authentication process requires additional device support. This method solves the problem of attacks, but it is unusable, which limits its application. At present, most authentication schemes for the Internet of Things and mobile platforms either focus on security, thus ignoring availability, or have excellent convenience but insufficient security. This is a symmetry problem worth exploring. Therefore, users need a new type of login authentication scheme that can balance security and usability to protect users’ private data or maintain device security. In this paper, we propose a login authentication scheme named PinWheel, which combines a textual password, a graphical password, and biometrics to prevent both shoulder-surfing attacks and smudge attacks and solves the current schemes’ lack of usability. We implemented PinWheel and evaluated it from the perspective of security and usability. The experiments required 262 days, and 573 subjects participated in our investigation. The evaluation results show that PinWheel can at least effectively resist both mainstream attacks and is superior to most existing schemes in terms of usability.

Augmented Reality (AR) smart glasses strengthen user interaction by merging real-world visuals with digital information. This study explores the impact of wearability, usability, and social influence on the feeling of groundedness and purchase intentions for AR smart glasses moderated by privacy concerns. Text mining and PLS-SEM were employed to analyze 3,164 Amazon smart glasses online reviews. Results suggest that the feeling of groundedness is influenced by usability and social influence, while wearability showed no significant effect. Privacy concerns moderate the relationship between groundedness and purchase intentions, emphasizing the need for privacy measures to improve user trust. These findings suggest that AR smart glasses create meaningful connections for users, affecting their preferences, choices, and willingness to pay.

BackgroundChallenges in emergency medicine include overcrowding, insufficient emergency care resources, and extended emergency department (ED) waiting times. These issues contribute to delays in treatment and unfavorable outcomes. This situation worsens in events with large crowds and particularly worsened during the COVID-19 pandemic. The integration of augmented reality (AR) smart glasses could potentially enhance patient care in the ED.ObjectiveThis study aims to assess the effectiveness of AR smart glasses in reducing patient care time in the ED during the 19th Asian Games and the Fourth Asian Para Games Hangzhou 2022 (HAG2022). The study specifically compares the prepreparation time (PPT) and consult response time (CRT) in patients receiving teleconsultations via AR smart glasses versus those receiving standard care without AR.MethodsThis retrospective study was conducted between September 13, 2023, and October 28, 2023, during HAG2022. The data were gathered from AR smart glasses using 5G technology at the HAG2022 village and electronic health records at Sir Run Run Shaw Hospital, China. The study included 2 groups: the teleconsultation by augmented reality telemedicine system (ARTS) group and the non-ARTS group. The main data assessed were PPT and CRT in ED.ResultsDuring the research period, 80 patients were divided into 2 cohorts: the ARTS cohort (n=10) and the non-ARTS cohort (n=70). Gender and age demographics showed no significant differences between the cohorts. The ARTS cohort had a significantly lower average PPT of 23 minutes compared to the non-ARTS cohort’s 40.3 minutes (P<.001). In addition, CRT in the ARTS cohort was significantly lower at 15.6 minutes compared to the non-ARTS cohort’s 164.8 minutes (P=.03). The outcomes suggest that smart glasses are effective in decreasing PPT and CRT.ConclusionsAR smart glasses have the potential to enhance patient admission efficiency and reduce care time in EDs. However, despite these benefits, further research is needed to confirm their effectiveness, and additional studies are essential to identify the challenges and barriers to their successful implementation in emergency medicine.

The increasing reliance on Automated Teller Machines (ATMs) has highlighted the urgent need for advanced authentication mechanisms to safeguard user transactions against fraud and unauthorized access. However, traditional methods such as Personal Identification Numbers (PINs) and passwords remain vulnerable to attacks, while unimodal biometric systems face challenges of inter-class variance, environmental interference, and non-universality. Specifically, single-modality approaches and conventional ATM cameras fall short in capturing reliable biometric features under varying conditions, while the effectiveness of bimodal approaches in such environments has not been adequately investigated. Therefore, this study developed a bimodal biometric authentication system integrating face and iris recognition with Gray Level Co-Occurrence Matrix (GLCM) for enhanced ATM security. The system leverages GLCM for powerful texture feature extraction from both modalities, capturing intricate spatial relationships that are difficult to spoof. The extracted feature vectors were used to train Support Vector Machines (SVM) with a Radial Basis Function (RBF) kernel as classifiers for both face and iris recognition. The final authentication decision was made using Boolean OR rule fusion. The system achieved a remarkable accuracy of 98.2%, with a False Acceptance Rate (FAR) of 1.8% and a False Rejection Rate (FRR) of 1.2%. These results demonstrably outperformed comparable unimodal systems and existing biometric ATMs, validating the proposed framework as a highly secure and efficient solution for financial authentication systems.

Nowadays we are experiencing a radical increase in skimming in the Automated Teller Machine (ATM) systems. So, actuation in advancement and security of the ATM machines is required.An automated teller machine (ATM) is an electronic telecommunications device that helps customers of banking departments in transactions and transfer of money in their accounts. The customer enters their unique personal identification number (PIN), i.e. stored in the chip of the card. Due to an increase in the installation of ATM and the number of ATM cardholders, the number of cases of fraudulence has also increased radically. The advancement in technology has resulted in an increase in various skimming activities.So, developments are incorporated in the existing systems to make it more secure, convenient and reliable. The employed secured system must have high speed and must be durable. The presented design is unique because of biometric scanners such as Iris scanner and the two-way check with fingerprint scanner makes it more reliable. The iris scanner being the primary security check lets the system access the further steps for transaction. Fingerprint scanner embedded in the ATM card acts as the secondary security check for the system. The transaction procedure is successful only if the input data by the card holder matches with the database. It consumes less energy that makes it suitable for use. The suggested modified system is pragmatic moreover economical when correlating to the alternative existing classification and affirmation processes of ATMs.