Pub Date : 2016-05-26DOI: 10.1109/ISBA.2016.7477235
Kat Krol, S. Parkin, M. Sasse
Biometric technologies have the potential to reduce the effort involved in securing personal activities online, such as purchasing goods and services. Verifying that a user session on a website is attributable to a real human is one candidate application, especially as the existing CAPTCHA technology is burdensome and can frustrate users. Here we examine the viability of biometrics as part of the consumer experience in this space. We invited 87 participants to take part in a lab study, using a realistic ticket-buying website with a range of human verification mechanisms including a face biometric technology. User perceptions and acceptance of the various security technologies were explored through interviews and a range of questionnaires within the study. The results show that some users wanted reassurance that their personal image will be protected or discarded after verifying, whereas others felt that if they saw enough people using face biometrics they would feel assured that it was trustworthy. Face biometrics were seen by some participants to be more suitable for high-security contexts, and by others as providing extra personal data that had unacceptable privacy implications.
{"title":"\"I don't like putting my face on the Internet!\": An acceptance study of face biometrics as a CAPTCHA replacement","authors":"Kat Krol, S. Parkin, M. Sasse","doi":"10.1109/ISBA.2016.7477235","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477235","url":null,"abstract":"Biometric technologies have the potential to reduce the effort involved in securing personal activities online, such as purchasing goods and services. Verifying that a user session on a website is attributable to a real human is one candidate application, especially as the existing CAPTCHA technology is burdensome and can frustrate users. Here we examine the viability of biometrics as part of the consumer experience in this space. We invited 87 participants to take part in a lab study, using a realistic ticket-buying website with a range of human verification mechanisms including a face biometric technology. User perceptions and acceptance of the various security technologies were explored through interviews and a range of questionnaires within the study. The results show that some users wanted reassurance that their personal image will be protected or discarded after verifying, whereas others felt that if they saw enough people using face biometrics they would feel assured that it was trustworthy. Face biometrics were seen by some participants to be more suitable for high-security contexts, and by others as providing extra personal data that had unacceptable privacy implications.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130160785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-01DOI: 10.1109/ISBA.2016.7477229
Fatimah Abdulsattar, J. Carter
In real security scenarios, gait data may be highly distorted due to perspective effects and there may be significant change in appearance, orientation and occlusion between different measurements. To deal with this problem, a new identification technique is proposed by reconstructing 3D models of the walking subject, which are then used to identify subject images from an arbitrary camera. 3D models in one gait cycle are aligned to match silhouettes in a 2D gait cycle by estimating the positions of a 3D and 2D gait cycles in a 3D space. This allows the gait data in a gallery and probe share the same appearance, perspective and occlusion. Generic Fourier Descriptors are used as gait features. The performance is evaluated using a new collected dataset of 17 subjects walking in a narrow walkway. A Correct Classification Rate of 98.8% is achieved. This high recognition rate has still been achieved using a modest number of features. The analysis indicate that the technique can handle truncated gait cycles of different length and is insensitive to noisy silhouettes. However, calibration errors have a negative impact upon recognition performance.
{"title":"Performance analysis of gait recognition with large perspective distortion","authors":"Fatimah Abdulsattar, J. Carter","doi":"10.1109/ISBA.2016.7477229","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477229","url":null,"abstract":"In real security scenarios, gait data may be highly distorted due to perspective effects and there may be significant change in appearance, orientation and occlusion between different measurements. To deal with this problem, a new identification technique is proposed by reconstructing 3D models of the walking subject, which are then used to identify subject images from an arbitrary camera. 3D models in one gait cycle are aligned to match silhouettes in a 2D gait cycle by estimating the positions of a 3D and 2D gait cycles in a 3D space. This allows the gait data in a gallery and probe share the same appearance, perspective and occlusion. Generic Fourier Descriptors are used as gait features. The performance is evaluated using a new collected dataset of 17 subjects walking in a narrow walkway. A Correct Classification Rate of 98.8% is achieved. This high recognition rate has still been achieved using a modest number of features. The analysis indicate that the technique can handle truncated gait cycles of different length and is insensitive to noisy silhouettes. However, calibration errors have a negative impact upon recognition performance.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131536480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477227
D. Morocho, A. Morales, Julian Fierrez, R. Vera-Rodríguez
This work explores human-assisted schemes for improving automatic signature recognition systems. We present a crowdsourcing experiment to establish the human baseline performance for signature recognition tasks and a novel attribute-based semi-automatic signature verification system inspired in FDE analysis. We present different experiments over a public database and a self-developed tool for the manual annotation of signature attributes. The results demonstrate the benefits of attribute-based recognition approaches and encourage to further research in the capabilities of human intervention to improve the performance of automatic signature recognition systems.
{"title":"Towards human-assisted signature recognition: Improving biometric systems through attribute-based recognition","authors":"D. Morocho, A. Morales, Julian Fierrez, R. Vera-Rodríguez","doi":"10.1109/ISBA.2016.7477227","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477227","url":null,"abstract":"This work explores human-assisted schemes for improving automatic signature recognition systems. We present a crowdsourcing experiment to establish the human baseline performance for signature recognition tasks and a novel attribute-based semi-automatic signature verification system inspired in FDE analysis. We present different experiments over a public database and a self-developed tool for the manual annotation of signature attributes. The results demonstrate the benefits of attribute-based recognition approaches and encourage to further research in the capabilities of human intervention to improve the performance of automatic signature recognition systems.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123905992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477242
S. Burg, Pranav Channakeshava, O. Bringmann
To protect data against theft from Trojan horses, some of the common approaches like End-to-End Encryption fail to counter such malicious attempts as they do not account for vulnerabilities of the user's endpoint. Any data which is decrypted on the endpoint, can become visible to attackers. A technique that can prevent this dataloss is by employing encryption in the pixel-domain and using additional hardware to decrypt the graphics-stream. This is done by End-to-Display Encryption, which decrypts the data between the endpoint and the display, ensuring that the data-at-rest is always encrypted. In this paper, we present a linebased encryption method for a more user-friendly and improved End-to-Display Encryption design, which can be used to effectively counter corporate espionage by providing secure access to confidential documents.
{"title":"Linebased end-to-display encryption for secure documents","authors":"S. Burg, Pranav Channakeshava, O. Bringmann","doi":"10.1109/ISBA.2016.7477242","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477242","url":null,"abstract":"To protect data against theft from Trojan horses, some of the common approaches like End-to-End Encryption fail to counter such malicious attempts as they do not account for vulnerabilities of the user's endpoint. Any data which is decrypted on the endpoint, can become visible to attackers. A technique that can prevent this dataloss is by employing encryption in the pixel-domain and using additional hardware to decrypt the graphics-stream. This is done by End-to-Display Encryption, which decrypts the data between the endpoint and the display, ensuring that the data-at-rest is always encrypted. In this paper, we present a linebased encryption method for a more user-friendly and improved End-to-Display Encryption design, which can be used to effectively counter corporate espionage by providing secure access to confidential documents.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133873051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477248
Yong Qi, Ya Zhou, Chang Zhou, Xinran Hu, Xiaoming Hu
Traditional vein recognition technology is usually based on the 2D infrared images of hand vein. However, the hand vein patterns extracted from 2D images are seriously distorted with hand posture changes. A point cloud matching vein recognition system based on Kernel Correlation(KC) algorithm is designed, which provides a new perspective to hand vein recognition but also suffers from posture change because KC value is sensitive to coordinate shift. In this paper, a vein point cloud registration algorithm is proposed to improve the vein authentication under multi-pose. Experiments show that the point cloud registration algorithm can effectively improve the recognition rate. After the point cloud registration, when the hand posture changes limited to the range ± 20 degrees, the system can keep more than 90% recognition rate, the corresponding error rate is only 4%.
{"title":"Vein point cloud registration algorithm for multi-pose hand vein authentication","authors":"Yong Qi, Ya Zhou, Chang Zhou, Xinran Hu, Xiaoming Hu","doi":"10.1109/ISBA.2016.7477248","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477248","url":null,"abstract":"Traditional vein recognition technology is usually based on the 2D infrared images of hand vein. However, the hand vein patterns extracted from 2D images are seriously distorted with hand posture changes. A point cloud matching vein recognition system based on Kernel Correlation(KC) algorithm is designed, which provides a new perspective to hand vein recognition but also suffers from posture change because KC value is sensitive to coordinate shift. In this paper, a vein point cloud registration algorithm is proposed to improve the vein authentication under multi-pose. Experiments show that the point cloud registration algorithm can effectively improve the recognition rate. After the point cloud registration, when the hand posture changes limited to the range ± 20 degrees, the system can keep more than 90% recognition rate, the corresponding error rate is only 4%.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129476758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477245
Bharath Subramanyam, Piyush Joshi, M. Meena, S. Prakash
Quality of an image plays a fundamental role in taking vital decisions. In various walks of life, one such decision is personal identification. Hence, it's assessment is essential prior to using it in many biometric applications such as face recognition, iris, fingerprint analysis etc. The proposed technique classifies images into four classes based on their illumination and contrast quality. Then, the proposed technique chooses the most suitable enhancement technique for particular class to get best possible image. The proposed technique has been experimented on the Yale B database and the results obtained are 97.14% accurate on an average in terms of the correct classification of images into the appropriate classes. In another experiment where 50 random images of 30 random subjects were selected and this process repeated over 10 times, the classifier was 99.17% accurate in classifying the images.
{"title":"Quality based classification of images for illumination invariant face recognition","authors":"Bharath Subramanyam, Piyush Joshi, M. Meena, S. Prakash","doi":"10.1109/ISBA.2016.7477245","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477245","url":null,"abstract":"Quality of an image plays a fundamental role in taking vital decisions. In various walks of life, one such decision is personal identification. Hence, it's assessment is essential prior to using it in many biometric applications such as face recognition, iris, fingerprint analysis etc. The proposed technique classifies images into four classes based on their illumination and contrast quality. Then, the proposed technique chooses the most suitable enhancement technique for particular class to get best possible image. The proposed technique has been experimented on the Yale B database and the results obtained are 97.14% accurate on an average in terms of the correct classification of images into the appropriate classes. In another experiment where 50 random images of 30 random subjects were selected and this process repeated over 10 times, the classifier was 99.17% accurate in classifying the images.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128638514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477228
Soumik Mondal, Patrick A. H. Bours
In this paper, we analyze the performance of a continuous user authentication and identification system for a PC under various analysis techniques. We applied a novel identification technique called Pairwise User Coupling (PUC) on our own dataset for the analysis. This dataset is a combination of keystroke and mouse usage behaviour data. We obtained an identification accuracy of 62.2% for a closed-set experiment, where the system needs on average of 471 actions to detect an impostor. In case of an open-set experiment the Detection and Identification Rate (DIR) of 58.9% was obtained, where the system needs on average of 333 actions to detect an impostor.
{"title":"Combining keystroke and mouse dynamics for continuous user authentication and identification","authors":"Soumik Mondal, Patrick A. H. Bours","doi":"10.1109/ISBA.2016.7477228","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477228","url":null,"abstract":"In this paper, we analyze the performance of a continuous user authentication and identification system for a PC under various analysis techniques. We applied a novel identification technique called Pairwise User Coupling (PUC) on our own dataset for the analysis. This dataset is a combination of keystroke and mouse usage behaviour data. We obtained an identification accuracy of 62.2% for a closed-set experiment, where the system needs on average of 471 actions to detect an impostor. In case of an open-set experiment the Detection and Identification Rate (DIR) of 58.9% was obtained, where the system needs on average of 333 actions to detect an impostor.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128928791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477226
Vijay Kumar, Ramachandra Raghavendra, A. Namboodiri, C. Busch
Transgender face recognition is gaining increasing attention in the face recognition community because of its potential in real life applications. Despite extensive progress in traditional face recognition domain, it is very challenging to recognize faces under transgender setting. The gender transformation results in significant face variations, both in shape and texture gradually over time. This introduces additional complexities to existing face recognition algorithms to achieve a reliable performance. In this paper, we present a novel framework that incorporates appearance factor and a transformation factor caused due to Hormone Replacement Therapy (HRT) for recognition. To this extent, we employ the Hidden Factor Analysis (HFA) to jointly model a face under therapy as a linear combination of appearance and transformation factors. This is based on the intuition that the appearance factor captures the features that are unaffected by the therapy and transformation factor captures the feature changes due to therapy. Extensive experiments carried out on publicly available HRT transgender face database shows the efficacy of the proposed scheme with a recognition accuracy of 82.36%.
{"title":"Robust transgender face recognition: Approach based on appearance and therapy factors","authors":"Vijay Kumar, Ramachandra Raghavendra, A. Namboodiri, C. Busch","doi":"10.1109/ISBA.2016.7477226","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477226","url":null,"abstract":"Transgender face recognition is gaining increasing attention in the face recognition community because of its potential in real life applications. Despite extensive progress in traditional face recognition domain, it is very challenging to recognize faces under transgender setting. The gender transformation results in significant face variations, both in shape and texture gradually over time. This introduces additional complexities to existing face recognition algorithms to achieve a reliable performance. In this paper, we present a novel framework that incorporates appearance factor and a transformation factor caused due to Hormone Replacement Therapy (HRT) for recognition. To this extent, we employ the Hidden Factor Analysis (HFA) to jointly model a face under therapy as a linear combination of appearance and transformation factors. This is based on the intuition that the appearance factor captures the features that are unaffected by the therapy and transformation factor captures the feature changes due to therapy. Extensive experiments carried out on publicly available HRT transgender face database shows the efficacy of the proposed scheme with a recognition accuracy of 82.36%.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129126424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477232
I. Patil, Shruti Bhilare, Vivek Kanhangad
This paper investigates vulnerability of the dorsal hand-vein biometric systems to display based presentation attacks. The database collected for our experiments consists of624 real and 312 spoof images from left and right hands of 52 subjects, of which 32 are males and 20 are females. In order to assess the vulnerability of the system, we have created artefacts in a more realistic scenario assuming no access to real images in the database. Specifically, a smart-phone camera is used to capture user's hand images, which are then displayed on its screen and presented to the biometric sensor as artefacts. Scale invariant feature transform (SIFT) based image descriptors are employed for image matching. For detection of keypoints, we have considered three techniques, namely, difference of Gaussian (DoG), Harris-Laplace and Hessian-Laplace and performed comparative assessment of vulnerability. Worst-case vulnerability of these approaches in terms of spoof false acceptance rate (SFAR) has been found to be 61.8%, 46.1% and 49.03%, respectively. SFAR values obtained in our experiments are too high to be acceptable for real-world deployments and indicate that dorsal hand-vein biometric systems are also vulnerable to spoofing attacks.
{"title":"Assessing vulnerability of dorsal hand-vein verification system to spoofing attacks using smartphone camera","authors":"I. Patil, Shruti Bhilare, Vivek Kanhangad","doi":"10.1109/ISBA.2016.7477232","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477232","url":null,"abstract":"This paper investigates vulnerability of the dorsal hand-vein biometric systems to display based presentation attacks. The database collected for our experiments consists of624 real and 312 spoof images from left and right hands of 52 subjects, of which 32 are males and 20 are females. In order to assess the vulnerability of the system, we have created artefacts in a more realistic scenario assuming no access to real images in the database. Specifically, a smart-phone camera is used to capture user's hand images, which are then displayed on its screen and presented to the biometric sensor as artefacts. Scale invariant feature transform (SIFT) based image descriptors are employed for image matching. For detection of keypoints, we have considered three techniques, namely, difference of Gaussian (DoG), Harris-Laplace and Hessian-Laplace and performed comparative assessment of vulnerability. Worst-case vulnerability of these approaches in terms of spoof false acceptance rate (SFAR) has been found to be 61.8%, 46.1% and 49.03%, respectively. SFAR values obtained in our experiments are too high to be acceptable for real-world deployments and indicate that dorsal hand-vein biometric systems are also vulnerable to spoofing attacks.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131229674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1109/ISBA.2016.7477234
Ramón Blanco-Gonzalo, R. Sánchez-Reillo, Carlos Sanchez-Redondo, Jose Luis Alonso-Aguilera
Biometric recognition systems have highlighted the possibility of easily performing common actions (which require personal authentication) to those users with accessibility concerns. Nevertheless, this topic has not been deeply studied yet and there are only a few previous researches in this line. In this work, we have evaluated the accessibility of a mobile app for making payments using fingerprint and handwritten signature as authentication mechanisms. Several people with accessibility concerns (physical and mental) have used this app and provided valuable feedback according to their needs. Our findings suggest that people requirements are highly subject dependent. On the other hand, in addition to the recently published EN 301 549, proper accessibility evaluation mechanisms for biometric recognition are required in order to cover the specific features of biometric recognition systems.
{"title":"Accessibility evaluation of a mobile biometric recognition system","authors":"Ramón Blanco-Gonzalo, R. Sánchez-Reillo, Carlos Sanchez-Redondo, Jose Luis Alonso-Aguilera","doi":"10.1109/ISBA.2016.7477234","DOIUrl":"https://doi.org/10.1109/ISBA.2016.7477234","url":null,"abstract":"Biometric recognition systems have highlighted the possibility of easily performing common actions (which require personal authentication) to those users with accessibility concerns. Nevertheless, this topic has not been deeply studied yet and there are only a few previous researches in this line. In this work, we have evaluated the accessibility of a mobile app for making payments using fingerprint and handwritten signature as authentication mechanisms. Several people with accessibility concerns (physical and mental) have used this app and provided valuable feedback according to their needs. Our findings suggest that people requirements are highly subject dependent. On the other hand, in addition to the recently published EN 301 549, proper accessibility evaluation mechanisms for biometric recognition are required in order to cover the specific features of biometric recognition systems.","PeriodicalId":198009,"journal":{"name":"2016 IEEE International Conference on Identity, Security and Behavior Analysis (ISBA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129548729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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