939 research outputs found

    Improving the Security of Mobile Devices Through Multi-Dimensional and Analog Authentication

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    Mobile devices are ubiquitous in today\u27s society, and the usage of these devices for secure tasks like corporate email, banking, and stock trading grows by the day. The first, and often only, defense against attackers who get physical access to the device is the lock screen: the authentication task required to gain access to the device. To date mobile devices have languished under insecure authentication scheme offerings like PINs, Pattern Unlock, and biometrics-- or slow offerings like alphanumeric passwords. This work addresses the design and creation of five proof-of-concept authentication schemes that seek to increase the security of mobile authentication without compromising memorability or usability. These proof-of-concept schemes demonstrate the concept of Multi-Dimensional Authentication, a method of using data from unrelated dimensions of information, and the concept of Analog Authentication, a method utilizing continuous rather than discrete information. Security analysis will show that these schemes can be designed to exceed the security strength of alphanumeric passwords, resist shoulder-surfing in all but the worst-case scenarios, and offer significantly fewer hotspots than existing approaches. Usability analysis, including data collected from user studies in each of the five schemes, will show promising results for entry times, in some cases on-par with existing PIN or Pattern Unlock approaches, and comparable qualitative ratings with existing approaches. Memorability results will demonstrate that the psychological advantages utilized by these schemes can lead to real-world improvements in recall, in some instances leading to near-perfect recall after two weeks, significantly exceeding the recall rates of similarly secure alphanumeric passwords

    Biometrics in schools: the role of authentic and inauthentic social transactions

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    Biometrics have always been part of the social world, but it is only recently that we have moved from an instinctive human model of recognition to a digital one. Recent scientific developments in the field have been capitalised upon by the commercial sector and exploited in various respects by school administration systems, with biometrics becoming comparatively widespread in UK and US schools. This brings both advantages and disadvantages as biometrics begin to change the fundamental relationship between institutions and the children in their care. This paper discusses the current state of research in terms of biometrics and social identity, the impact of commercial pressures to adopt biometric systems, and the growing relationship with data privacy issues. It analyses potential problems surrounding unproblematic adoption, and discusses how this might inform future data privacy policies. Additionally, in the paper, I identify three key social issues relating to biometric use in schools, and offer a theory of social exchange, building on the work of Homans. This includes a classification of authentic versus inauthentic transations, in the democratic sense. Finally, the paper identifies biometrics as an area of social (and legal) risk for the future

    Biometrics in Schools

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    Biometrics have always been part of the social world, but it is only recently that we have moved from an instinctive human model to a digital one. Anyone who has been a school student will be aware that, along with eyes in the back of their heads, teachers are supposed to have a mythical sixth sense that means they are able to smell potential trouble a mile off, or identify potential culprits by individual gaits as they attempt to escape. Teachers have also long been regarded as societal experts in identifying homework and examination cheating, in the form of informally analysing patterns of handwriting and pencil use, as those of us who have attended school ourselves may recall. However identification techniques in school are currently in a process of being corporatised and commoditised, with biometric technologies being at the forefront of these developments. This chapter discusses the social and theoretical context for such change

    Accessible On-Body Interaction for People With Visual Impairments

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    While mobile devices offer new opportunities to gain independence in everyday activities for people with disabilities, modern touchscreen-based interfaces can present accessibility challenges for low vision and blind users. Even with state-of-the-art screenreaders, it can be difficult or time-consuming to select specific items without visual feedback. The smooth surface of the touchscreen provides little tactile feedback compared to physical button-based phones. Furthermore, in a mobile context, hand-held devices present additional accessibility issues when both of the users’ hands are not available for interaction (e.g., on hand may be holding a cane or a dog leash). To improve mobile accessibility for people with visual impairments, I investigate on-body interaction, which employs the user’s own skin surface as the input space. On-body interaction may offer an alternative or complementary means of mobile interaction for people with visual impairments by enabling non-visual interaction with extra tactile and proprioceptive feedback compared to a touchscreen. In addition, on-body input may free users’ hands and offer efficient interaction as it can eliminate the need to pull out or hold the device. Despite this potential, little work has investigated the accessibility of on-body interaction for people with visual impairments. Thus, I begin by identifying needs and preferences of accessible on-body interaction. From there, I evaluate user performance in target acquisition and shape drawing tasks on the hand compared to on a touchscreen. Building on these studies, I focus on the design, implementation, and evaluation of an accessible on-body interaction system for visually impaired users. The contributions of this dissertation are: (1) identification of perceived advantages and limitations of on-body input compared to a touchscreen phone, (2) empirical evidence of the performance benefits of on-body input over touchscreen input in terms of speed and accuracy, (3) implementation and evaluation of an on-body gesture recognizer using finger- and wrist-mounted sensors, and (4) design implications for accessible non-visual on-body interaction for people with visual impairments

    Open source face recognition API

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    Face recognition applications are widely used today for a variety of tasks, whether personal or professional. When looking for a service that provides face detection and classification, it is easy to find several solutions. In this project another way is described so that it is possible to perform this task according to the desired needs without the need to use proprietary software. With the emergence of the Django Rest Frame Work, web application development has become easier. This work describes development of stable foundation and features that offer an administration panel, relational database management, and support for a Restful Application Programming Interface (API). This takes advantage of the exclusive use of Open Source technologies thus the application code can be modified and distributed free of charge. For the development of an API that could perform detection and facial recognition, applying an Open Source philosophy, in addition to Django Rest Framework technologies such as Python, C++, MySql and JSON were used. The prototype is initially capable of recognizing the number of faces per image, assessing eyes, smile, age and gender. Flexibility is designed to increase application capabilities with new algorithms implemented in various programing languages.Atualmente, as aplicaçÔes de reconhecimento de facial sĂŁo amplamente utilizadas para uma variedade de tarefas, pessoais ou profissionais. Ao procurarmos um serviço que forneça deteção e classificação de rosto, Ă© fĂĄcil encontrar vĂĄrias soluçÔes. Neste projeto, Ă© descrita outra maneira para que seja possĂ­vel executar esta tarefa de acordo com as necessidades desejadas, sem a necessidade de usar software proprietĂĄrio. Com o surgimento do Django Rest Framework, o desenvolvimento de aplicaçÔes web ficou mais fĂĄcil. Este trabalho descreve o desenvolvimento de bases e recursos estĂĄveis que oferecem um painel de administração, gestĂŁo de uma base de dados relacional e o suporte para uma API (Application Programming Interface) Restful. Ao tirar proveito do uso exclusivo de tecnologias Open Source, Ă© permitido que o cĂłdigo possa ser modificado e distribuĂ­do gratuitamente. Para o desenvolvimento de uma API que pudesse realizar a deteção e o reconhecimento facial, aplicando uma filosofia Open Source, para alĂ©m da tecnologia Django Rest Framework foram utilizadas tecnologias como Python, C ++, MySql e JSON. O protĂłtipo Ă© inicialmente capaz de reconhecer o nĂșmero de rostos por imagem, e avaliar olhos, sorriso, idade e sexo. Mas para alĂ©m disso, foi projetada flexibilidade para aumentar os recursos atravĂ©s da implementação de novos algoritmos em vĂĄrias linguagens de programação

    Transparent User Authentication For Mobile Applications

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    The use of smartphones in our daily lives has grown steadily, due to the combination of mobility and round-the-clock multi-connectivity. In particular, smartphones are used to perform activities, such as sending emails, transferring money via mobile Internet banking, making calls, texting, surfing the Internet, viewing documents, storing medical, confidential and personal information, shopping online and playing games. Some active applications are considered sensitive and confidential and the risks are high in the event of the loss of any sensitive data or privacy breaches. In addition, after the point of entry, using techniques such as a PIN or password, the user of the device can perform almost all tasks, of different risk levels, without having to re-authenticate periodically to re-validate the user’s identity. Furthermore, the current point-of-entry authentication mechanisms consider all the applications on a mobile device to have the same level of importance and so do not apply any further access control rules. As a result, with the rapid growth of smartphones for use in daily life, securing the sensitive data stored upon them makes authentication of paramount importance. In this research, it is argued that within a single mobile application there are different processes operating on the same data but with differing risks attached. The unauthorised disclosure or modification of mobile data has the potential to lead to a number of undesirable consequences for the user. Thus, there is no single level of risk associated with a given application and the risk level changes during use. In this context, a novel mobile applications data risk assessment model is proposed to appreciate the risk involved within an application (intra-process security). Accordingly, there is a need to suggest a method to be applied continuously and transparently (i.e., without obstructing the user’s activities) to authenticate legitimate users, which is maintained beyond point of entry, without the explicit involvement of the user. To this end, a transparent and continuous authentication mechanism provides a basis for convenient and secure re-authentication of the user. The mechanism is used to gather user data in the background without requiring any dedicated activity, by regularly and periodically checking user behaviour to provide continuous monitoring for the protection of the smartphone. In order to investigate the feasibility of the proposed system, a study involving data collected from 76 participants over a one-month period using 12 mobile applications was undertaken. A series of four experiments were conducted based upon data from one month of normal device usage. The first experiment sought to explore the intra-process (i.e., within-app) and inter-process (i.e., access-only app) access levels across different time windows. The experimental results show that this approach achieved desirable outcomes for applying a transparent authentication system at an intra-process level, with an average of 6% intrusive authentication requests. Having achieved promising experimental results, it was identified that there were some users who undertook an insufficient number of activities on the device and, therefore, achieved a high level of intrusive authentication requests. As a result, there was a need to investigate whether a specific combination of time windows would perform better with a specific type of user. To do this, the numbers of intrusive authentication requests were computed based on three usage levels (high, medium and low) at both the intra- and inter-process access levels. This approach achieved better results when compared with the first set of results: the average percentage of intrusive authentication requests was 3%, which indicates a clear enhancement. The second and third experiments investigated only the intra-process and inter-process, respectively, to examine the effect of the access level. Finally, the fourth experiment investigated the impact of specific biometric modalities on overall system performance. In this research study, a Non-Intrusive Continuous Authentication (NICA) framework was applied by utilising two security mechanisms: Alert Level (AL) and Integrity Level (IL). During specific time windows, the AL process is used to seek valid samples. If there are no samples, the identity confidence is periodically reduced by a degradation function, which is 10% of current confidence in order to save power while the mobile device is inactive. In the case of the mobile user requesting to perform a task, the IL is applied to check the legitimacy of that user. If the identity confidence level is equal to or greater than the specified risk action level, transparent access is allowed. Otherwise, an intrusive authentication request is required in order to proceed with the service. In summary, the experimental results show that this approach achieved sufficiently high results to fulfil the security obligations. The shortest time window of AL= 2 min / IL = 5 min produced an average intrusive authentication request rate of 18%, whereas the largest time window (AL= 20 min / IL = 20 min) provided 6%. Interestingly, when the participants were divided into three levels of usage, the average intrusive authentication request rate was 12% and 3% for the shortest time window (AL = 2 min / IL = 5 min) and the largest time window (AL= 20 min / IL = 20), respectively. Therefore, this approach has been demonstrated to provide transparent and continuous protection to ensure the validity of the current user by understanding the risk involved within a given application.Royal Embassy of Saudi Arabia Cultural Bureau in U

    Transparent User Authentication For Mobile Applications

    Get PDF
    The use of smartphones in our daily lives has grown steadily, due to the combination of mobility and round-the-clock multi-connectivity. In particular, smartphones are used to perform activities, such as sending emails, transferring money via mobile Internet banking, making calls, texting, surfing the Internet, viewing documents, storing medical, confidential and personal information, shopping online and playing games. Some active applications are considered sensitive and confidential and the risks are high in the event of the loss of any sensitive data or privacy breaches. In addition, after the point of entry, using techniques such as a PIN or password, the user of the device can perform almost all tasks, of different risk levels, without having to re-authenticate periodically to re-validate the user’s identity. Furthermore, the current point-of-entry authentication mechanisms consider all the applications on a mobile device to have the same level of importance and so do not apply any further access control rules. As a result, with the rapid growth of smartphones for use in daily life, securing the sensitive data stored upon them makes authentication of paramount importance. In this research, it is argued that within a single mobile application there are different processes operating on the same data but with differing risks attached. The unauthorised disclosure or modification of mobile data has the potential to lead to a number of undesirable consequences for the user. Thus, there is no single level of risk associated with a given application and the risk level changes during use. In this context, a novel mobile applications data risk assessment model is proposed to appreciate the risk involved within an application (intra-process security). Accordingly, there is a need to suggest a method to be applied continuously and transparently (i.e., without obstructing the user’s activities) to authenticate legitimate users, which is maintained beyond point of entry, without the explicit involvement of the user. To this end, a transparent and continuous authentication mechanism provides a basis for convenient and secure re-authentication of the user. The mechanism is used to gather user data in the background without requiring any dedicated activity, by regularly and periodically checking user behaviour to provide continuous monitoring for the protection of the smartphone. In order to investigate the feasibility of the proposed system, a study involving data collected from 76 participants over a one-month period using 12 mobile applications was undertaken. A series of four experiments were conducted based upon data from one month of normal device usage. The first experiment sought to explore the intra-process (i.e., within-app) and inter-process (i.e., access-only app) access levels across different time windows. The experimental results show that this approach achieved desirable outcomes for applying a transparent authentication system at an intra-process level, with an average of 6% intrusive authentication requests. Having achieved promising experimental results, it was identified that there were some users who undertook an insufficient number of activities on the device and, therefore, achieved a high level of intrusive authentication requests. As a result, there was a need to investigate whether a specific combination of time windows would perform better with a specific type of user. To do this, the numbers of intrusive authentication requests were computed based on three usage levels (high, medium and low) at both the intra- and inter-process access levels. This approach achieved better results when compared with the first set of results: the average percentage of intrusive authentication requests was 3%, which indicates a clear enhancement. The second and third experiments investigated only the intra-process and inter-process, respectively, to examine the effect of the access level. Finally, the fourth experiment investigated the impact of specific biometric modalities on overall system performance. In this research study, a Non-Intrusive Continuous Authentication (NICA) framework was applied by utilising two security mechanisms: Alert Level (AL) and Integrity Level (IL). During specific time windows, the AL process is used to seek valid samples. If there are no samples, the identity confidence is periodically reduced by a degradation function, which is 10% of current confidence in order to save power while the mobile device is inactive. In the case of the mobile user requesting to perform a task, the IL is applied to check the legitimacy of that user. If the identity confidence level is equal to or greater than the specified risk action level, transparent access is allowed. Otherwise, an intrusive authentication request is required in order to proceed with the service. In summary, the experimental results show that this approach achieved sufficiently high results to fulfil the security obligations. The shortest time window of AL= 2 min / IL = 5 min produced an average intrusive authentication request rate of 18%, whereas the largest time window (AL= 20 min / IL = 20 min) provided 6%. Interestingly, when the participants were divided into three levels of usage, the average intrusive authentication request rate was 12% and 3% for the shortest time window (AL = 2 min / IL = 5 min) and the largest time window (AL= 20 min / IL = 20), respectively. Therefore, this approach has been demonstrated to provide transparent and continuous protection to ensure the validity of the current user by understanding the risk involved within a given application.Royal Embassy of Saudi Arabia Cultural Bureau in U

    Continuous User Authentication Using Multi-Modal Biometrics

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    It is commonly acknowledged that mobile devices now form an integral part of an individual’s everyday life. The modern mobile handheld devices are capable to provide a wide range of services and applications over multiple networks. With the increasing capability and accessibility, they introduce additional demands in term of security. This thesis explores the need for authentication on mobile devices and proposes a novel mechanism to improve the current techniques. The research begins with an intensive review of mobile technologies and the current security challenges that mobile devices experience to illustrate the imperative of authentication on mobile devices. The research then highlights the existing authentication mechanism and a wide range of weakness. To this end, biometric approaches are identified as an appropriate solution an opportunity for security to be maintained beyond point-of-entry. Indeed, by utilising behaviour biometric techniques, the authentication mechanism can be performed in a continuous and transparent fashion. This research investigated three behavioural biometric techniques based on SMS texting activities and messages, looking to apply these techniques as a multi-modal biometric authentication method for mobile devices. The results showed that linguistic profiling; keystroke dynamics and behaviour profiling can be used to discriminate users with overall Equal Error Rates (EER) 12.8%, 20.8% and 9.2% respectively. By using a combination of biometrics, the results showed clearly that the classification performance is better than using single biometric technique achieving EER 3.3%. Based on these findings, a novel architecture of multi-modal biometric authentication on mobile devices is proposed. The framework is able to provide a robust, continuous and transparent authentication in standalone and server-client modes regardless of mobile hardware configuration. The framework is able to continuously maintain the security status of the devices. With a high level of security status, users are permitted to access sensitive services and data. On the other hand, with the low level of security, users are required to re-authenticate before accessing sensitive service or data
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