The advent of embedded systems has completely transformed the information landscape. With the explosive growth in the use of interactive real-time technologies, this internet landscape aims to support an even broader range of application domains. The large amount of data that is exchanged by these applications has made them an attractive target for attacks. Thus it is important to employ security mechanisms to protect these systems from attackers. A major challenge facing researchers is the resource constrained nature of these systems, which renders most of the traditional security mechanisms almost useless. In this paper we propose a lightweight ICmetrics based security architecture using lattices. The features of the proposed architecture fulfill both the requirements of security as well as energy efficiency. The proposed architecture provides authentication, confidentiality, non-repudiation and integrity of data. Using the identity information derived from ICmetrics of the device, we further construct a sign cryption scheme based on lattices that makes use of certificate less PKC to achieve the security requirements of the design. This scheme is targeted on resource constrained environments, and can be used widely in applications that require sufficient levels of security with limited resources.
{"title":"An ICMetrics Based Lightweight Security Architecture Using Lattice Signcryption","authors":"Ruhma Tahir, K. Mcdonald-Maier","doi":"10.1109/EST.2012.43","DOIUrl":"https://doi.org/10.1109/EST.2012.43","url":null,"abstract":"The advent of embedded systems has completely transformed the information landscape. With the explosive growth in the use of interactive real-time technologies, this internet landscape aims to support an even broader range of application domains. The large amount of data that is exchanged by these applications has made them an attractive target for attacks. Thus it is important to employ security mechanisms to protect these systems from attackers. A major challenge facing researchers is the resource constrained nature of these systems, which renders most of the traditional security mechanisms almost useless. In this paper we propose a lightweight ICmetrics based security architecture using lattices. The features of the proposed architecture fulfill both the requirements of security as well as energy efficiency. The proposed architecture provides authentication, confidentiality, non-repudiation and integrity of data. Using the identity information derived from ICmetrics of the device, we further construct a sign cryption scheme based on lattices that makes use of certificate less PKC to achieve the security requirements of the design. This scheme is targeted on resource constrained environments, and can be used widely in applications that require sufficient levels of security with limited resources.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128349513","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}
Wireless Sensor Networks (WSNs) have the potential of being employed in a variety of applications ranging from battlefield surveillance to everyday applications such as smart homes and patient monitoring. Security is a major challenge that all applications based on WSNs are facing nowadays. Firstly, due to the wireless nature of WSNs, and secondly due to their ability to operate in unattended environments makes them even more vulnerable to various sorts of attacks. Among these attacks is node capture attack in WSNs, whose threat severity can range from a single node being compromised in the network to the whole network being compromised as a result of that single node compromise. In this paper, we propose the use of ICMetric technology to provide resilience against node compromise in WSN. ICmetrics generates the security attributes of the sensor node based on measurable hardware and software characteristics of the integrated circuit. These properties of ICmetrics can help safeguard WSNs from various node capture attacks.
{"title":"Improving Resilience Against Node Capture Attacks in Wireless Sensor Networks Using ICmetrics","authors":"Ruhma Tahir, K. Mcdonald-Maier","doi":"10.1109/EST.2012.44","DOIUrl":"https://doi.org/10.1109/EST.2012.44","url":null,"abstract":"Wireless Sensor Networks (WSNs) have the potential of being employed in a variety of applications ranging from battlefield surveillance to everyday applications such as smart homes and patient monitoring. Security is a major challenge that all applications based on WSNs are facing nowadays. Firstly, due to the wireless nature of WSNs, and secondly due to their ability to operate in unattended environments makes them even more vulnerable to various sorts of attacks. Among these attacks is node capture attack in WSNs, whose threat severity can range from a single node being compromised in the network to the whole network being compromised as a result of that single node compromise. In this paper, we propose the use of ICMetric technology to provide resilience against node compromise in WSN. ICmetrics generates the security attributes of the sensor node based on measurable hardware and software characteristics of the integrated circuit. These properties of ICmetrics can help safeguard WSNs from various node capture attacks.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120957436","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}
Critical applications in areas such as defence, security and space exploration will have design challenges created by factors such as cost, size and tolerance. Scaled technologies will offer a huge potential in these areas, as they are inherently faster, low-power, low-cost and more harsh-environment tolerant. Moving toward nanoscale designs will trigger many design challenges that need to be addressed and dealt with for better system performance and reliability of operation. One such design challenge is the close proximity of on-chip interconnects coupled with reduced dielectric-thickness, leading to cross-coupling effects. The effect of cross-coupling may range from minor performance deterioration to system failure - thus impeding planned operations and tasks. A method for effectively and efficiently describing and determining the cross-coupling effects between multi-layer, multi-coupled interconnect-systems is presented.
{"title":"Computation of Cross-Coupling for Reliable System Operation","authors":"H. Kadim, L. M. Coulibaly","doi":"10.1109/EST.2012.10","DOIUrl":"https://doi.org/10.1109/EST.2012.10","url":null,"abstract":"Critical applications in areas such as defence, security and space exploration will have design challenges created by factors such as cost, size and tolerance. Scaled technologies will offer a huge potential in these areas, as they are inherently faster, low-power, low-cost and more harsh-environment tolerant. Moving toward nanoscale designs will trigger many design challenges that need to be addressed and dealt with for better system performance and reliability of operation. One such design challenge is the close proximity of on-chip interconnects coupled with reduced dielectric-thickness, leading to cross-coupling effects. The effect of cross-coupling may range from minor performance deterioration to system failure - thus impeding planned operations and tasks. A method for effectively and efficiently describing and determining the cross-coupling effects between multi-layer, multi-coupled interconnect-systems is presented.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121123854","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}
I. Ide, Takumi Kuhara, Daisuke Deguchi, Tomokazu Takahashi, H. Murase
Detection and classification of significant human motions are important tasks when analyzing a video that records human activities. Among various human motions, we consider that repetitious motions are specially important since they are usually results of activities with clear intentions. In this paper, we propose and evaluate a method that detects video segments that contain repetitious motions, which is robust to motion shift. Experimental results showed the effectiveness of the proposed method compared to conventional methods. In addition, we report a preliminary result of an experiment on the classification of the types of the detected repetitious motions.
{"title":"Detection and Classification of Repetitious Human Motions Combining Shift Variant and Invariant Features","authors":"I. Ide, Takumi Kuhara, Daisuke Deguchi, Tomokazu Takahashi, H. Murase","doi":"10.1109/EST.2012.7","DOIUrl":"https://doi.org/10.1109/EST.2012.7","url":null,"abstract":"Detection and classification of significant human motions are important tasks when analyzing a video that records human activities. Among various human motions, we consider that repetitious motions are specially important since they are usually results of activities with clear intentions. In this paper, we propose and evaluate a method that detects video segments that contain repetitious motions, which is robust to motion shift. Experimental results showed the effectiveness of the proposed method compared to conventional methods. In addition, we report a preliminary result of an experiment on the classification of the types of the detected repetitious motions.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132034420","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}
Stepán Mrácek, J. Váňa, M. Drahanský, R. Dvořák, S. Yanushkevich
One of underused biometric methods is the face recognition based on thermal images. Nevertheless, in the applications such as liveness detection or fever scan, the thermal face recognition is used as a standalone module, or as a part of a multimodal biometric system. This article presents an overview and comparison of various statistical methods for thermal facial image analysis and recognition. It also proposes an approach to fusion of some methods to improve the overall performance.
{"title":"Thermal Face Recognition: A Fusion Approach","authors":"Stepán Mrácek, J. Váňa, M. Drahanský, R. Dvořák, S. Yanushkevich","doi":"10.1109/EST.2012.24","DOIUrl":"https://doi.org/10.1109/EST.2012.24","url":null,"abstract":"One of underused biometric methods is the face recognition based on thermal images. Nevertheless, in the applications such as liveness detection or fever scan, the thermal face recognition is used as a standalone module, or as a part of a multimodal biometric system. This article presents an overview and comparison of various statistical methods for thermal facial image analysis and recognition. It also proposes an approach to fusion of some methods to improve the overall performance.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128345502","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}
This paper presents a liveness detection method based on tracking the gaze of the user of a face recognition system using a single camera. The user is required to follow a visual animation of a moving object on a display screen while his/her gaze is measured. The visual stimulus is designed to direct the gaze of the user to sets of collinear points on the screen. Features based on the measured collinearity of the observed gaze are then used to discriminate between live attempts at responding to this challenge and those conducted by "impostors" holding photographs and attempting to follow the stimulus. An initial set of experiments is reported that indicates the effectiveness of the proposed method in detecting this class of spoofing attacks.
{"title":"Liveness Detection Using Gaze Collinearity","authors":"Asad Ali, F. Deravi, Sanaul Hoque","doi":"10.1109/EST.2012.12","DOIUrl":"https://doi.org/10.1109/EST.2012.12","url":null,"abstract":"This paper presents a liveness detection method based on tracking the gaze of the user of a face recognition system using a single camera. The user is required to follow a visual animation of a moving object on a display screen while his/her gaze is measured. The visual stimulus is designed to direct the gaze of the user to sets of collinear points on the screen. Features based on the measured collinearity of the observed gaze are then used to discriminate between live attempts at responding to this challenge and those conducted by \"impostors\" holding photographs and attempting to follow the stimulus. An initial set of experiments is reported that indicates the effectiveness of the proposed method in detecting this class of spoofing attacks.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126856072","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}
Localization plays a significant role in the autonomous navigation of a mobile robot. This paper investigates mobile robot localization based on Extended Kalman Filter(EKF) algorithm and a feature based map. Corner angles in the environment are detected as the features, and the detailed processes of feature extraction are described. Then the motion model and odometry information are elaborated, and the EKF localization algorithm is presented. Finally, the experimental result is given to verify the feasibility and performance of the proposed localization algorithm.
{"title":"EKF Based Mobile Robot Localization","authors":"Ling Chen, Huosheng Hu, K. Mcdonald-Maier","doi":"10.1109/EST.2012.19","DOIUrl":"https://doi.org/10.1109/EST.2012.19","url":null,"abstract":"Localization plays a significant role in the autonomous navigation of a mobile robot. This paper investigates mobile robot localization based on Extended Kalman Filter(EKF) algorithm and a feature based map. Corner angles in the environment are detected as the features, and the detailed processes of feature extraction are described. Then the motion model and odometry information are elaborated, and the EKF localization algorithm is presented. Finally, the experimental result is given to verify the feasibility and performance of the proposed localization algorithm.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115381211","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}
Authentication and Identity Management help to protect resources and justify trust in "bona fide" operation by service client and service provider. Besides, identity management can support hardware assisted integrity protection. In the Internet of Things (IoT), the high number of lightweight devices requires scalable and lightweight solutions to trust management. The paper proposes a framework for authentication and integrity protection well suited for anIoT environment.
{"title":"Identity Management and Integrity Protection in the Internet of Things","authors":"A. Fongen","doi":"10.1109/EST.2012.15","DOIUrl":"https://doi.org/10.1109/EST.2012.15","url":null,"abstract":"Authentication and Identity Management help to protect resources and justify trust in \"bona fide\" operation by service client and service provider. Besides, identity management can support hardware assisted integrity protection. In the Internet of Things (IoT), the high number of lightweight devices requires scalable and lightweight solutions to trust management. The paper proposes a framework for authentication and integrity protection well suited for anIoT environment.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132690329","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}
This paper presents a biometric person recognition system using electroencephalogram (EEG) signals as the source of identity information. Wavelet transform is used for extracting features from raw EEG signals which are then classified using a support vector machine and a knearestneighbour classifier to recognize the individuals. A number of stimuli are explored using up to 18 subjects to generate person-specific EEG patterns to explore which type of stimulus may achieve better recognition rates. A comparison between two kinds of tasks - motor movement and motor imagery - appears to indicate that imagery tasks show better and more stable performance than movement tasks. The paper also reports on the impact of the number and positioning of the electrodes on performance.
{"title":"On the Effectiveness of EEG Signals as a Source of Biometric Information","authors":"Su Yang, F. Deravi","doi":"10.1109/EST.2012.8","DOIUrl":"https://doi.org/10.1109/EST.2012.8","url":null,"abstract":"This paper presents a biometric person recognition system using electroencephalogram (EEG) signals as the source of identity information. Wavelet transform is used for extracting features from raw EEG signals which are then classified using a support vector machine and a knearestneighbour classifier to recognize the individuals. A number of stimuli are explored using up to 18 subjects to generate person-specific EEG patterns to explore which type of stimulus may achieve better recognition rates. A comparison between two kinds of tasks - motor movement and motor imagery - appears to indicate that imagery tasks show better and more stable performance than movement tasks. The paper also reports on the impact of the number and positioning of the electrodes on performance.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130103394","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}
Clay or computerised facial reconstructions are often presented to the public for recognition without information about the external features of a head (hair, ears and neck) as these are thought to be potentially distracting or even misleading. In this context, the mechanisms of face recognition are poorly understood, but existing research using photographs of familiar faces suggests that external features play an important role for recognition, and external features may even be necessary for recognition to occur at all. The current research aimed to determine the contribution that external features make to the recognition of a familiar face rendered in 3D. It will also determine whether the inclusion or exclusion of external features from a reconstruction is likely to be beneficial. Volunteers were asked to name images of 3D faces of people known to them, presented as either full face 3D surface scans, or where the internal or external features had been removed. As was expected, a clear correlation was found between information presented in the scans and the recognition rate, with participants correctly naming full face images most often and images of external features least often. Logistic regression analysis demonstrated a significant linear trend in recognition rate in the order of external features, internal features and full face. Incorrect naming also increased linearly, indicating that participants were more likely to offer a name (correct or otherwise) when more useful facial information was provided.
{"title":"Understanding Familiar Face Recognition for 3D Scanned Images: The Importance of Internal and External Facial Features","authors":"Anna Williams, H. Chang, C. Frowd","doi":"10.1109/EST.2012.36","DOIUrl":"https://doi.org/10.1109/EST.2012.36","url":null,"abstract":"Clay or computerised facial reconstructions are often presented to the public for recognition without information about the external features of a head (hair, ears and neck) as these are thought to be potentially distracting or even misleading. In this context, the mechanisms of face recognition are poorly understood, but existing research using photographs of familiar faces suggests that external features play an important role for recognition, and external features may even be necessary for recognition to occur at all. The current research aimed to determine the contribution that external features make to the recognition of a familiar face rendered in 3D. It will also determine whether the inclusion or exclusion of external features from a reconstruction is likely to be beneficial. Volunteers were asked to name images of 3D faces of people known to them, presented as either full face 3D surface scans, or where the internal or external features had been removed. As was expected, a clear correlation was found between information presented in the scans and the recognition rate, with participants correctly naming full face images most often and images of external features least often. Logistic regression analysis demonstrated a significant linear trend in recognition rate in the order of external features, internal features and full face. Incorrect naming also increased linearly, indicating that participants were more likely to offer a name (correct or otherwise) when more useful facial information was provided.","PeriodicalId":314247,"journal":{"name":"2012 Third International Conference on Emerging Security Technologies","volume":"604 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134600466","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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