Pub Date : 2016-10-01DOI: 10.1109/CCST.2016.7815696
Michael Brockly, S. Elliott, R. Proctor, R. Guest
Biometric test reports are an important tool in the evaluation of biometric systems, and therefore the data entered into the system needs to be of the highest integrity. Data collection, especially across multiple modalities, can be a challenging experience for test administrators. They have to ensure that the data are collected properly, the test subjects are treated appropriately, and the test plan is followed. Tests become more complex as the number of sensors are increased, and therefore it becomes increasingly important that a test harness be developed to improve the accuracy of the data collection. This paper describes the development of a test harness for a complex multi-sensor, multi-visit data collection, and explains the processes for the development of such a harness. The applicability of such a software package for the broader biometric community is also considered.
{"title":"The development of a test harness for biometric data collection and validation","authors":"Michael Brockly, S. Elliott, R. Proctor, R. Guest","doi":"10.1109/CCST.2016.7815696","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815696","url":null,"abstract":"Biometric test reports are an important tool in the evaluation of biometric systems, and therefore the data entered into the system needs to be of the highest integrity. Data collection, especially across multiple modalities, can be a challenging experience for test administrators. They have to ensure that the data are collected properly, the test subjects are treated appropriately, and the test plan is followed. Tests become more complex as the number of sensors are increased, and therefore it becomes increasingly important that a test harness be developed to improve the accuracy of the data collection. This paper describes the development of a test harness for a complex multi-sensor, multi-visit data collection, and explains the processes for the development of such a harness. The applicability of such a software package for the broader biometric community is also considered.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"32 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80122751","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815725
K. Harman, Shailesh Singh
Over the past 25 years a number of fiber optic sensors have been developed to address fence and buried perimeters, and pipeline security. Today, sensors that locate targets along the length of the fiber sensor dominate the long-range perimeter market. There are a number of fiber optic sensors that locate targets including sensors based on interferometry and C-OTDR (Coherent Optical Time Domain Reflectometry). In general, existing interferometric techniques infer the location of a disturbance based on the magnitude of the interfering signals, as opposed to the actual phase differences, and critically suffer from polarization induced fading. A novel technology is developed, as discussed in Optellios' earlier patent, which measures the actual phase difference of the interferometric signal. As a result, this technology is more accurate and precise for locating a disturbance, works well with any magnitude of disturbance, and does not critically depend on polarization of the interfering signals. The technology uses a hybrid Michelson and Mach-Zehnder interferometer architecture that shares the same two sensing fibers. The laser light is frequency modulated, and the In-phase and Quadrature phase responses of the sensor are measured to extract the phase difference of the interfering signals. A disturbance of the sensor cable causes the phase difference of the sensor to change. This phase change is measured from each end of the fiber sensor, and the time delay between the two phase signals is used to locate the disturbance along the length of the sensor cable. The Michelson interferometer is terminated in Faraday Rotational Mirrors to avoid the issues relating to polarization induced fading. Fundamentals of this novel technology will be presented along with its relative performance and merits compared to other interferometric technologies. This technology will be further compared with C-OTDR technology, and experimental data will be discussed.
{"title":"A novel long-range perimeter security sensor based on hybrid michelson and Mach-Zehnder interferometers","authors":"K. Harman, Shailesh Singh","doi":"10.1109/CCST.2016.7815725","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815725","url":null,"abstract":"Over the past 25 years a number of fiber optic sensors have been developed to address fence and buried perimeters, and pipeline security. Today, sensors that locate targets along the length of the fiber sensor dominate the long-range perimeter market. There are a number of fiber optic sensors that locate targets including sensors based on interferometry and C-OTDR (Coherent Optical Time Domain Reflectometry). In general, existing interferometric techniques infer the location of a disturbance based on the magnitude of the interfering signals, as opposed to the actual phase differences, and critically suffer from polarization induced fading. A novel technology is developed, as discussed in Optellios' earlier patent, which measures the actual phase difference of the interferometric signal. As a result, this technology is more accurate and precise for locating a disturbance, works well with any magnitude of disturbance, and does not critically depend on polarization of the interfering signals. The technology uses a hybrid Michelson and Mach-Zehnder interferometer architecture that shares the same two sensing fibers. The laser light is frequency modulated, and the In-phase and Quadrature phase responses of the sensor are measured to extract the phase difference of the interfering signals. A disturbance of the sensor cable causes the phase difference of the sensor to change. This phase change is measured from each end of the fiber sensor, and the time delay between the two phase signals is used to locate the disturbance along the length of the sensor cable. The Michelson interferometer is terminated in Faraday Rotational Mirrors to avoid the issues relating to polarization induced fading. Fundamentals of this novel technology will be presented along with its relative performance and merits compared to other interferometric technologies. This technology will be further compared with C-OTDR technology, and experimental data will be discussed.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"54 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85234152","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815695
S. J. Berlin, M. John
This paper provides an efficient framework for recognizing human interactions based on deep learning based architecture. The Harris corner points and the histogram form the feature vector of the spatiotemporal volume. The feature vector extraction is restricted to the region of interaction. A stacked autoencoder configuration is embedded in the deep learning framework used for classification. The method is evaluated on the benchmark UT interaction dataset and average recognition rates as high as 95% and 88% are obtained on setl and set2 respectively.
{"title":"Human interaction recognition through deep learning network","authors":"S. J. Berlin, M. John","doi":"10.1109/CCST.2016.7815695","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815695","url":null,"abstract":"This paper provides an efficient framework for recognizing human interactions based on deep learning based architecture. The Harris corner points and the histogram form the feature vector of the spatiotemporal volume. The feature vector extraction is restricted to the region of interaction. A stacked autoencoder configuration is embedded in the deep learning framework used for classification. The method is evaluated on the benchmark UT interaction dataset and average recognition rates as high as 95% and 88% are obtained on setl and set2 respectively.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"27 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77377479","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815676
S. Stubberud, K. Kramer
Information assurance is the process of protecting information from theft, destruction, or manipulation. While many attacks are straightforward such as denial of service or viruses in that they require just a step or two to implement, more dangerous can require numerous steps to implement. Often, these steps need not be done in quick succession or even in a definite order. While techniques have been developed to behave as sensors to quickly assess elements of attacks, they rely on a decision engine to fuse the information to estimate whether or not an attack is underway. To identify such attacks, an evidence accrual system is proposed fuse information and estimate the possibility of an attack. The technique is based on a systems approach to combining information and provides nit only a level of evidence but a degree of uncertainty about the estimate.
{"title":"Evidence accrual technique for information assurance","authors":"S. Stubberud, K. Kramer","doi":"10.1109/CCST.2016.7815676","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815676","url":null,"abstract":"Information assurance is the process of protecting information from theft, destruction, or manipulation. While many attacks are straightforward such as denial of service or viruses in that they require just a step or two to implement, more dangerous can require numerous steps to implement. Often, these steps need not be done in quick succession or even in a definite order. While techniques have been developed to behave as sensors to quickly assess elements of attacks, they rely on a decision engine to fuse the information to estimate whether or not an attack is underway. To identify such attacks, an evidence accrual system is proposed fuse information and estimate the possibility of an attack. The technique is based on a systems approach to combining information and provides nit only a level of evidence but a degree of uncertainty about the estimate.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"12 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81800492","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815719
Somayeh Sobati Moghadam, G. Gavin, J. Darmont
Cloud computing offers the opportunity of data outsourcing as well as data management. However, because of various privacy issues, confidential data must be encrypted before being outsourced to the cloud. But query processing over encrypted data without decrypting data is a very challenging task. Property-preserving encryption schemes allow encrypting data while still enabling efficient querying over encrypted data. The inherent merits of property-preserving encryption schemes make them very suitable and efficient for cloud data outsourcing. However, the security of such schemes is still a challenge because they are vulnerable to statistical attacks. We present a new order-preserving scheme for indexing encrypted data, as an alternative to propertypreserving schemes, which hides data frequency to achieve a strictly stronger notion of security. The proposed indexing method is secure against statistical attacks. Hence, data cannot be recovered from indexes. Moreover, our scheme is still efficient for query processing.
{"title":"A secure order-preserving indexing scheme for outsourced data","authors":"Somayeh Sobati Moghadam, G. Gavin, J. Darmont","doi":"10.1109/CCST.2016.7815719","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815719","url":null,"abstract":"Cloud computing offers the opportunity of data outsourcing as well as data management. However, because of various privacy issues, confidential data must be encrypted before being outsourced to the cloud. But query processing over encrypted data without decrypting data is a very challenging task. Property-preserving encryption schemes allow encrypting data while still enabling efficient querying over encrypted data. The inherent merits of property-preserving encryption schemes make them very suitable and efficient for cloud data outsourcing. However, the security of such schemes is still a challenge because they are vulnerable to statistical attacks. We present a new order-preserving scheme for indexing encrypted data, as an alternative to propertypreserving schemes, which hides data frequency to achieve a strictly stronger notion of security. The proposed indexing method is secure against statistical attacks. Hence, data cannot be recovered from indexes. Moreover, our scheme is still efficient for query processing.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"89 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90608109","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815698
Pablo Fernández López, J. Liu-Jimenez, Carlos Sanchez-Redondo, R. Sánchez-Reillo
Gait recognition on smartphones could be considered as one of the most user-friendly biometric modalities. The main benefit of gait recognition is that it is an unobtrusive biometric modality, since it requires little interaction with the user. Users would only have to carry the sensor device and walk as normally. Its unobtrusiveness make it suitable for a user-friendly access system. Up to date, most studies on gait recognition have been done using dedicated hardware acquisition sensors. Nevertheless, one possible solution for gait recognition is using sensors embedded on smartphones. This paper compares the performance of four state-of-art algorithms on a smartphone. These algorithms have already been tested on dedicated hardware but not in a commercial phone. For such purpose, a database using a smartphone as acquisition device has been obtained. State-of-art gait recognition algorithms have been tested on this data base, as well as a new cycle detection algorithm which has been designed to have the same starting point. As a result, the algorithms have shown EER ranging from 16.38% to 29.07%, These EERs are significantly higher than the ones obtained in dedicated hardware which ranged from 5.7% to 13%.
{"title":"Gait recognition using smartphone","authors":"Pablo Fernández López, J. Liu-Jimenez, Carlos Sanchez-Redondo, R. Sánchez-Reillo","doi":"10.1109/CCST.2016.7815698","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815698","url":null,"abstract":"Gait recognition on smartphones could be considered as one of the most user-friendly biometric modalities. The main benefit of gait recognition is that it is an unobtrusive biometric modality, since it requires little interaction with the user. Users would only have to carry the sensor device and walk as normally. Its unobtrusiveness make it suitable for a user-friendly access system. Up to date, most studies on gait recognition have been done using dedicated hardware acquisition sensors. Nevertheless, one possible solution for gait recognition is using sensors embedded on smartphones. This paper compares the performance of four state-of-art algorithms on a smartphone. These algorithms have already been tested on dedicated hardware but not in a commercial phone. For such purpose, a database using a smartphone as acquisition device has been obtained. State-of-art gait recognition algorithms have been tested on this data base, as well as a new cycle detection algorithm which has been designed to have the same starting point. As a result, the algorithms have shown EER ranging from 16.38% to 29.07%, These EERs are significantly higher than the ones obtained in dedicated hardware which ranged from 5.7% to 13%.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"36 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73265870","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815706
Nazariy K. Shaydyuk, T. Cleland
Current biometric modalities include fingerprint, palm, voice, face, gate, iris and even DNA recognition. Another known biometric technique involves subject identification using retinal Mood vasculature pattern matching. Regardless of the modality, however, there is an inherent requirement for liveness detection so as to make the acquisition system less susceptible to deception. One possible solution for retina scanning systems is verification of blood llow in the retinal vessels - the definite feature of live tissue. Laser speckle contrast imaging is a common method of blood flow detection and could be used to explicitly confirm liveness. The dynamics of the speckle pattern can be statistically quantified and interpreted as the regions with and without flow. Using a model of the retinal vasculature, this paper reviews speckle contrast imaging as it applies to liveness verification by means of blood flow detection in retina-based biometric systems.
{"title":"Biometric identification via retina scanning with liveness detection using speckle contrast imaging","authors":"Nazariy K. Shaydyuk, T. Cleland","doi":"10.1109/CCST.2016.7815706","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815706","url":null,"abstract":"Current biometric modalities include fingerprint, palm, voice, face, gate, iris and even DNA recognition. Another known biometric technique involves subject identification using retinal Mood vasculature pattern matching. Regardless of the modality, however, there is an inherent requirement for liveness detection so as to make the acquisition system less susceptible to deception. One possible solution for retina scanning systems is verification of blood llow in the retinal vessels - the definite feature of live tissue. Laser speckle contrast imaging is a common method of blood flow detection and could be used to explicitly confirm liveness. The dynamics of the speckle pattern can be statistically quantified and interpreted as the regions with and without flow. Using a model of the retinal vasculature, this paper reviews speckle contrast imaging as it applies to liveness verification by means of blood flow detection in retina-based biometric systems.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89630889","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815717
T. W. Rogers, Nicolas Jaccard, E. Protonotarios, J. Ollier, E. Morton, Lewis D. Griffin
We propose a framework for Threat Image Projection (TIP) in cargo transmission X-ray imagery. The method exploits the approximately multiplicative nature of X-ray imagery to extract a library of threat items. These items can then be projected into real cargo. We show using experimental data that there is no significant qualitative or quantitative difference between real threat images and TIP images. We also describe methods for adding realistic variation to TIP images in order to robustify Machine Learning (ML) based algorithms trained on TIP. These variations are derived from cargo X-ray image formation, and include: (i) translations; (ii) magnification; (iii) rotations; (iv) noise; (v) illumination; (vi) volume and density; and (vii) obscuration. These methods are particularly relevant for representation learning, since it allows the system to learn features that are invariant to these variations. The framework also allows efficient addition of new or emerging threats to a detection system, which is important if time is critical. We have applied the framework to training ML-based cargo algorithms for (i) detection of loads (empty verification), (ii) detection of concealed cars (ii) detection of Small Metallic Threats (SMTs). TIP also enables algorithm testing under controlled conditions, allowing one to gain a deeper understanding of performance. Whilst we have focused on robustifying ML-based threat detectors, our TIP method can also be used to train and robustify human threat detectors as is done in cabin baggage screening.
{"title":"Threat Image Projection (TIP) into X-ray images of cargo containers for training humans and machines","authors":"T. W. Rogers, Nicolas Jaccard, E. Protonotarios, J. Ollier, E. Morton, Lewis D. Griffin","doi":"10.1109/CCST.2016.7815717","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815717","url":null,"abstract":"We propose a framework for Threat Image Projection (TIP) in cargo transmission X-ray imagery. The method exploits the approximately multiplicative nature of X-ray imagery to extract a library of threat items. These items can then be projected into real cargo. We show using experimental data that there is no significant qualitative or quantitative difference between real threat images and TIP images. We also describe methods for adding realistic variation to TIP images in order to robustify Machine Learning (ML) based algorithms trained on TIP. These variations are derived from cargo X-ray image formation, and include: (i) translations; (ii) magnification; (iii) rotations; (iv) noise; (v) illumination; (vi) volume and density; and (vii) obscuration. These methods are particularly relevant for representation learning, since it allows the system to learn features that are invariant to these variations. The framework also allows efficient addition of new or emerging threats to a detection system, which is important if time is critical. We have applied the framework to training ML-based cargo algorithms for (i) detection of loads (empty verification), (ii) detection of concealed cars (ii) detection of Small Metallic Threats (SMTs). TIP also enables algorithm testing under controlled conditions, allowing one to gain a deeper understanding of performance. Whilst we have focused on robustifying ML-based threat detectors, our TIP method can also be used to train and robustify human threat detectors as is done in cabin baggage screening.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"22 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83318605","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815712
Sam Abbott-McCune, Lisa A. Shay
This research will demonstrate hacking techniques on the modern automotive network and describe the design and implementation of a benchtop simulator. In currently-produced vehicles, the primary network is based on the Controller Area Network (CAN) bus described in the ISO 11898 family of protocols. The CAN bus performs well in the electronically noisy environment found in the modern automobile. While the CAN bus is ideal for the exchange of information in this environment, when the protocol was designed security was not a priority due to the presumed isolation of the network. That assumption has been invalidated by recent, well-publicized attacks where hackers were able to remotely control an automobile, leading to a product recall that affected more than a million vehicles. The automobile has a multitude of electronic control units (ECUs) which are interconnected with the CAN bus to control the various systems which include the infotainment, light, and engine systems. The CAN bus allows the ECUs to share information along a common bus which has led to improvements in fuel and emission efficiency, but has also introduced vulnerabilities by giving access on the same network to cyber-physical systems (CPS). These CPS systems include the anti-lock braking systems (ABS) and on late model vehicles the ability to turn the steering wheel and control the accelerator. Testing functionality on an operational vehicle can be dangerous and place others in harm's way, but simulating the vehicle network and functionality of the ECUs on a bench-top system provides a safe way to test for vulnerabilities and to test possible security solutions to prevent CPS access over the CAN bus network. This paper will describe current research on the automotive network, provide techniques in capturing network traffic for playback, and demonstrate the design and implementation of a benchtop system for continued research on the CAN bus.
{"title":"Techniques in hacking and simulating a modem automotive controller area network","authors":"Sam Abbott-McCune, Lisa A. Shay","doi":"10.1109/CCST.2016.7815712","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815712","url":null,"abstract":"This research will demonstrate hacking techniques on the modern automotive network and describe the design and implementation of a benchtop simulator. In currently-produced vehicles, the primary network is based on the Controller Area Network (CAN) bus described in the ISO 11898 family of protocols. The CAN bus performs well in the electronically noisy environment found in the modern automobile. While the CAN bus is ideal for the exchange of information in this environment, when the protocol was designed security was not a priority due to the presumed isolation of the network. That assumption has been invalidated by recent, well-publicized attacks where hackers were able to remotely control an automobile, leading to a product recall that affected more than a million vehicles. The automobile has a multitude of electronic control units (ECUs) which are interconnected with the CAN bus to control the various systems which include the infotainment, light, and engine systems. The CAN bus allows the ECUs to share information along a common bus which has led to improvements in fuel and emission efficiency, but has also introduced vulnerabilities by giving access on the same network to cyber-physical systems (CPS). These CPS systems include the anti-lock braking systems (ABS) and on late model vehicles the ability to turn the steering wheel and control the accelerator. Testing functionality on an operational vehicle can be dangerous and place others in harm's way, but simulating the vehicle network and functionality of the ECUs on a bench-top system provides a safe way to test for vulnerabilities and to test possible security solutions to prevent CPS access over the CAN bus network. This paper will describe current research on the automotive network, provide techniques in capturing network traffic for playback, and demonstrate the design and implementation of a benchtop system for continued research on the CAN bus.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"38 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82280020","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 : 2016-10-01DOI: 10.1109/CCST.2016.7815724
Chaofan Wang, Michael Olson, Nyambuu Dorjkhand, Shailesh Singh
Leaks in pipelines transporting oil, gas, or any tluid may cause enormous propern and environmental damage, hence early leak detection and accurate localization are highly desirable. Sensors to detect leaks can be broadly classified into internal and external sensors depending on where they are installed. In general, internal sensors have matured over decades while external sensors based on fiber optics are just beginning to show promise for early and precise leak detection. In this work, a novel technology DdTS (Distributed Differential Temperature Sensor) is developed that can almost instantaneously detect differential temperature in the optical fiber of as little as 0.0005 C with a location accuracy of several meters. The temperature sensitivity is several orders of magnitude higher than other Brillouin or Raman based distributed temperature sensors based on fiber optics in the market. The technology utilizes standard optical fibers installed adjacent to a pipeline and can be retrofitted to a preexisting cable in most cases. In addition to detecting differential temperature, the DdTS technology also uses acoustic signatures to detect leaks, which is effective in cases where the fluid temperature closely matches that of the background soil. The DdTS technology is based on an enhanced version of Coherent Optical Time-Domain Reflectometry (C-OTDR) and can measure not only the quasi-static changes, such as temperature or strain, but also dynamic acoustic signals in the fiber. Experimental results for gas leaks from a simulated buried pipeline are discussed for different vertical and horizontal offsets, gas pressures, leak-hole sizes, and orifice acoustic signals. Experimental data simulating a liquid leak are also discussed. All experiments confirmed the theoretical capabilities of the DdTS sensor.
{"title":"A novel DdTS technology based on fiber optics for early leak detection in pipelines","authors":"Chaofan Wang, Michael Olson, Nyambuu Dorjkhand, Shailesh Singh","doi":"10.1109/CCST.2016.7815724","DOIUrl":"https://doi.org/10.1109/CCST.2016.7815724","url":null,"abstract":"Leaks in pipelines transporting oil, gas, or any tluid may cause enormous propern and environmental damage, hence early leak detection and accurate localization are highly desirable. Sensors to detect leaks can be broadly classified into internal and external sensors depending on where they are installed. In general, internal sensors have matured over decades while external sensors based on fiber optics are just beginning to show promise for early and precise leak detection. In this work, a novel technology DdTS (Distributed Differential Temperature Sensor) is developed that can almost instantaneously detect differential temperature in the optical fiber of as little as 0.0005 C with a location accuracy of several meters. The temperature sensitivity is several orders of magnitude higher than other Brillouin or Raman based distributed temperature sensors based on fiber optics in the market. The technology utilizes standard optical fibers installed adjacent to a pipeline and can be retrofitted to a preexisting cable in most cases. In addition to detecting differential temperature, the DdTS technology also uses acoustic signatures to detect leaks, which is effective in cases where the fluid temperature closely matches that of the background soil. The DdTS technology is based on an enhanced version of Coherent Optical Time-Domain Reflectometry (C-OTDR) and can measure not only the quasi-static changes, such as temperature or strain, but also dynamic acoustic signals in the fiber. Experimental results for gas leaks from a simulated buried pipeline are discussed for different vertical and horizontal offsets, gas pressures, leak-hole sizes, and orifice acoustic signals. Experimental data simulating a liquid leak are also discussed. All experiments confirmed the theoretical capabilities of the DdTS sensor.","PeriodicalId":6510,"journal":{"name":"2016 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"29 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80880022","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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