Pub Date : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972294
Hongjie Fang, R. Obermaisser
In the railway domain, the development trend is evolving from federated to integrated architectures, which promise massive cost reduction through higher functional integration of Train Control and Monitoring Systems (TCMS). An integrated architecture means that components are integrated on a computing node, which formerly were allocated to separate computing nodes. Therefore, the execution environment needs to support communication between these components on a computing node. Based on an integrated architecture, a virtual switch supporting time-space isolation and dynamic configuration has been proposed in previous work to address the mixed criticality of TCMS applications and dynamic coupling of vehicles. However, controlled information import and export between different data flows is not addressed in the state of the art.In this paper, we propose a virtual gateway residing in the TCMS execution environment to resolve property mismatches between different data flows and prevent fault propagation between applications of different safety critical levels. We capture the properties of data flows in the gateway specification and realise the gateway services by leveraging a database in the gateway. The experimental results show the isolation and the controlled information transportation between data flows.
{"title":"Virtual Gateway in TCMS Execution Environment based on an Integrated Architecture","authors":"Hongjie Fang, R. Obermaisser","doi":"10.1109/INDIN41052.2019.8972294","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972294","url":null,"abstract":"In the railway domain, the development trend is evolving from federated to integrated architectures, which promise massive cost reduction through higher functional integration of Train Control and Monitoring Systems (TCMS). An integrated architecture means that components are integrated on a computing node, which formerly were allocated to separate computing nodes. Therefore, the execution environment needs to support communication between these components on a computing node. Based on an integrated architecture, a virtual switch supporting time-space isolation and dynamic configuration has been proposed in previous work to address the mixed criticality of TCMS applications and dynamic coupling of vehicles. However, controlled information import and export between different data flows is not addressed in the state of the art.In this paper, we propose a virtual gateway residing in the TCMS execution environment to resolve property mismatches between different data flows and prevent fault propagation between applications of different safety critical levels. We capture the properties of data flows in the gateway specification and realise the gateway services by leveraging a database in the gateway. The experimental results show the isolation and the controlled information transportation between data flows.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133885990","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972018
Lehlogonolo P. I. Ledwaba, G. Hancke, S. Isaac, H. Venter
The ability for the smart microgrid to allow for the independent generation and distribution of electrical energy makes it an attractive solution towards enabling universal access to electricity within developing economies. Distributed Ledger Technologies (DLTs) are being considered as an enabling technology for the secure energy trade market however the high processing, energy and data exchange requirements may make them unsuitable for the Industrial Internet of Things technologies used in the implementation of the microgrid and the limited connectivity infrastructure in developing technologies. This work serves to assess the suitability of DLTs for IIoT edge node operation and as a solution for the microgrid energy market by considering node transaction times, operating temperature, power consumption, processor and memory useage, in addition to mining effort and end user costs.
{"title":"Developing a Secure, Smart Microgrid Energy Market using Distributed Ledger Technologies","authors":"Lehlogonolo P. I. Ledwaba, G. Hancke, S. Isaac, H. Venter","doi":"10.1109/INDIN41052.2019.8972018","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972018","url":null,"abstract":"The ability for the smart microgrid to allow for the independent generation and distribution of electrical energy makes it an attractive solution towards enabling universal access to electricity within developing economies. Distributed Ledger Technologies (DLTs) are being considered as an enabling technology for the secure energy trade market however the high processing, energy and data exchange requirements may make them unsuitable for the Industrial Internet of Things technologies used in the implementation of the microgrid and the limited connectivity infrastructure in developing technologies. This work serves to assess the suitability of DLTs for IIoT edge node operation and as a solution for the microgrid energy market by considering node transaction times, operating temperature, power consumption, processor and memory useage, in addition to mining effort and end user costs.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"33 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114035606","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972226
R. Taherkhani, S. Nihtianov
Wireless sensor networks (WSNs) are gaining increasing popularity in industry. Success of these systems depends on two very important factors: power efficiency of the sensor nodes and communication reliability. In this paper, we investigate the effect of using unidirectional (broadcasting) communication on the power consumption and reliability of a wireless sensor node. A high-precision wireless temperature sensor reported in an earlier publication is employed as a case study. First, we calculate the energy required to transmit and receive a message using Bluetooth low energy (BLE) in the physical layer without taking any reliability precautions. Then, we estimate the amount of energy required for the reliable transmission of a BLE packet using the BLE acknowledgment method and forward error correction (FEC) in the application layer. Through this paper, we show that the power consumption of a wireless temperature sensor can be reduced using broadcast communication and simultaneous forward error correction while providing enough reliability in short ranges.
{"title":"Power Consumption Optimization of a Wireless Temperature Sensor Node Using Unidirectional Communication","authors":"R. Taherkhani, S. Nihtianov","doi":"10.1109/INDIN41052.2019.8972226","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972226","url":null,"abstract":"Wireless sensor networks (WSNs) are gaining increasing popularity in industry. Success of these systems depends on two very important factors: power efficiency of the sensor nodes and communication reliability. In this paper, we investigate the effect of using unidirectional (broadcasting) communication on the power consumption and reliability of a wireless sensor node. A high-precision wireless temperature sensor reported in an earlier publication is employed as a case study. First, we calculate the energy required to transmit and receive a message using Bluetooth low energy (BLE) in the physical layer without taking any reliability precautions. Then, we estimate the amount of energy required for the reliable transmission of a BLE packet using the BLE acknowledgment method and forward error correction (FEC) in the application layer. Through this paper, we show that the power consumption of a wireless temperature sensor can be reduced using broadcast communication and simultaneous forward error correction while providing enough reliability in short ranges.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122854041","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972025
Weiyi Zhang, Z. Salcic, Avinash Malik
SystemJ is a programming language developed for implementing safety critical cyber-physical systems, including industrial automation systems. However, the current tools do not support an efficient mechanism to verify SystemJ programs formally. This paper presents a semantics-preserving translation of the synchronous subset of SystemJ to Coloured Petri Net (CPN), which in turn enables leveraging the plethora of analysis and verification tools for CPN to verify SystemJ programs. The translation and verification approach is illustrated on a pedagogical industrial automation example of a SystemJ program.
{"title":"Towards Formal Modeling and Analysis of SystemJ GALS Systems using Coloured Petri Nets","authors":"Weiyi Zhang, Z. Salcic, Avinash Malik","doi":"10.1109/INDIN41052.2019.8972025","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972025","url":null,"abstract":"SystemJ is a programming language developed for implementing safety critical cyber-physical systems, including industrial automation systems. However, the current tools do not support an efficient mechanism to verify SystemJ programs formally. This paper presents a semantics-preserving translation of the synchronous subset of SystemJ to Coloured Petri Net (CPN), which in turn enables leveraging the plethora of analysis and verification tools for CPN to verify SystemJ programs. The translation and verification approach is illustrated on a pedagogical industrial automation example of a SystemJ program.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127955702","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972164
Christian Reich, Christina Nicolaou, Ahmad Mansour, Kristof Van Laerhoven
In this study, we consider the problem of detecting process-related anomalies for machine tools. The similar shape of successive sensor signals, which arises due to the same process step sequence applied to each workpiece, suggests extracting shape-related features. In recent years, shapelets dominated the field of shape-related features. Unfortunately, they involve a high computational burden due to hyperparameter optimization.We introduce alternative shape-related features relying on abrupt signal changes (changepoints) reflecting the changes of process steps. During normal operation, changepoints follow a highly recurrent pattern, i.e., appear at similar locations. Thus, being able to distinguish regular, recurrent from abnormal, non-recurrent changepoints allows detecting process anomalies.For changepoint recurrence estimation, we extend the Bayesian Online Changepoint Detection (BOCPD) method. The extension allows distinguishing normal and abnormal changepoints relying on empirical estimates of the changepoint recurrence distribution. Subsequently, changepoint-related features are introduced and compared to shapelets and wavelet-based features in a case study comprising real-world machine tool data.Qualitative results verify changepoint locations being comparable to shapelet locations found by the FLAG shapelet approach. Furthermore, quantitative results suggest superior classification performance both to shapelets and wavelet-based features.
{"title":"Detection of Machine Tool Anomalies from Bayesian Changepoint Recurrence Estimation","authors":"Christian Reich, Christina Nicolaou, Ahmad Mansour, Kristof Van Laerhoven","doi":"10.1109/INDIN41052.2019.8972164","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972164","url":null,"abstract":"In this study, we consider the problem of detecting process-related anomalies for machine tools. The similar shape of successive sensor signals, which arises due to the same process step sequence applied to each workpiece, suggests extracting shape-related features. In recent years, shapelets dominated the field of shape-related features. Unfortunately, they involve a high computational burden due to hyperparameter optimization.We introduce alternative shape-related features relying on abrupt signal changes (changepoints) reflecting the changes of process steps. During normal operation, changepoints follow a highly recurrent pattern, i.e., appear at similar locations. Thus, being able to distinguish regular, recurrent from abnormal, non-recurrent changepoints allows detecting process anomalies.For changepoint recurrence estimation, we extend the Bayesian Online Changepoint Detection (BOCPD) method. The extension allows distinguishing normal and abnormal changepoints relying on empirical estimates of the changepoint recurrence distribution. Subsequently, changepoint-related features are introduced and compared to shapelets and wavelet-based features in a case study comprising real-world machine tool data.Qualitative results verify changepoint locations being comparable to shapelet locations found by the FLAG shapelet approach. Furthermore, quantitative results suggest superior classification performance both to shapelets and wavelet-based features.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617644","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972082
Md. Zia Uddin, W. Khaksar, J. Tørresen
Recognizing human activities from sensor data is one of the key areas of image processing, computer vision, and pattern recognition researches today. The target of human activity recognition (HAR) is usually to detect and analyze distinguished activities from the data acquired via different sensors (e.g. thermal cameras). This work proposes a HAR approach from videos recorded via a thermal camera. Skeletons of human bodies are extracted from thermal frames using an opensource deep convolutional neural network (CNN)-based approach named OpenPose. It is generally applied on videos of typical color cameras. However, this work adopts OpenPose on thermal images to extract useful features so that the HAR system can be deployed in environments with low lights as well. Once skeletons of human silhouettes are obtained from the thermal images, robust spatiotemporal features are extracted followed by discriminant analysis. Finally, the discriminant features are fed into a deep recurrent neural network (RNN) for activity training and recognition. The proposed HAR method can be applied to monitor the users such as elderly in both bright and dark environments to prolong their independent life, unlike other typical color cameras which are generally applied in bright environments.
{"title":"A Thermal Camera-based Activity Recognition Using Discriminant Skeleton Features and RNN","authors":"Md. Zia Uddin, W. Khaksar, J. Tørresen","doi":"10.1109/INDIN41052.2019.8972082","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972082","url":null,"abstract":"Recognizing human activities from sensor data is one of the key areas of image processing, computer vision, and pattern recognition researches today. The target of human activity recognition (HAR) is usually to detect and analyze distinguished activities from the data acquired via different sensors (e.g. thermal cameras). This work proposes a HAR approach from videos recorded via a thermal camera. Skeletons of human bodies are extracted from thermal frames using an opensource deep convolutional neural network (CNN)-based approach named OpenPose. It is generally applied on videos of typical color cameras. However, this work adopts OpenPose on thermal images to extract useful features so that the HAR system can be deployed in environments with low lights as well. Once skeletons of human silhouettes are obtained from the thermal images, robust spatiotemporal features are extracted followed by discriminant analysis. Finally, the discriminant features are fed into a deep recurrent neural network (RNN) for activity training and recognition. The proposed HAR method can be applied to monitor the users such as elderly in both bright and dark environments to prolong their independent life, unlike other typical color cameras which are generally applied in bright environments.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126177932","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972031
Emanuel Palm, O. Schelén, Ulf Bodin, Richard Hedman
Many use cases coming out of initiatives such as Industry 4.0 and Ubiquitous Computing require that systems be able to cooperate by negotiating about and agreeing on the exchange of arbitrary values. While solutions able to facilitate such negotiation exist, they tend to either be domain-specific or lack mechanisms for non-repudiation, which make them unfit for the heterogeneity and scale of many compelling applications. In this paper, we present the Exchange Network, a general-purpose and implementation-independent architecture for digital negotiation and non-repudiable exchanges of tokens, which are symbolic representations of arbitrary values. We consider the implications of implementing the architecture in three different ways, using a common database, a blockchain, and our own Signature Chain data structure, which we also describe. We demonstrate the feasibility of the architecture by outlining our own implementation of it and also describe a supply-chain scenario inspired by one transportation process at Volvo Trucks.
{"title":"The Exchange Network: An Architecture for the Negotiation of Non-Repudiable Token Exchanges","authors":"Emanuel Palm, O. Schelén, Ulf Bodin, Richard Hedman","doi":"10.1109/INDIN41052.2019.8972031","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972031","url":null,"abstract":"Many use cases coming out of initiatives such as Industry 4.0 and Ubiquitous Computing require that systems be able to cooperate by negotiating about and agreeing on the exchange of arbitrary values. While solutions able to facilitate such negotiation exist, they tend to either be domain-specific or lack mechanisms for non-repudiation, which make them unfit for the heterogeneity and scale of many compelling applications. In this paper, we present the Exchange Network, a general-purpose and implementation-independent architecture for digital negotiation and non-repudiable exchanges of tokens, which are symbolic representations of arbitrary values. We consider the implications of implementing the architecture in three different ways, using a common database, a blockchain, and our own Signature Chain data structure, which we also describe. We demonstrate the feasibility of the architecture by outlining our own implementation of it and also describe a supply-chain scenario inspired by one transportation process at Volvo Trucks.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125832765","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972229
Zahra Ramezani, Nicholas Smallbone, Martin Fabian, K. Åkesson
We consider the falsification of temporal logic properties as a method to test complex systems, such as autonomous systems. Since these systems are often safety-critical, it is important to assess whether they fulfill given specifications or not. An adaptive cruise controller for an autonomous car is considered where the closed-loop model has unknown parameters and an important problem is to find parameter combinations for which given specification are broken. We assume that the closed-loop system can be simulated with the known given parameters, no other information is available to the testing framework. The specification, such as, the ability to avoid collisions, is expressed using Signal Temporal Logic (STL). In general, systems consist of a large number of parameters, and it is not possible or feasible to explicitly enumerate all combinations of the parameters. Thus, an optimization-based approach is used to guide the search for parameters that might falsify the specification. However, a key challenge is how to select the objective function such that the falsification of the specification, if it can be falsified, can be falsified using as few simulations as possible. For falsification using optimization it is required to have a measure representing the distance to the falsification of the specification. The way the measure is defined results in different objective functions used during optimization. Different measures have been proposed in the literature and in this paper the properties of the Max Semantics (MAX) and the Mean Alternative Robustness Value (MARV) semantics are discussed. After evaluating these two semantics on an adaptive cruise control example, we discuss their strengths and weaknesses to better understand the properties of the two semantics.
{"title":"Evaluating Two Semantics for Falsification using an Autonomous Driving Example","authors":"Zahra Ramezani, Nicholas Smallbone, Martin Fabian, K. Åkesson","doi":"10.1109/INDIN41052.2019.8972229","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972229","url":null,"abstract":"We consider the falsification of temporal logic properties as a method to test complex systems, such as autonomous systems. Since these systems are often safety-critical, it is important to assess whether they fulfill given specifications or not. An adaptive cruise controller for an autonomous car is considered where the closed-loop model has unknown parameters and an important problem is to find parameter combinations for which given specification are broken. We assume that the closed-loop system can be simulated with the known given parameters, no other information is available to the testing framework. The specification, such as, the ability to avoid collisions, is expressed using Signal Temporal Logic (STL). In general, systems consist of a large number of parameters, and it is not possible or feasible to explicitly enumerate all combinations of the parameters. Thus, an optimization-based approach is used to guide the search for parameters that might falsify the specification. However, a key challenge is how to select the objective function such that the falsification of the specification, if it can be falsified, can be falsified using as few simulations as possible. For falsification using optimization it is required to have a measure representing the distance to the falsification of the specification. The way the measure is defined results in different objective functions used during optimization. Different measures have been proposed in the literature and in this paper the properties of the Max Semantics (MAX) and the Mean Alternative Robustness Value (MARV) semantics are discussed. After evaluating these two semantics on an adaptive cruise control example, we discuss their strengths and weaknesses to better understand the properties of the two semantics.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126681701","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972078
Reuben Borrison, Benjamin Kloepper, Jennifer Mullen
Data preparation for data mining in industrial applications is a key success factor which requires considerable repeated efforts. Although the required activities need to be repeated in very similar fashion across many projects, details of their implementation differ and require both application understanding and experience. As a result, data preparation is done by data mining experts with a strong domain background and a good understanding of the characteristics of the data to be analyzed. Experts with these profiles usually have an engineering background and no strong expertise in distributed programming or big data technology. Unfortunately, the amount of data can be so large that distributed algorithms are required to allow for inspection of results and iteration of preparation steps. This contribution introduces an interactive data preparation workflow for signal data from chemical plants enabling domain experts without background in distributed computing and extensive programming experience to leverage the power of big data technologies.
{"title":"Data Preparation for Data Mining in Chemical Plants using Big Data","authors":"Reuben Borrison, Benjamin Kloepper, Jennifer Mullen","doi":"10.1109/INDIN41052.2019.8972078","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972078","url":null,"abstract":"Data preparation for data mining in industrial applications is a key success factor which requires considerable repeated efforts. Although the required activities need to be repeated in very similar fashion across many projects, details of their implementation differ and require both application understanding and experience. As a result, data preparation is done by data mining experts with a strong domain background and a good understanding of the characteristics of the data to be analyzed. Experts with these profiles usually have an engineering background and no strong expertise in distributed programming or big data technology. Unfortunately, the amount of data can be so large that distributed algorithms are required to allow for inspection of results and iteration of preparation steps. This contribution introduces an interactive data preparation workflow for signal data from chemical plants enabling domain experts without background in distributed computing and extensive programming experience to leverage the power of big data technologies.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127297450","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 : 2019-07-01DOI: 10.1109/INDIN41052.2019.8972053
J. Long, Sam Matsumoto
Hacking of every-day sensors is now a common problem with a disproportionate impact over life-critical assets. It is precisely because they are low-cost and low-complexity that these sensors make such easy targets that this problem will grow exponentially as sensors become more indispensable to modern life. This paper examines the impact of sensor hacking and offers a two-phase approach to security: a low-cost authentication scheme and a novel Machine Learning approach using a Malware Predictive Interpreter.
{"title":"Cryptographic Strength and Machine Learning Security for Low Complexity IoT Sensors","authors":"J. Long, Sam Matsumoto","doi":"10.1109/INDIN41052.2019.8972053","DOIUrl":"https://doi.org/10.1109/INDIN41052.2019.8972053","url":null,"abstract":"Hacking of every-day sensors is now a common problem with a disproportionate impact over life-critical assets. It is precisely because they are low-cost and low-complexity that these sensors make such easy targets that this problem will grow exponentially as sensors become more indispensable to modern life. This paper examines the impact of sensor hacking and offers a two-phase approach to security: a low-cost authentication scheme and a novel Machine Learning approach using a Malware Predictive Interpreter.","PeriodicalId":260220,"journal":{"name":"2019 IEEE 17th International Conference on Industrial Informatics (INDIN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125068867","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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