Pub Date : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096720
Hajar Barrak Alharbi, Nuha Abdulrazak Baghanim, A. Munshi
Internet of Things (IoT) is an emerging technology which has revolutionized the network in the global world. It is estimated that about 38.5 billion IoT devices will be connected by 2020. These devices are used in every part of life. Large number of data are collected by these IoT devices and transmitted from one device to another and from devices to enterprise systems. As large numbers of devices are connected with each other and to the world network and the number is increasing every day, there is a major risk of security threat, vulnerabilities, data manipulation, stealing, identity, device manipulation, and hacking. Due to the ease of automation and digitization, these devices bring with them numerous security issues. Poor security of these devices can provide an entry point for cyberattacks which may compromise sensitive data, threaten users’ privacy and weaponize the device. The IoT ecosystem needs proper security at device level, application level, and network level. Different vendors with diverse goals but inadequate cybersecurity expertise manufacture these devices. The purpose of this paper is to identify the current security and privacy issues in IoT devices and propose recommendations for the solution of Cyber security issues in IoT devices
{"title":"Cyber Risk in Internet of Things World","authors":"Hajar Barrak Alharbi, Nuha Abdulrazak Baghanim, A. Munshi","doi":"10.1109/ICCAIS48893.2020.9096720","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096720","url":null,"abstract":"Internet of Things (IoT) is an emerging technology which has revolutionized the network in the global world. It is estimated that about 38.5 billion IoT devices will be connected by 2020. These devices are used in every part of life. Large number of data are collected by these IoT devices and transmitted from one device to another and from devices to enterprise systems. As large numbers of devices are connected with each other and to the world network and the number is increasing every day, there is a major risk of security threat, vulnerabilities, data manipulation, stealing, identity, device manipulation, and hacking. Due to the ease of automation and digitization, these devices bring with them numerous security issues. Poor security of these devices can provide an entry point for cyberattacks which may compromise sensitive data, threaten users’ privacy and weaponize the device. The IoT ecosystem needs proper security at device level, application level, and network level. Different vendors with diverse goals but inadequate cybersecurity expertise manufacture these devices. The purpose of this paper is to identify the current security and privacy issues in IoT devices and propose recommendations for the solution of Cyber security issues in IoT devices","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130588548","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 : 2020-03-01DOI: 10.1109/iccais48893.2020.9096712
{"title":"ICCAIS 2020 TOC","authors":"","doi":"10.1109/iccais48893.2020.9096712","DOIUrl":"https://doi.org/10.1109/iccais48893.2020.9096712","url":null,"abstract":"","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134367488","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096725
Tanveer Ahmad, Nauman Ahmed, J. Peltenburg, Z. Al-Ars
The rapidly growing size of genomics data bases, driven by advances in sequencing technologies, demands fast and cost-effective processing. However, processing this data creates many challenges, particularly in selecting appropriate algorithms and computing platforms. Computing systems need data closer to the processor for fast processing. Traditionally, due to cost, volatility and other physical constraints of DRAM, it was not feasible to place large amounts of working data sets in memory. However, new emerging storage class memories allow storing and processing big data closer to the processor. In this work, we show how the commonly used genomics data format, Sequence Alignment/Map (SAM), can be presented in the Apache Arrow in-memory data representation to benefit of in-memory processing and to ensure better scalability through shared memory objects, by avoiding large (de)-serialization overheads in cross-language interoperability. To demonstrate the benefits of such a system, we propose ArrowSAM, an in-memory SAM format that uses the Apache Arrow framework, and integrate it into genome pre-processing pipelines including BWA-MEM, Picard and Sambamba. Results show 15x and 2.4x speedups as compared to Picard and Sambamba, respectively. The code and scripts for running all workflows are freely available at https://github.com/abs-tudelft/ArrowSAM.
{"title":"ArrowSAM: In-Memory Genomics Data Processing Using Apache Arrow","authors":"Tanveer Ahmad, Nauman Ahmed, J. Peltenburg, Z. Al-Ars","doi":"10.1109/ICCAIS48893.2020.9096725","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096725","url":null,"abstract":"The rapidly growing size of genomics data bases, driven by advances in sequencing technologies, demands fast and cost-effective processing. However, processing this data creates many challenges, particularly in selecting appropriate algorithms and computing platforms. Computing systems need data closer to the processor for fast processing. Traditionally, due to cost, volatility and other physical constraints of DRAM, it was not feasible to place large amounts of working data sets in memory. However, new emerging storage class memories allow storing and processing big data closer to the processor. In this work, we show how the commonly used genomics data format, Sequence Alignment/Map (SAM), can be presented in the Apache Arrow in-memory data representation to benefit of in-memory processing and to ensure better scalability through shared memory objects, by avoiding large (de)-serialization overheads in cross-language interoperability. To demonstrate the benefits of such a system, we propose ArrowSAM, an in-memory SAM format that uses the Apache Arrow framework, and integrate it into genome pre-processing pipelines including BWA-MEM, Picard and Sambamba. Results show 15x and 2.4x speedups as compared to Picard and Sambamba, respectively. The code and scripts for running all workflows are freely available at https://github.com/abs-tudelft/ArrowSAM.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133504299","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096738
Sarah. A Alkhaldi, Sultana Alzuabi, Ryoof Alqahtani, A. Alshammari, Fatimah J. Alyousif, D. Alboaneen, Modhe Almelihi
Sentiment analysis can be defined as a natural language process to determine the individual’s sentiment or opinion towards something. It helps institutions, companies and governments to gain a deeper understanding and supports decision-making. This paper aims to analyse individuals’ opinions in Twitter on the activities of the Saudi General Entertainment Authority (GEA) using machine and deep learning techniques. To achieve this aim, 3,817 tweets were collected using RapidMiner. To classify tweets into supporters and opposers, three machine learning algorithms were used namely, Multi-Layer Percptron (MLP), Support Vector Machine (SVM), Random Forest (RF), and one deep learning algorithm, which is Recurrent Neural Network (RNN). Two test options were applied to evaluate the classification model, percentage split and K-fold validation tests. The results show that the people are happy and agree with the GEAs’ activities. As for the gender, the support rate of females was higher than males. In addition, RF algorithm outperforms other algorithms in terms of the classification accuracy and the error rate.
{"title":"Twitter Sentiment Analysis on Activities of Saudi General Entertainment Authority","authors":"Sarah. A Alkhaldi, Sultana Alzuabi, Ryoof Alqahtani, A. Alshammari, Fatimah J. Alyousif, D. Alboaneen, Modhe Almelihi","doi":"10.1109/ICCAIS48893.2020.9096738","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096738","url":null,"abstract":"Sentiment analysis can be defined as a natural language process to determine the individual’s sentiment or opinion towards something. It helps institutions, companies and governments to gain a deeper understanding and supports decision-making. This paper aims to analyse individuals’ opinions in Twitter on the activities of the Saudi General Entertainment Authority (GEA) using machine and deep learning techniques. To achieve this aim, 3,817 tweets were collected using RapidMiner. To classify tweets into supporters and opposers, three machine learning algorithms were used namely, Multi-Layer Percptron (MLP), Support Vector Machine (SVM), Random Forest (RF), and one deep learning algorithm, which is Recurrent Neural Network (RNN). Two test options were applied to evaluate the classification model, percentage split and K-fold validation tests. The results show that the people are happy and agree with the GEAs’ activities. As for the gender, the support rate of females was higher than males. In addition, RF algorithm outperforms other algorithms in terms of the classification accuracy and the error rate.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"5 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132334598","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096715
F. Shaikh, Rawan H. Alghamdi, R. S. A. Alkabour, Rehab M. Alonaizan, D. A. AlBuhairi, Dalal M. Alyami, Waad S. Attiyah
This paper proposes an AHP based real-time solution to facilitate response to road flooding which is a recurrent issue in almost all cities in Saudi Arabia. In the event of heavy rains, municipalities face a surge in the demand to attend to road flooding incidents and it can be difficult to decide which road sections to prioritize. The study first introduces the proposed web-based road flooding management system which utilizes a variety of different information including real-time and historical weather data, digital terrain data and descriptive road parameters to provide flood response teams with clear information on the real-time status of roads. It then proposes the AHP based multi-parameter decision analysis solution which analyses the significance of the road parameters with respect to each other and assigns a specific response priority to each road section. This final priority will allow flood response teams to expedite the response to road sections with a higher priority, thus improving the efficiency of flood responses.
{"title":"Proactive Priority Based Response to Road Flooding using AHP: A Case Study in Dammam","authors":"F. Shaikh, Rawan H. Alghamdi, R. S. A. Alkabour, Rehab M. Alonaizan, D. A. AlBuhairi, Dalal M. Alyami, Waad S. Attiyah","doi":"10.1109/ICCAIS48893.2020.9096715","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096715","url":null,"abstract":"This paper proposes an AHP based real-time solution to facilitate response to road flooding which is a recurrent issue in almost all cities in Saudi Arabia. In the event of heavy rains, municipalities face a surge in the demand to attend to road flooding incidents and it can be difficult to decide which road sections to prioritize. The study first introduces the proposed web-based road flooding management system which utilizes a variety of different information including real-time and historical weather data, digital terrain data and descriptive road parameters to provide flood response teams with clear information on the real-time status of roads. It then proposes the AHP based multi-parameter decision analysis solution which analyses the significance of the road parameters with respect to each other and assigns a specific response priority to each road section. This final priority will allow flood response teams to expedite the response to road sections with a higher priority, thus improving the efficiency of flood responses.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114627598","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096834
Dimah Almani
The paper is a research report on data mining – a subject which has been studied widely and whose application spans a wide range of field including the Internet of Things (IoT) and business developments. Data mining techniques come along with serious challenges due to the disclosure of private information and violation of privacy. Privacy preservation data mining and security (PPDMS) is a vital branch in the science of data mining and an essential topic in privacy preservation. The subject has gained significant attention in the recent past. PPDMS protects sensitive and private data from being disclosed without permission from the providers or data owners. The paper gives a research report on PPDMS techniques. It outlines security measures employed in preserving data and compares the techniques’ advantages and disadvantages. The paper also suggests better ways to improve the methods.
{"title":"Privacy Preservation Data Mining and Security","authors":"Dimah Almani","doi":"10.1109/ICCAIS48893.2020.9096834","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096834","url":null,"abstract":"The paper is a research report on data mining – a subject which has been studied widely and whose application spans a wide range of field including the Internet of Things (IoT) and business developments. Data mining techniques come along with serious challenges due to the disclosure of private information and violation of privacy. Privacy preservation data mining and security (PPDMS) is a vital branch in the science of data mining and an essential topic in privacy preservation. The subject has gained significant attention in the recent past. PPDMS protects sensitive and private data from being disclosed without permission from the providers or data owners. The paper gives a research report on PPDMS techniques. It outlines security measures employed in preserving data and compares the techniques’ advantages and disadvantages. The paper also suggests better ways to improve the methods.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133729687","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096850
Hussain Alsalman
Recently, sentiment analysis of social media contents is very important for opinion mining in several applications and different fields. Arabic sentiment analysis is one of the more complicated sentiment analysis tools of social media due to the informal noisy contents and the rich morphology of Arabic language. There is a number of works has been proposed for Arabic sentiment analysis. However, these works need an improvement in terms of effectiveness and accuracy. Consequently, in this paper, a corpus-based approach is proposed for Arabic sentiment analysis of tweets annotated as either negative or positive in twitter social media. The approach is based on a Discriminative multinomial naïve Bayes (DMNB) method with N-grams tokenizer, stemming, and term frequency-inverse document frequency (TF-IDF) techniques. The experiments are conducted using a set of performance evaluation metrics on a public twitter dataset to test the proposed sentiment analysis approach. Experimental results demonstrated the usefulness of the proposed approach. Furthermore, the comparison results showed that the approach outperformed the related work and improved the accuracy with 0.3%.
{"title":"An Improved Approach for Sentiment Analysis of Arabic Tweets in Twitter Social Media","authors":"Hussain Alsalman","doi":"10.1109/ICCAIS48893.2020.9096850","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096850","url":null,"abstract":"Recently, sentiment analysis of social media contents is very important for opinion mining in several applications and different fields. Arabic sentiment analysis is one of the more complicated sentiment analysis tools of social media due to the informal noisy contents and the rich morphology of Arabic language. There is a number of works has been proposed for Arabic sentiment analysis. However, these works need an improvement in terms of effectiveness and accuracy. Consequently, in this paper, a corpus-based approach is proposed for Arabic sentiment analysis of tweets annotated as either negative or positive in twitter social media. The approach is based on a Discriminative multinomial naïve Bayes (DMNB) method with N-grams tokenizer, stemming, and term frequency-inverse document frequency (TF-IDF) techniques. The experiments are conducted using a set of performance evaluation metrics on a public twitter dataset to test the proposed sentiment analysis approach. Experimental results demonstrated the usefulness of the proposed approach. Furthermore, the comparison results showed that the approach outperformed the related work and improved the accuracy with 0.3%.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130545662","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096714
W. Saad, Abdulaziz S. Alsayyari
Animals (especially camels) vehicle collisions are a growing problem in the Kingdom of Saudi Arabia (KSA), resulting in loss of money, animals' lives and considerable human injury and death every year. Therefore, it has become an urgent need to implement a reliable system for camel detection and drivers warning for KSA. Although many existing systems were installed in other countries, they are not suitable for camels or the KSA environment. In this paper, a reliable, low cost, real time Internet of Things (IoT) based Camel-Vehicle Collision Avoidance (CVCA) system is proposed. The system consists of two main parts which are; the camel detection and the driver warning systems. It requires low data traffic to be uploaded to the cloud. Therefore, the probability of network congestion is very low. Moreover, it can be operated at night when most camel vehicles accidents occur.
{"title":"Real Time IoT Based Camel-Vehicle Collision Avoidance System for KSA","authors":"W. Saad, Abdulaziz S. Alsayyari","doi":"10.1109/ICCAIS48893.2020.9096714","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096714","url":null,"abstract":"Animals (especially camels) vehicle collisions are a growing problem in the Kingdom of Saudi Arabia (KSA), resulting in loss of money, animals' lives and considerable human injury and death every year. Therefore, it has become an urgent need to implement a reliable system for camel detection and drivers warning for KSA. Although many existing systems were installed in other countries, they are not suitable for camels or the KSA environment. In this paper, a reliable, low cost, real time Internet of Things (IoT) based Camel-Vehicle Collision Avoidance (CVCA) system is proposed. The system consists of two main parts which are; the camel detection and the driver warning systems. It requires low data traffic to be uploaded to the cloud. Therefore, the probability of network congestion is very low. Moreover, it can be operated at night when most camel vehicles accidents occur.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"810 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126956967","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096758
Eshraq Ali Alweshail, Hajar Brahim
Good health is a way of good life, however, vision 2030 in Saudi Arabia aims to expand the ways of providing home health care, this application is designed to provide home health care to people in remote areas or to people who can’t go to the hospital because of their working conditions or their health doesn’t allow them to travel or go to the hospital. There are many benefits of using this application. It helps the patients to open a new file without visiting the hospital, they also can communicate with their doctors or health care providers, request home services, evaluate the services that provided by healthcare providers, pay the fees of any services received, they can also verify laboratory results.By this way, the hospitals benefit from creating a new way to increase the number of patients (online or inside the hospital).
{"title":"A Smartphone Application to Provide the Health Care Services at Home","authors":"Eshraq Ali Alweshail, Hajar Brahim","doi":"10.1109/ICCAIS48893.2020.9096758","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096758","url":null,"abstract":"Good health is a way of good life, however, vision 2030 in Saudi Arabia aims to expand the ways of providing home health care, this application is designed to provide home health care to people in remote areas or to people who can’t go to the hospital because of their working conditions or their health doesn’t allow them to travel or go to the hospital. There are many benefits of using this application. It helps the patients to open a new file without visiting the hospital, they also can communicate with their doctors or health care providers, request home services, evaluate the services that provided by healthcare providers, pay the fees of any services received, they can also verify laboratory results.By this way, the hospitals benefit from creating a new way to increase the number of patients (online or inside the hospital).","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125746927","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 : 2020-03-01DOI: 10.1109/ICCAIS48893.2020.9096742
Waleed Alghamd, M. Schukat
The IEEE 1588 Precision Time Protocol (PTP) is a widely used mechanism to provide time synchronization of computer clocks down to microsecond accuracy as required by many financial and industrial applications ("IEEE Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems," 2008). However, PTP is vulnerable to infrastructure cyber-attacks that reduce the desired accuracy. IEEE 1588 defined an experimental security extension (Annex K) in order to protect a PTP network, but various drawbacks have been discovered, resulting in further improvements including the use of public-key encryption ( Itkin & Wool, 2020 ) and reduce the three-way handshake mechanism to one way authentication ( Önal & Kirrmann, 2012 ). Today Annex K is deprecated in favor of L2 / L3 security mechanisms. Further on, in 2020 a backwards compatible IEEE 1588 version (v2.1) will be introduced, that contains a new security extension called Annex S. Annex S consists of four prongs as follows ("IEEE Draft Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems," 2019): • Prong (A) PTP Integrated Security Mechanism describes an authentication type-length-value (TLV) that is aligned with and integrated into the PTP message. • Prong (B) PTP External Transport Security Mechanisms describes the current external security mechanisms that can be used to provide protection to PTP message i.e., IPsec and MACsec. • Prong (C) Architecture Guidance describes a redundant time system, redundant grandmaster, and redundant paths. • Prong D (Monitoring and Management Guidance) suggests monitoring the slaves’ synchronization process.
{"title":"A Detection Model Against Precision Time Protocol Attacks","authors":"Waleed Alghamd, M. Schukat","doi":"10.1109/ICCAIS48893.2020.9096742","DOIUrl":"https://doi.org/10.1109/ICCAIS48893.2020.9096742","url":null,"abstract":"The IEEE 1588 Precision Time Protocol (PTP) is a widely used mechanism to provide time synchronization of computer clocks down to microsecond accuracy as required by many financial and industrial applications (\"IEEE Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems,\" 2008). However, PTP is vulnerable to infrastructure cyber-attacks that reduce the desired accuracy. IEEE 1588 defined an experimental security extension (Annex K) in order to protect a PTP network, but various drawbacks have been discovered, resulting in further improvements including the use of public-key encryption ( Itkin & Wool, 2020 ) and reduce the three-way handshake mechanism to one way authentication ( Önal & Kirrmann, 2012 ). Today Annex K is deprecated in favor of L2 / L3 security mechanisms. Further on, in 2020 a backwards compatible IEEE 1588 version (v2.1) will be introduced, that contains a new security extension called Annex S. Annex S consists of four prongs as follows (\"IEEE Draft Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems,\" 2019): • Prong (A) PTP Integrated Security Mechanism describes an authentication type-length-value (TLV) that is aligned with and integrated into the PTP message. • Prong (B) PTP External Transport Security Mechanisms describes the current external security mechanisms that can be used to provide protection to PTP message i.e., IPsec and MACsec. • Prong (C) Architecture Guidance describes a redundant time system, redundant grandmaster, and redundant paths. • Prong D (Monitoring and Management Guidance) suggests monitoring the slaves’ synchronization process.","PeriodicalId":422184,"journal":{"name":"2020 3rd International Conference on Computer Applications & Information Security (ICCAIS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127058220","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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