Pub Date : 2019-06-01DOI: 10.1109/iacs.2019.8809130
{"title":"ICICS 2019 Sponsors","authors":"","doi":"10.1109/iacs.2019.8809130","DOIUrl":"https://doi.org/10.1109/iacs.2019.8809130","url":null,"abstract":"","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121335249","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809167
Y. M. Al-Rawashdeh, S. E. Ferik, M. A. Abido
In this paper, a robust full-car active suspension system is designed. All parameters involved, except those related to the chassis of the car, are considered uncertain and the center of gravity position is assumed to be fixed. The resulting uncertain system constitutes of many uncertain parameters and the robust problem is found to be non-convex. Particle Swarm Optimization technique is devised to solve this problem resulting in an iterative PSO/LMI optimization algorithm. SimMechanics is used to build the nonlinear full-car model and to allow future extensions such that complex cases can be considered, i.e., the passengers, goods, or the like might be uncertain or having their own dynamics onboard.
{"title":"Robust Full-Car Active Suspension System","authors":"Y. M. Al-Rawashdeh, S. E. Ferik, M. A. Abido","doi":"10.1109/IACS.2019.8809167","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809167","url":null,"abstract":"In this paper, a robust full-car active suspension system is designed. All parameters involved, except those related to the chassis of the car, are considered uncertain and the center of gravity position is assumed to be fixed. The resulting uncertain system constitutes of many uncertain parameters and the robust problem is found to be non-convex. Particle Swarm Optimization technique is devised to solve this problem resulting in an iterative PSO/LMI optimization algorithm. SimMechanics is used to build the nonlinear full-car model and to allow future extensions such that complex cases can be considered, i.e., the passengers, goods, or the like might be uncertain or having their own dynamics onboard.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124803116","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809108
S. Khanji, S. Assaf
Ridesharing or carpooling has a valuable potential in large cities that suffer from traffic jams and congestion especially in places with poor public transportation infrastructure and fuel trip expenses are too high. By increasing the level of vehicles occupancy; colleagues who share the same workplace can smoothly hop into each other’s vehicles to reach their destination. In this research paper we utilize the decentralization nature of the blockchain to build a smart ridesharing application – GreenRide - through incentivizing its users via token rewards. Our work investigates boosting ridesharing efficiency through utilizing the blockchain merits of decentralization, trustless, and scalability. We also emphasize on the application’s environmental impacts where it promotes carbon emission reduction, and enhances air quality. Moreover, the research paper identifies GreenRide’s economic and social impacts as per it helps road users to share the costly fuel expenses and to create friendships between like-minded people respectively. The research findings unlock the tremendous potential of the blockchain technology in other business-related fields not only limited to finance and cryptocurrencies.
{"title":"Boosting Ridesharing Efficiency Through Blockchain: GreenRide Application Case Study","authors":"S. Khanji, S. Assaf","doi":"10.1109/IACS.2019.8809108","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809108","url":null,"abstract":"Ridesharing or carpooling has a valuable potential in large cities that suffer from traffic jams and congestion especially in places with poor public transportation infrastructure and fuel trip expenses are too high. By increasing the level of vehicles occupancy; colleagues who share the same workplace can smoothly hop into each other’s vehicles to reach their destination. In this research paper we utilize the decentralization nature of the blockchain to build a smart ridesharing application – GreenRide - through incentivizing its users via token rewards. Our work investigates boosting ridesharing efficiency through utilizing the blockchain merits of decentralization, trustless, and scalability. We also emphasize on the application’s environmental impacts where it promotes carbon emission reduction, and enhances air quality. Moreover, the research paper identifies GreenRide’s economic and social impacts as per it helps road users to share the costly fuel expenses and to create friendships between like-minded people respectively. The research findings unlock the tremendous potential of the blockchain technology in other business-related fields not only limited to finance and cryptocurrencies.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124858966","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809132
Lana Issa, Mahdi Alkhatib, Aalaa Al-badarneh, A. Qusef
In today’s contemporary world, one of the most significant challenges facing most organizations is the challenge of employee retention. To remain efficient in an extremely competitive world, it is important for organizations to invest in measures that enhance the productivity and motivation of their workforce. In essence, this is the key to remaining relevant. Agile project management is the newest trend in project management methods that support concepts of flexibility and continuous improvements which help to keep an organization’s workforce efficient and motivated and reflect positively on employee retention. In this theoretical paper, we aim to critically analyze how the various Agile methods support employee retention better than traditional approaches by matching employee retention’s best practices within its approach. In this work, we found that agile systems implicitly handle several job satisfaction factor and thus help with employee retention without extra effort done by human resource management in traditional approaches.
{"title":"Employee Retention in Agile Project Management","authors":"Lana Issa, Mahdi Alkhatib, Aalaa Al-badarneh, A. Qusef","doi":"10.1109/IACS.2019.8809132","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809132","url":null,"abstract":"In today’s contemporary world, one of the most significant challenges facing most organizations is the challenge of employee retention. To remain efficient in an extremely competitive world, it is important for organizations to invest in measures that enhance the productivity and motivation of their workforce. In essence, this is the key to remaining relevant. Agile project management is the newest trend in project management methods that support concepts of flexibility and continuous improvements which help to keep an organization’s workforce efficient and motivated and reflect positively on employee retention. In this theoretical paper, we aim to critically analyze how the various Agile methods support employee retention better than traditional approaches by matching employee retention’s best practices within its approach. In this work, we found that agile systems implicitly handle several job satisfaction factor and thus help with employee retention without extra effort done by human resource management in traditional approaches.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128292754","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809123
Cerine Tafran, Mohamad El-Abed, Islam Elkabani, Ziad Osman
The Quality assessment of a face image is a topic of great interest for biometric applications where images with bad samples decrease the system performance and increase authentication errors, especially in biometric passport applications that use only a single image for enrollment. Thus, in order to have a useful biometric authentication system, the quality of the biometric sample images must be controlled. This paper presents a no-reference quality assessment method which detects the illumination problem using Symmetric Based Features along with BLIINDS Based Features. The experimental results on the AR database recorded an accuracy of 90.3 % by using Stochastic Gradient Descent (SGD) classifier.
{"title":"A No-Reference Image Quality Assessment For Detecting Illumination Alteration","authors":"Cerine Tafran, Mohamad El-Abed, Islam Elkabani, Ziad Osman","doi":"10.1109/IACS.2019.8809123","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809123","url":null,"abstract":"The Quality assessment of a face image is a topic of great interest for biometric applications where images with bad samples decrease the system performance and increase authentication errors, especially in biometric passport applications that use only a single image for enrollment. Thus, in order to have a useful biometric authentication system, the quality of the biometric sample images must be controlled. This paper presents a no-reference quality assessment method which detects the illumination problem using Symmetric Based Features along with BLIINDS Based Features. The experimental results on the AR database recorded an accuracy of 90.3 % by using Stochastic Gradient Descent (SGD) classifier.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129645245","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809174
Saif Rawashdeh, Walaa Eyadat, Areen Magableh, W. Mardini, M. B. Yasin
The smart world is an era in which things (e.g., cars, buses, computers, and mobile phones) can serve people in an effective and collaborative manner. Internet of Things (IoT) connects many devices with each other. IoT devises sense, gather, process, and transmit information from their surroundings. This transmission and exchange of a large amount of data between billions of devices cause massive consumption of energy. The central aim of Green IoT is reducing power consumption of IoT devices to create a safe and sustainable environment for IoT. In this paper, we presented an overview about IoT and the Green IoT, then classified the techniques of the Green IoT into three taxonomies that are Software Based Green IoT techniques, Hardware-Based Green IoT techniques and Policy Based Green IoT techniques. Finally, we compared many Green models, systems, and algorithms to improve and reduce the energy consumption of IoT devices.
{"title":"Sustainable Smart World","authors":"Saif Rawashdeh, Walaa Eyadat, Areen Magableh, W. Mardini, M. B. Yasin","doi":"10.1109/IACS.2019.8809174","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809174","url":null,"abstract":"The smart world is an era in which things (e.g., cars, buses, computers, and mobile phones) can serve people in an effective and collaborative manner. Internet of Things (IoT) connects many devices with each other. IoT devises sense, gather, process, and transmit information from their surroundings. This transmission and exchange of a large amount of data between billions of devices cause massive consumption of energy. The central aim of Green IoT is reducing power consumption of IoT devices to create a safe and sustainable environment for IoT. In this paper, we presented an overview about IoT and the Green IoT, then classified the techniques of the Green IoT into three taxonomies that are Software Based Green IoT techniques, Hardware-Based Green IoT techniques and Policy Based Green IoT techniques. Finally, we compared many Green models, systems, and algorithms to improve and reduce the energy consumption of IoT devices.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130896503","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809144
D. Maddi, A. Sheta, Dharani Davineni, Heba Al-Hiary
Design of the Proportional-Integral-Derivative (PID) controller for an industrial process represents a challenge due to process complexity and non-linearity. Traditional methods such as Ziegler-Nichols (ZN) for PID controller tuning do not provide an optimal gain; thus, might leave the system with potential instability condition and cause significant losses and damages to the system. This paper investigates the merits of evolutionary and swarm-based optimization algorithms in fine-tuning the parameters of a PID controller. Here, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) algorithm were utilized to optimize the PID controller for a DC motor system. Various fitness functions were provided for the presented algorithms to compute the performance of the controller. A new fitness function was proposed to achieve an outstanding control response for the DC motor system. Results demonstrate the efficacy of the proposed methods in improving closed loop system response.
{"title":"Optimization of PID Controller Gain Using Evolutionary Algorithm and Swarm Intelligence","authors":"D. Maddi, A. Sheta, Dharani Davineni, Heba Al-Hiary","doi":"10.1109/IACS.2019.8809144","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809144","url":null,"abstract":"Design of the Proportional-Integral-Derivative (PID) controller for an industrial process represents a challenge due to process complexity and non-linearity. Traditional methods such as Ziegler-Nichols (ZN) for PID controller tuning do not provide an optimal gain; thus, might leave the system with potential instability condition and cause significant losses and damages to the system. This paper investigates the merits of evolutionary and swarm-based optimization algorithms in fine-tuning the parameters of a PID controller. Here, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) algorithm were utilized to optimize the PID controller for a DC motor system. Various fitness functions were provided for the presented algorithms to compute the performance of the controller. A new fitness function was proposed to achieve an outstanding control response for the DC motor system. Results demonstrate the efficacy of the proposed methods in improving closed loop system response.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132891263","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809122
Hassan M. Najadat, Ahmad A. Alshboul, Abdullah Alabed
Recognition of Arabic handwritten characters is very important due to its various benefits and usages. Ancient documents, bank processing, postal mailing and others are examples where we may need character recognition systems. But many obstacles may be faced due to diversity of human writing styles. Language characters recognition has been widely covered in many languages and many algorithms and paradigms were used. With the strong appealing of deep CNN classifier promise results were reached in many classification problems. CNN is a feed forward neural network that is extensively used in several applications such as image classification. The main benefit of using CNN is the merging of feature extraction and classification itself. Some researchers used CNN in Arabic character recognition, one of those El-Sawy et al [1] who applied CNN architecture on a dataset namely (AHCD) of 16800 characters. They obtained a good accuracy of 94.9% and a misclassification error of 5.1% on testing data. In our paper we will explore their dataset by proposing a modified CNN architecture hopefully to overcome their results.
{"title":"Arabic Handwritten Characters Recognition using Convolutional Neural Network","authors":"Hassan M. Najadat, Ahmad A. Alshboul, Abdullah Alabed","doi":"10.1109/IACS.2019.8809122","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809122","url":null,"abstract":"Recognition of Arabic handwritten characters is very important due to its various benefits and usages. Ancient documents, bank processing, postal mailing and others are examples where we may need character recognition systems. But many obstacles may be faced due to diversity of human writing styles. Language characters recognition has been widely covered in many languages and many algorithms and paradigms were used. With the strong appealing of deep CNN classifier promise results were reached in many classification problems. CNN is a feed forward neural network that is extensively used in several applications such as image classification. The main benefit of using CNN is the merging of feature extraction and classification itself. Some researchers used CNN in Arabic character recognition, one of those El-Sawy et al [1] who applied CNN architecture on a dataset namely (AHCD) of 16800 characters. They obtained a good accuracy of 94.9% and a misclassification error of 5.1% on testing data. In our paper we will explore their dataset by proposing a modified CNN architecture hopefully to overcome their results.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128576547","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809117
Omar Almomani, Adeeb Saaidah, Firas Al Balas, L. Al-Qaisi
Congestion crumbles the network performance, therefore. This paper evaluates several Active Queue Management (AQM) algorithms which used to control congestion. The main Objective of the paper is to find optimal algorithm that can be use to avoid congestion. AQM are router based mechanism which can detect congestion in early stage in the network ask the transmitter to decrease its transmitting rate, in this way the network can control the congestion for incoming packets. So some of AQM algorithms were evaluated by analyzed their performance, the selected AQM algorithms are Gentle BLUE (GB), Dynamic Gentle Random Early Detection (DGRED), Effective Random Early Detection (ERED), BLUE and Adaptive Max Threshold algorithms. Performance evaluation is carried by using JAVA simulation environments. Evaluation results show that GB compared with DGRED, ERED, BLUE and Adaptive Max Threshold outperformed in terms of mean queue length, delay and packet loss. GB had maximum dropping probability as compare with DGRED, ERED, BLUE and Adaptive Max Threshold. In term of throughput all tested algorithms all most give same throughput. The results prove that the GB is can be appropriate algorithm to handle congestion as compare to DGRED, ERED, BLUE and Adaptive Max Threshold.
因此，拥塞会降低网络性能。本文评价了几种用于控制拥塞的主动队列管理(AQM)算法。本文的主要目标是找到可用于避免拥塞的最优算法。AQM是一种基于路由器的机制，它可以在网络的早期检测到拥塞，要求发送方降低传输速率，从而控制传入数据包的拥塞。本文通过对几种AQM算法的性能分析，对几种AQM算法进行了评价，选取的AQM算法有:Gentle BLUE (GB)算法、Dynamic Gentle Random Early Detection (DGRED)算法、Effective Random Early Detection (ERED)算法、BLUE算法和Adaptive Max Threshold算法。利用JAVA仿真环境进行性能评估。评估结果表明，与DGRED、ERED、BLUE和Adaptive Max Threshold算法相比，GB算法在平均队列长度、延迟和丢包方面表现优于DGRED算法。与DGRED、ERED、BLUE和Adaptive Max Threshold相比，GB具有最大的掉落概率。在吞吐量方面，所有被测试的算法都给出了相同的吞吐量。结果表明，与DGRED、ERED、BLUE和Adaptive Max Threshold算法相比，GB is算法是一种较好的拥塞处理算法。
{"title":"Simulation Based Performance Evaluation of Several Active Queue Management Algorithms for Computer Network","authors":"Omar Almomani, Adeeb Saaidah, Firas Al Balas, L. Al-Qaisi","doi":"10.1109/IACS.2019.8809117","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809117","url":null,"abstract":"Congestion crumbles the network performance, therefore. This paper evaluates several Active Queue Management (AQM) algorithms which used to control congestion. The main Objective of the paper is to find optimal algorithm that can be use to avoid congestion. AQM are router based mechanism which can detect congestion in early stage in the network ask the transmitter to decrease its transmitting rate, in this way the network can control the congestion for incoming packets. So some of AQM algorithms were evaluated by analyzed their performance, the selected AQM algorithms are Gentle BLUE (GB), Dynamic Gentle Random Early Detection (DGRED), Effective Random Early Detection (ERED), BLUE and Adaptive Max Threshold algorithms. Performance evaluation is carried by using JAVA simulation environments. Evaluation results show that GB compared with DGRED, ERED, BLUE and Adaptive Max Threshold outperformed in terms of mean queue length, delay and packet loss. GB had maximum dropping probability as compare with DGRED, ERED, BLUE and Adaptive Max Threshold. In term of throughput all tested algorithms all most give same throughput. The results prove that the GB is can be appropriate algorithm to handle congestion as compare to DGRED, ERED, BLUE and Adaptive Max Threshold.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115217732","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 : 2019-06-01DOI: 10.1109/IACS.2019.8809125
Qasem Abu Al-Haija, L. Tawalbeh
Recently, cybercrimes are causing huge impact on different cyber systems that might include vital information such as financial transactions and medical records. A better understanding of the accelerating numbers of cybercrimes and their enormous cost could help the global in bridging the gap between their defenses and the escalating numbers cyber criminals. In this paper, we present an estimation model of cybercrimes time series using auto-regressive (AR) model by employing the optimal modeling order that maximizes the estimation accuracy while maintaining minimum prediction error. The proposed model was developed using Matlab to estimate the time series for yearly global number of cybersecurity incidents activity during the period from 2009-2018 and forecast the figures for next upcoming years 2019-2020. The simulation results showed that the optimal model order to estimate the given cybercrime activity is AR(4) since its corresponds to minimum acceptable predication error values to estimate the signal recording an estimation accuracy of 93.5%.
{"title":"Autoregressive Modeling and Prediction of Annual Worldwide Cybercrimes for Cloud Environments","authors":"Qasem Abu Al-Haija, L. Tawalbeh","doi":"10.1109/IACS.2019.8809125","DOIUrl":"https://doi.org/10.1109/IACS.2019.8809125","url":null,"abstract":"Recently, cybercrimes are causing huge impact on different cyber systems that might include vital information such as financial transactions and medical records. A better understanding of the accelerating numbers of cybercrimes and their enormous cost could help the global in bridging the gap between their defenses and the escalating numbers cyber criminals. In this paper, we present an estimation model of cybercrimes time series using auto-regressive (AR) model by employing the optimal modeling order that maximizes the estimation accuracy while maintaining minimum prediction error. The proposed model was developed using Matlab to estimate the time series for yearly global number of cybersecurity incidents activity during the period from 2009-2018 and forecast the figures for next upcoming years 2019-2020. The simulation results showed that the optimal model order to estimate the given cybercrime activity is AR(4) since its corresponds to minimum acceptable predication error values to estimate the signal recording an estimation accuracy of 93.5%.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114146802","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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