In this paper, an optimum dynamic programming (DP) based time-normalization algorithm is designed for Network traffic anomaly detection. The two sets of data matched namely the sample data and the actual data, will need to calculate the time normalized distance through dynamic programming so as to achieve the effect of the anomaly detection, and have been using dynamic programming matching symmetry. By analyzing the experimental data, the traffic anomaly detection based on symmetry dynamic programming verify the improvement in the accuracy.
{"title":"Network Traffic Anomaly Detection Based on Dynamic Programming","authors":"Qing Yu, Xi-Wu Gu","doi":"10.1109/CIIS.2017.18","DOIUrl":"https://doi.org/10.1109/CIIS.2017.18","url":null,"abstract":"In this paper, an optimum dynamic programming (DP) based time-normalization algorithm is designed for Network traffic anomaly detection. The two sets of data matched namely the sample data and the actual data, will need to calculate the time normalized distance through dynamic programming so as to achieve the effect of the anomaly detection, and have been using dynamic programming matching symmetry. By analyzing the experimental data, the traffic anomaly detection based on symmetry dynamic programming verify the improvement in the accuracy.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121404744","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}
Fuzzy control has lots of advantages compared with traditional PID control. Good performance can be obtained by fuzzy control without mathematic model of control object. Meanwhile, fuzzy controller is equipped with high stability and robustness. The characteristics of traditional PID control and fuzzy controls were integrated as fuzzy PID control, greatly enhancing performance of the controller. The work discussed the design of fuzzy parameter self-tuning PID controller. The performance of the controller was compared with traditional PID controller mainly from the robustness. Results indicated robustness of fuzzy PID controller is better after comparison.
{"title":"Study on the Robustness Based on PID Fuzzy Controller","authors":"Q. Song, Yaochun Wu","doi":"10.1109/CIIS.2017.30","DOIUrl":"https://doi.org/10.1109/CIIS.2017.30","url":null,"abstract":"Fuzzy control has lots of advantages compared with traditional PID control. Good performance can be obtained by fuzzy control without mathematic model of control object. Meanwhile, fuzzy controller is equipped with high stability and robustness. The characteristics of traditional PID control and fuzzy controls were integrated as fuzzy PID control, greatly enhancing performance of the controller. The work discussed the design of fuzzy parameter self-tuning PID controller. The performance of the controller was compared with traditional PID controller mainly from the robustness. Results indicated robustness of fuzzy PID controller is better after comparison.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122825998","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}
M. A. A. Sibahee, Songfeng Lu, Z. Hussien, M. Hussain, Keyan Abdul-Aziz Mutlaq, Z. Abduljabbar
Wireless Sensor Networks (WSNs), applications are growing rapidly, so the needs to protect such applications are increased. Cryptography plays a main role in information system security where encryption algorithm is the essential component of the security. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper provides evaluation of four of the most common encryption algorithms namely: RC4, DES, and AES as a symmetric cipher and RSA for asymmetric cipher. A comparison has been conducted for those encryption algorithms at different settings such as different sizes of data blocks, different key size and finally encryption/decryption speed. Simulation results are given to demonstrate the effectiveness of each algorithm on power consuming.
{"title":"The Best Performance Evaluation of Encryption Algorithms to Reduce Power Consumption in WSN","authors":"M. A. A. Sibahee, Songfeng Lu, Z. Hussien, M. Hussain, Keyan Abdul-Aziz Mutlaq, Z. Abduljabbar","doi":"10.1109/CIIS.2017.50","DOIUrl":"https://doi.org/10.1109/CIIS.2017.50","url":null,"abstract":"Wireless Sensor Networks (WSNs), applications are growing rapidly, so the needs to protect such applications are increased. Cryptography plays a main role in information system security where encryption algorithm is the essential component of the security. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper provides evaluation of four of the most common encryption algorithms namely: RC4, DES, and AES as a symmetric cipher and RSA for asymmetric cipher. A comparison has been conducted for those encryption algorithms at different settings such as different sizes of data blocks, different key size and finally encryption/decryption speed. Simulation results are given to demonstrate the effectiveness of each algorithm on power consuming.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131261575","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}
Redundancy is a traditional technique for improving the reliability of distributed systems. In many scenes, system redundancy is not available or not feasible. How to assign the tasks of parallel applications to the distributed system's processors and maximize the reliability of the system becomes one of the important issues that need to be studied. This paper proposes a dynamic non-redundant data allocation method for distributed database system, which specifies the fragment update parameters and dynamic cost parameters, to find the best solution for reallocating redundant data. Specifically, we use the parameters to iterative estimate the reassignment of the fragment to the cost of the node, according to the choice of the lowest cost of the node for data migration. The result shows that this kind of scheme can make full use of the advantages of non-redundant data allocation and fasten the speech of communication, which can further improve the consistency and reliability of the distributed database system.
{"title":"Non-redundant Distributed Database Allocation Technology Research","authors":"Qiao Sun, Bu-qiao Deng, Lan-mei Fu, Jiasong Sun","doi":"10.1109/CIIS.2017.57","DOIUrl":"https://doi.org/10.1109/CIIS.2017.57","url":null,"abstract":"Redundancy is a traditional technique for improving the reliability of distributed systems. In many scenes, system redundancy is not available or not feasible. How to assign the tasks of parallel applications to the distributed system's processors and maximize the reliability of the system becomes one of the important issues that need to be studied. This paper proposes a dynamic non-redundant data allocation method for distributed database system, which specifies the fragment update parameters and dynamic cost parameters, to find the best solution for reallocating redundant data. Specifically, we use the parameters to iterative estimate the reassignment of the fragment to the cost of the node, according to the choice of the lowest cost of the node for data migration. The result shows that this kind of scheme can make full use of the advantages of non-redundant data allocation and fasten the speech of communication, which can further improve the consistency and reliability of the distributed database system.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132457963","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}
In recent years, Cloud Computing becomes more prevalent in data store domain. More and more sensitive to store information into the cloud, Due to the importance the protection of data privacy, to protect sensitive data, should be encrypted before outsourcing, which makes ineffective data utilization and a very challenging task. Although the protection of the privacy of the data has to be encrypted, There should be schemes allow a user to securely search over encrypted data through keywords and selectively retrieve the appropriate files interest. These techniques support only exact searchable over encryption. In this paper, find a solution to the problem of effective keyword search over encrypted cloud data while maintaining keyword privacy. Keyword search greatly enhances system usability by returning the matching files when users' searching inputs exactly match the predefined keywords. In our solution, we extract the keywords from the file and encrypted the keywords then added into the index. Instead of storing file and searchable index on a cloud system, the proposed system will store the file on cloud and store searchable index on a private server. Which greatly reduces network congestion and representation overheads, also retrieval fast for files, and reduces the storage by file compression With enhanced security using encryption techniques and permission to access the data, through accurate security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of retrieval data.
{"title":"Secure Cloud Storage and Quick Keyword Based Retrieval System","authors":"Song Lu, Abdulruhman I Ahmed Abomakhelb","doi":"10.1109/CIIS.2017.67","DOIUrl":"https://doi.org/10.1109/CIIS.2017.67","url":null,"abstract":"In recent years, Cloud Computing becomes more prevalent in data store domain. More and more sensitive to store information into the cloud, Due to the importance the protection of data privacy, to protect sensitive data, should be encrypted before outsourcing, which makes ineffective data utilization and a very challenging task. Although the protection of the privacy of the data has to be encrypted, There should be schemes allow a user to securely search over encrypted data through keywords and selectively retrieve the appropriate files interest. These techniques support only exact searchable over encryption. In this paper, find a solution to the problem of effective keyword search over encrypted cloud data while maintaining keyword privacy. Keyword search greatly enhances system usability by returning the matching files when users' searching inputs exactly match the predefined keywords. In our solution, we extract the keywords from the file and encrypted the keywords then added into the index. Instead of storing file and searchable index on a cloud system, the proposed system will store the file on cloud and store searchable index on a private server. Which greatly reduces network congestion and representation overheads, also retrieval fast for files, and reduces the storage by file compression With enhanced security using encryption techniques and permission to access the data, through accurate security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of retrieval data.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"6 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120835880","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}
Software reliability is an essential quality indicator which can provide critical messages for software managers. Due to fact that most of researchers might improperly infer the variance regarding the mean value function, its confidence interval would not conform to the real world situation. In this situation, software manager cannot accurately estimate the possible risk variation of software system by using the randomness of mean value function, and it might debase the practicability of applications. In this paper, Ohba's model is used to build the SRGM with confidence intervals that can help the software developers to effectively determine the optimal release time in practice.
{"title":"Effective Confidence Interval Estimation Based on Ohba's Software Reliability Growth Model","authors":"Po-Chiang Tsai, Chih-Chiang Fang","doi":"10.1109/CIIS.2017.38","DOIUrl":"https://doi.org/10.1109/CIIS.2017.38","url":null,"abstract":"Software reliability is an essential quality indicator which can provide critical messages for software managers. Due to fact that most of researchers might improperly infer the variance regarding the mean value function, its confidence interval would not conform to the real world situation. In this situation, software manager cannot accurately estimate the possible risk variation of software system by using the randomness of mean value function, and it might debase the practicability of applications. In this paper, Ohba's model is used to build the SRGM with confidence intervals that can help the software developers to effectively determine the optimal release time in practice.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120931467","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}
With the fast development of information technology and increasing number of image database, how to retrieval a large amount of information from the image quickly and effectively becomes more and more important. Brain Storm Optimization (BSO) is simple, robust and has high searching precision. So it is applied into the image retrieval in this paper. Content-based image retrieval (CBIR) extracts the color, texture, shape and other low-level visual features of images to realize image matching. Compared with image retrieval based on single feature, image retrieval based on multi-feature fusion can fully represent image information. In the multi-feature fusion, the ratio of each feature selection is critical to the search result. Traditional method is manually set or proportional integration, which ignores the priority between the various features. This paper uses BSO for image retrieval. Color histogram, color moment, color structure descriptor, Tamura texture feature, GLCM texture, wavelet transform texture, Gabor transform texture, edge histogram descriptors and Hu invariant moment are extracted in the paper and BSO is used for image retrieval. Experiment results show that the proposed method can retrieval the target image accurately and improve the precision of the system.
{"title":"Content-Based Image Retrieval Based on Multi-feature Fusion Optimized by Brain Storm Optimization","authors":"Hengjun Zhou, M. Jiang","doi":"10.1109/CIIS.2017.20","DOIUrl":"https://doi.org/10.1109/CIIS.2017.20","url":null,"abstract":"With the fast development of information technology and increasing number of image database, how to retrieval a large amount of information from the image quickly and effectively becomes more and more important. Brain Storm Optimization (BSO) is simple, robust and has high searching precision. So it is applied into the image retrieval in this paper. Content-based image retrieval (CBIR) extracts the color, texture, shape and other low-level visual features of images to realize image matching. Compared with image retrieval based on single feature, image retrieval based on multi-feature fusion can fully represent image information. In the multi-feature fusion, the ratio of each feature selection is critical to the search result. Traditional method is manually set or proportional integration, which ignores the priority between the various features. This paper uses BSO for image retrieval. Color histogram, color moment, color structure descriptor, Tamura texture feature, GLCM texture, wavelet transform texture, Gabor transform texture, edge histogram descriptors and Hu invariant moment are extracted in the paper and BSO is used for image retrieval. Experiment results show that the proposed method can retrieval the target image accurately and improve the precision of the system.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"393 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122994705","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}
In order to realize the rapid and exact image registration, a multi-modal image registration algorithm under the framework of membrane computing is proposed in this paper, which is named as MCIR algorithm. First, a cell-like P system of membrane structure is designed. Each object in membranes represents a group of transform parameters of floated images. All objects are constantly evolved by the group intelligent algorithm, which obtains the best parameters and transforms them into upper-layer membrane. At the same time, the best objects between the same layers transport randomly in the process of evolution. Finally, the global optimal object is stored in the skin membrane. The proposed MCIR algorithm is evaluated on the multi-modal image, such as the computer tomography (CT) images of the brain, the visible images, and the thermal infrared images. Our algorithm is superior to other methods in terms of properties of global convergence and obtains better registration accuracy and robustness.
{"title":"MCIR: A Multi-modal Image Registration Algorithm Based on Membrane Computing","authors":"Zhilv Gao, Chengfang Zhang","doi":"10.1109/CIIS.2017.46","DOIUrl":"https://doi.org/10.1109/CIIS.2017.46","url":null,"abstract":"In order to realize the rapid and exact image registration, a multi-modal image registration algorithm under the framework of membrane computing is proposed in this paper, which is named as MCIR algorithm. First, a cell-like P system of membrane structure is designed. Each object in membranes represents a group of transform parameters of floated images. All objects are constantly evolved by the group intelligent algorithm, which obtains the best parameters and transforms them into upper-layer membrane. At the same time, the best objects between the same layers transport randomly in the process of evolution. Finally, the global optimal object is stored in the skin membrane. The proposed MCIR algorithm is evaluated on the multi-modal image, such as the computer tomography (CT) images of the brain, the visible images, and the thermal infrared images. Our algorithm is superior to other methods in terms of properties of global convergence and obtains better registration accuracy and robustness.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122149292","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}
Yuchen Xie, Qing Yang, Pan Lin, Y. Leng, Yuankui Yang, Haixian Wang, S. Ge
We developed a highly accurate, few-channel, bimodal electroencephalograph (EEG) and near-infrared spectroscopy (NIRS) brain-computer interface (BCI) system by developing new methods for signal processing and feature extraction. For data processing, we performed source analysis of EEG and NIRS signals to select the best channels from which to build a few-channel system. For EEG feature extraction, we used phase space reconstruction to convert EEG few-channel signals into multichannel signals, facilitating the extraction of EEG features by common spatial pattern. The Hurst exponent of the selected 10 channels constituted the extracted NIRS data feature. For pattern classification, we fused EEG and NIRS features together and used the support vector machine classification method. The average accuracy of bimodal EEG-NIRS was significantly higher than that of either EEG or NIRS as unimodal techniques.
{"title":"Application of Phase Space Reconstruction in a Few-Channel EEG-NIRS Bimodal Brain-Computer Interface System","authors":"Yuchen Xie, Qing Yang, Pan Lin, Y. Leng, Yuankui Yang, Haixian Wang, S. Ge","doi":"10.1109/CIIS.2017.19","DOIUrl":"https://doi.org/10.1109/CIIS.2017.19","url":null,"abstract":"We developed a highly accurate, few-channel, bimodal electroencephalograph (EEG) and near-infrared spectroscopy (NIRS) brain-computer interface (BCI) system by developing new methods for signal processing and feature extraction. For data processing, we performed source analysis of EEG and NIRS signals to select the best channels from which to build a few-channel system. For EEG feature extraction, we used phase space reconstruction to convert EEG few-channel signals into multichannel signals, facilitating the extraction of EEG features by common spatial pattern. The Hurst exponent of the selected 10 channels constituted the extracted NIRS data feature. For pattern classification, we fused EEG and NIRS features together and used the support vector machine classification method. The average accuracy of bimodal EEG-NIRS was significantly higher than that of either EEG or NIRS as unimodal techniques.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131361080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper mainly proposed a kind of algorithm based on moving object detection and direction recognition, with a variety of data in video surveillance system, constructing a moving objects trajectories system with a combination of artificial and video surveillance system, to find escape routes of suspects accurately and make work easy for investigators. This system was created by Python language, MySQL database language and Open CV direction recognition technology, completing usage of map, creating database structure and recognizing the direction of a moving object, to predict object moving direction.
{"title":"Mathematical Modeling of Pursuit-Evasion System for Video Surveillance Network","authors":"Wenjun Wang, Fanliang Bu","doi":"10.1109/CIIS.2017.48","DOIUrl":"https://doi.org/10.1109/CIIS.2017.48","url":null,"abstract":"This paper mainly proposed a kind of algorithm based on moving object detection and direction recognition, with a variety of data in video surveillance system, constructing a moving objects trajectories system with a combination of artificial and video surveillance system, to find escape routes of suspects accurately and make work easy for investigators. This system was created by Python language, MySQL database language and Open CV direction recognition technology, completing usage of map, creating database structure and recognizing the direction of a moving object, to predict object moving direction.","PeriodicalId":254342,"journal":{"name":"2017 International Conference on Computing Intelligence and Information System (CIIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130016276","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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