Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359549
Hanxiao Shi, Yahui Zhang, Yiqian Zou, Xiaojun Li
There is a growing interest in sharing personal opinions on the Web, such as product reviews, economic analysis, political polls, etc. Existing research focuses on document-based approaches and documents are represented by bag-of-word. However, due to loss of contextual information, this representation fails to capture the associative information between an opinion and its corresponding target. Additionally, several researches focus on sentence-based approaches, which can effectively deal with an attribute-sentiment word pair within one sentence. However, those approaches are unable to process more than one attribute within one sentence. In this paper, we first present an improved sentiment word quantitative method to generate sentiment score for every word in sentiment lexicon. Additionally, we propose a novel identification approach of attribute-modifier-sentiment word triple using shallow semantic information. Experimental results show the feasibility and effectiveness of our approach.
{"title":"Fine-grained sentiment analysis of reviews using shallow semantic information","authors":"Hanxiao Shi, Yahui Zhang, Yiqian Zou, Xiaojun Li","doi":"10.1109/PIC.2017.8359549","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359549","url":null,"abstract":"There is a growing interest in sharing personal opinions on the Web, such as product reviews, economic analysis, political polls, etc. Existing research focuses on document-based approaches and documents are represented by bag-of-word. However, due to loss of contextual information, this representation fails to capture the associative information between an opinion and its corresponding target. Additionally, several researches focus on sentence-based approaches, which can effectively deal with an attribute-sentiment word pair within one sentence. However, those approaches are unable to process more than one attribute within one sentence. In this paper, we first present an improved sentiment word quantitative method to generate sentiment score for every word in sentiment lexicon. Additionally, we propose a novel identification approach of attribute-modifier-sentiment word triple using shallow semantic information. Experimental results show the feasibility and effectiveness of our approach.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124813779","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359562
Fangdong Zhu, Wen Chen, Yunpeng Wang, Ping Lin, Tao Li, Xiaochun Cao, Long Yuan
Online wallet has become an important method to manage Bitcoin. In a Bitcoin transaction, online wallet manages the private key automatically, and stores the encrypted private key in remote to ensure the accessibility of Bitcoin anywhere. In the traditional online wallet, the private key is stored centrally in a storage unit. However, if the storage unit is collapsed or hacked, users will suffer the risk of losing their Bitcoins. Motivated by this, in this paper, we propose a new online wallet architecture: HA-eWallet. In HA-eWallet, the transaction of Bitcoin is signed by multiple private keys rather than one, and private keys are stored separately in different places. In addition, we introduce a second service unit to construct the Active-Active architecture to rotate the capability and workload. Besides, we adopt a disaster recovery strategy in our proposed architecture in case of any disaster. According to the running states of each service unit, HA-eWallet have three operation models, and can be switched smoothly. Theoretical analyses and experiments show that: HA-eWallet can achieve higher availability compared with the traditional online wallet architecture, and users will not suffer a loss as long as the number of lost private keys are less than 50% of the users' total number of private keys.
{"title":"Trust your wallet: A new online wallet architecture for Bitcoin","authors":"Fangdong Zhu, Wen Chen, Yunpeng Wang, Ping Lin, Tao Li, Xiaochun Cao, Long Yuan","doi":"10.1109/PIC.2017.8359562","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359562","url":null,"abstract":"Online wallet has become an important method to manage Bitcoin. In a Bitcoin transaction, online wallet manages the private key automatically, and stores the encrypted private key in remote to ensure the accessibility of Bitcoin anywhere. In the traditional online wallet, the private key is stored centrally in a storage unit. However, if the storage unit is collapsed or hacked, users will suffer the risk of losing their Bitcoins. Motivated by this, in this paper, we propose a new online wallet architecture: HA-eWallet. In HA-eWallet, the transaction of Bitcoin is signed by multiple private keys rather than one, and private keys are stored separately in different places. In addition, we introduce a second service unit to construct the Active-Active architecture to rotate the capability and workload. Besides, we adopt a disaster recovery strategy in our proposed architecture in case of any disaster. According to the running states of each service unit, HA-eWallet have three operation models, and can be switched smoothly. Theoretical analyses and experiments show that: HA-eWallet can achieve higher availability compared with the traditional online wallet architecture, and users will not suffer a loss as long as the number of lost private keys are less than 50% of the users' total number of private keys.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115068709","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359552
Y. Liu, Hao-peng Chen, Fei Hu
For the sake of protecting users' privacy from the malicious data which is shared by other people and leasing the pressure of the clouds, an approach of verification based on the Blockchain is put forward in our article. By using the Blockchain to record the hash value and other necessary information of data sharing by other people, we can guarantee that the data user received from a third-party source (such as a cloud storage platform) is the original uploaded data indeed. After taking some experiments on the following method. We confirm that it can be easily distinguished whether a data has been modified by malicious people through our Blockchain-based approach. This Blockchain-based approach of verification can effectively help users find out if the data received is the one exactly he wants. In addition, our approach will imply that the data is not the original one and that data cannot be opened or executed.
{"title":"A blockchain-based verification for sharing data securely","authors":"Y. Liu, Hao-peng Chen, Fei Hu","doi":"10.1109/PIC.2017.8359552","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359552","url":null,"abstract":"For the sake of protecting users' privacy from the malicious data which is shared by other people and leasing the pressure of the clouds, an approach of verification based on the Blockchain is put forward in our article. By using the Blockchain to record the hash value and other necessary information of data sharing by other people, we can guarantee that the data user received from a third-party source (such as a cloud storage platform) is the original uploaded data indeed. After taking some experiments on the following method. We confirm that it can be easily distinguished whether a data has been modified by malicious people through our Blockchain-based approach. This Blockchain-based approach of verification can effectively help users find out if the data received is the one exactly he wants. In addition, our approach will imply that the data is not the original one and that data cannot be opened or executed.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127006488","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359567
T. Khanzada, A. Mukhtiar, N. Bushra, M. S. Talpur, A. Faisal
Network coding is a potential method that numerous investigators have move forwarded due to its significant advantages to enhance the proficiency of data communication. In this work, utilize simulations to assess the execution of various network topologies employing network coding. By contrasting the results of network and without network coding, it insists that network coding can improve the throughput, end-to-end delays, Packet Delivery Rate (PDR) and consistency. This paper presents the comparative performance analysis of network coding such as, XOR, LNC, and RLNC. The results demonstrates the XOR technique has attractive outcomes and can improve the real time performance metrics i.e.; throughput, end-to-end delay and PDR by substantial limitations. The analysis has been carried out based on packet size and also number of packets to be transmitted. Results illustrates that the network coding facilitate in dependence between networks.
{"title":"Evaluation and analysis of network coding at network layer","authors":"T. Khanzada, A. Mukhtiar, N. Bushra, M. S. Talpur, A. Faisal","doi":"10.1109/PIC.2017.8359567","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359567","url":null,"abstract":"Network coding is a potential method that numerous investigators have move forwarded due to its significant advantages to enhance the proficiency of data communication. In this work, utilize simulations to assess the execution of various network topologies employing network coding. By contrasting the results of network and without network coding, it insists that network coding can improve the throughput, end-to-end delays, Packet Delivery Rate (PDR) and consistency. This paper presents the comparative performance analysis of network coding such as, XOR, LNC, and RLNC. The results demonstrates the XOR technique has attractive outcomes and can improve the real time performance metrics i.e.; throughput, end-to-end delay and PDR by substantial limitations. The analysis has been carried out based on packet size and also number of packets to be transmitted. Results illustrates that the network coding facilitate in dependence between networks.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130571461","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359563
Tao Liu, Jian Cao, Yudong Tan, Quan-Wu Xiao
Since airlines usually keep their price strategies as commercial secrets and information is always asymmetric, it is difficult for ordinary customers to estimate future flight price changes. However, a reasonable prediction can help customers make decisions when to buy air tickets for a lower price. Flight price prediction can be regarded as a typical time series prediction problem. There are usually two main methods to solve this problem. One is using classical time series prediction methods such as ARIMA, etc. Another is extracting certain features and using regression models. For the latter, sometimes the flight price is context-aware, making it difficult to get an optimized single regression model for the whole price series. Meanwhile, effective context features vary on different air routes and change with time, therefore it is difficult to model context information. In this paper, we propose a context-aware ensemble regression model named ACER which combines different context-aware models and adjusts context features adaptively. Inspired by the idea of bagging and boosting, context features are randomly selected to cluster data efficiently and multiple regression models are trained for data with different contexts. In addition, the context feature list is dynamically adjusted by dropping some irrelevant features. In the experiment on the real data set, our model is compared with the baseline regression model, random forest and classical time series models. The results show that ACER performs much better than the other models.
{"title":"ACER: An adaptive context-aware ensemble regression model for airfare price prediction","authors":"Tao Liu, Jian Cao, Yudong Tan, Quan-Wu Xiao","doi":"10.1109/PIC.2017.8359563","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359563","url":null,"abstract":"Since airlines usually keep their price strategies as commercial secrets and information is always asymmetric, it is difficult for ordinary customers to estimate future flight price changes. However, a reasonable prediction can help customers make decisions when to buy air tickets for a lower price. Flight price prediction can be regarded as a typical time series prediction problem. There are usually two main methods to solve this problem. One is using classical time series prediction methods such as ARIMA, etc. Another is extracting certain features and using regression models. For the latter, sometimes the flight price is context-aware, making it difficult to get an optimized single regression model for the whole price series. Meanwhile, effective context features vary on different air routes and change with time, therefore it is difficult to model context information. In this paper, we propose a context-aware ensemble regression model named ACER which combines different context-aware models and adjusts context features adaptively. Inspired by the idea of bagging and boosting, context features are randomly selected to cluster data efficiently and multiple regression models are trained for data with different contexts. In addition, the context feature list is dynamically adjusted by dropping some irrelevant features. In the experiment on the real data set, our model is compared with the baseline regression model, random forest and classical time series models. The results show that ACER performs much better than the other models.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114627034","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359514
Haibo Shi, Yaoru Sun, Guangyuan Li
In this study, a hierarchical architecture for the intermittent control under the minimum transition hypothesis (MTH) was implemented. A two-stage hierarchy was adopted to perform the high-level and the low-level control respectively. The high-level controller performed the intermittent control by setting a sequence of goals for the low-level controller. Goal planning as the intermittent control policy was learned with hierarchical deep deterministic policy gradient (h-DDPG) proposed in this study, which is a hierarchical version of the conventional DDPG. The model successfully learned to temporally decompose a complex movement into a sequence of basic motor skills with sparse transitions, as shown in results of the two validation experiments: the trajectory following and the obstacle avoidance tasks.
{"title":"Intemittent control with reinforcement leaning","authors":"Haibo Shi, Yaoru Sun, Guangyuan Li","doi":"10.1109/PIC.2017.8359514","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359514","url":null,"abstract":"In this study, a hierarchical architecture for the intermittent control under the minimum transition hypothesis (MTH) was implemented. A two-stage hierarchy was adopted to perform the high-level and the low-level control respectively. The high-level controller performed the intermittent control by setting a sequence of goals for the low-level controller. Goal planning as the intermittent control policy was learned with hierarchical deep deterministic policy gradient (h-DDPG) proposed in this study, which is a hierarchical version of the conventional DDPG. The model successfully learned to temporally decompose a complex movement into a sequence of basic motor skills with sparse transitions, as shown in results of the two validation experiments: the trajectory following and the obstacle avoidance tasks.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124411853","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359523
Teng-Yu Ji, Tingzhu Huang, Xile Zhao, Dong-Lin Sun
How to define and relax the tensor rank is a challenging and meaningful topic. The CP-rank, n-rank, and tensor multirank are three of the most popular definitions. Among them n-rank and tensor multirank are widely studied in the low-rank tensor completion problem, and their relaxations are sum of nuclear norm (SNN) and tensor nuclear norm (TNN), respectively. Both the two kinds of nuclear norm treat the singular values equally, while the different singular values for the practical images represent different physical meanings and should be treated differently. In this paper, we propose a tensor logDet function as the relaxation for tensor multirank rather than TNN. To demonstrate the effectiveness of the proposed function, we introduce the function into the low-rank tensor completion problem and develop an alternating direction method of multipliers (ADMM)-based method. Extensive experiments have shown that the proposed method outperforms the SNN and TNN based methods.
{"title":"A new surrogate for tensor multirank and applications in image and video completion","authors":"Teng-Yu Ji, Tingzhu Huang, Xile Zhao, Dong-Lin Sun","doi":"10.1109/PIC.2017.8359523","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359523","url":null,"abstract":"How to define and relax the tensor rank is a challenging and meaningful topic. The CP-rank, n-rank, and tensor multirank are three of the most popular definitions. Among them n-rank and tensor multirank are widely studied in the low-rank tensor completion problem, and their relaxations are sum of nuclear norm (SNN) and tensor nuclear norm (TNN), respectively. Both the two kinds of nuclear norm treat the singular values equally, while the different singular values for the practical images represent different physical meanings and should be treated differently. In this paper, we propose a tensor logDet function as the relaxation for tensor multirank rather than TNN. To demonstrate the effectiveness of the proposed function, we introduce the function into the low-rank tensor completion problem and develop an alternating direction method of multipliers (ADMM)-based method. Extensive experiments have shown that the proposed method outperforms the SNN and TNN based methods.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131336940","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359528
Peipei Sun, Hongyi Liu
Hyperspectral image (HSI) is often contaminated by mixed noise in the acquisition process. In this paper, a hyperspectral image low-rank restoration method based spectral-spatial total variation (LRSSTV) is proposed. The spectral high correlation is exploited by low-rank representation and the sparse noise is represented by the /i-norm. Furthermore, to remove the Gaussian noise and enhance the edge information, spectral-spatial adaptive total variation prior knowledge is utilized. Both simulated and real-world data experimental results show that the proposed method can work well in detail preservation and noise removal.
{"title":"Hyperspectral image low-rank restoration based spectral-spatial total variation","authors":"Peipei Sun, Hongyi Liu","doi":"10.1109/PIC.2017.8359528","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359528","url":null,"abstract":"Hyperspectral image (HSI) is often contaminated by mixed noise in the acquisition process. In this paper, a hyperspectral image low-rank restoration method based spectral-spatial total variation (LRSSTV) is proposed. The spectral high correlation is exploited by low-rank representation and the sparse noise is represented by the /i-norm. Furthermore, to remove the Gaussian noise and enhance the edge information, spectral-spatial adaptive total variation prior knowledge is utilized. Both simulated and real-world data experimental results show that the proposed method can work well in detail preservation and noise removal.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133592956","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}
Cloud computing is a revolutionary information technology paradigm, which provides users with unlimited, scalale, low-cost and convenient resource services, but when data is outsourced to a semi-trusted cloud server, challenging security issues such as user privacy, access control, etc. still urgently need to be addressed. Attribute-based encryption (ABE) scheme can provide sufficient data security and fine-grained access control for cloud data. However, the limitation of ABE is that user's privacy would be disclosed with the access policy (structure) stored in clear text. Some works sacrificed the computing efficiency, key length or ciphertext size for privacy concerns. To overcome these problems, this paper proposes an efficient anonymous attributebased encryption scheme with access policy hidden. Using the idea of Boolean equivalent transformation, the proposed scheme can achieve fast encryption and protect the privacy for both data owner and legitimate access user. In addition, the proposed scheme can satisfy constant secret key length and reasonable size of ciphertext requirements. We conduct theoretical security analysis, and carry out experiments to prove that the proposed scheme has good performance in terms of computational, communication and storage overheads.
{"title":"Efficient anonymous attribute-based encryption with access policy hidden for cloud computing","authors":"Chanying Huang, Kedong Yan, Songjie Wei, Gongxuan Zhang, Dong Hoon Lee","doi":"10.1109/PIC.2017.8359555","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359555","url":null,"abstract":"Cloud computing is a revolutionary information technology paradigm, which provides users with unlimited, scalale, low-cost and convenient resource services, but when data is outsourced to a semi-trusted cloud server, challenging security issues such as user privacy, access control, etc. still urgently need to be addressed. Attribute-based encryption (ABE) scheme can provide sufficient data security and fine-grained access control for cloud data. However, the limitation of ABE is that user's privacy would be disclosed with the access policy (structure) stored in clear text. Some works sacrificed the computing efficiency, key length or ciphertext size for privacy concerns. To overcome these problems, this paper proposes an efficient anonymous attributebased encryption scheme with access policy hidden. Using the idea of Boolean equivalent transformation, the proposed scheme can achieve fast encryption and protect the privacy for both data owner and legitimate access user. In addition, the proposed scheme can satisfy constant secret key length and reasonable size of ciphertext requirements. We conduct theoretical security analysis, and carry out experiments to prove that the proposed scheme has good performance in terms of computational, communication and storage overheads.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115672710","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 : 2017-12-01DOI: 10.1109/PIC.2017.8359589
Lei Sun, Ning Pan, Liangsheng He, Zhiqiang Zhu
Role Based Access Control (RBAC) has become the de facto access control model in recent years. In order to deploy RBAC, organizations have to define a set of roles from the existing user-permission assignment relationships, the process of which is called role mining. There have been many role mining algorithms proposed to devise a complete and correct set of roles which may not be necessary because the user-permission assignment (UPA) relationships are dynamic. In this paper, we define the evaluation criterion and the 6-Approx Important Role Mining Problem (6-IRMP) which is proved to be NP-complete first, then we propose a heuristic bottom-up role mining approach that reduces the total number of roles with important assignments and permissions preserved. Furthermore, we carry out the experiments with public datasets to evaluate our approach and the experimental results compared with other algorithms demonstrate the effectiveness of our proposed approach.
{"title":"An importance-based approach for mining approximate roles","authors":"Lei Sun, Ning Pan, Liangsheng He, Zhiqiang Zhu","doi":"10.1109/PIC.2017.8359589","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359589","url":null,"abstract":"Role Based Access Control (RBAC) has become the de facto access control model in recent years. In order to deploy RBAC, organizations have to define a set of roles from the existing user-permission assignment relationships, the process of which is called role mining. There have been many role mining algorithms proposed to devise a complete and correct set of roles which may not be necessary because the user-permission assignment (UPA) relationships are dynamic. In this paper, we define the evaluation criterion and the 6-Approx Important Role Mining Problem (6-IRMP) which is proved to be NP-complete first, then we propose a heuristic bottom-up role mining approach that reduces the total number of roles with important assignments and permissions preserved. Furthermore, we carry out the experiments with public datasets to evaluate our approach and the experimental results compared with other algorithms demonstrate the effectiveness of our proposed approach.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124730182","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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