Pub Date : 1900-01-01DOI: 10.32604/jqc.2020.010819
Xinda Hao, Jianming Zhou, Xueqi Shen, Yu Yang
: In recent years, machine learning technology has been widely used for timely network attack detection and classification. However, due to the large number of network traffic and the complex and variable nature of malicious attacks, many challenges have arisen in the field of network intrusion detection. Aiming at the problem that massive and high-dimensional data in cloud computing networks will have a negative impact on anomaly detection, this paper proposes a Bi-LSTM method based on attention mechanism, which learns by transmitting IDS data to multiple hidden layers. Abstract information and high-dimensional feature representation in network data messages are used to improve the accuracy of intrusion detection. In the experiment, we use the public data set KDD-Cup 99 for verification. The experimental results show that the model can effectively detect unpredictable malicious behaviors under the current network environment, improve detection accuracy and reduce false positive rate compared with traditional intrusion detection methods.
{"title":"A Novel Intrusion Detection Algorithm Based on Long Short Term Memory Network","authors":"Xinda Hao, Jianming Zhou, Xueqi Shen, Yu Yang","doi":"10.32604/jqc.2020.010819","DOIUrl":"https://doi.org/10.32604/jqc.2020.010819","url":null,"abstract":": In recent years, machine learning technology has been widely used for timely network attack detection and classification. However, due to the large number of network traffic and the complex and variable nature of malicious attacks, many challenges have arisen in the field of network intrusion detection. Aiming at the problem that massive and high-dimensional data in cloud computing networks will have a negative impact on anomaly detection, this paper proposes a Bi-LSTM method based on attention mechanism, which learns by transmitting IDS data to multiple hidden layers. Abstract information and high-dimensional feature representation in network data messages are used to improve the accuracy of intrusion detection. In the experiment, we use the public data set KDD-Cup 99 for verification. The experimental results show that the model can effectively detect unpredictable malicious behaviors under the current network environment, improve detection accuracy and reduce false positive rate compared with traditional intrusion detection methods.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122981647","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 improve the anti-noise performance of quantum teleportation, this paper proposes a novel dynamic quantum anti-noise scheme based on the quantum teleportation which transmits single qubit state using Bell state. Considering that quantum noise only acts on the transmitted qubit, i.e., the entangled state that Alice and Bob share in advance is affected by the noise, thus affecting the final transmission result. In this paper, a method for dynamically adjusting the shared entangled state according to the noise environment is proposed. By calculating the maximum fidelity of the output state to determine the shared entangled state, which makes the quantum teleportation be affected by the noise as little as possible. This paper calculates the fidelity of teleportation under four kinds of channel noise (amplitude damping, phase damping, bit flip and depolarizing noise). The results show that the scheme has a suppression effect on phase damping, bit flip and depolarizing noise under certain conditions. When the noise intensity is larger, the optimized efficiency is better.
{"title":"A Novel Method to against Quantum Noises in Quantum Teleportation","authors":"Shengyao Wu, Wenjie Liu, Zhiguo Qu","doi":"10.32604/jqc.2019.08898","DOIUrl":"https://doi.org/10.32604/jqc.2019.08898","url":null,"abstract":"In order to improve the anti-noise performance of quantum teleportation, this paper proposes a novel dynamic quantum anti-noise scheme based on the quantum teleportation which transmits single qubit state using Bell state. Considering that quantum noise only acts on the transmitted qubit, i.e., the entangled state that Alice and Bob share in advance is affected by the noise, thus affecting the final transmission result. In this paper, a method for dynamically adjusting the shared entangled state according to the noise environment is proposed. By calculating the maximum fidelity of the output state to determine the shared entangled state, which makes the quantum teleportation be affected by the noise as little as possible. This paper calculates the fidelity of teleportation under four kinds of channel noise (amplitude damping, phase damping, bit flip and depolarizing noise). The results show that the scheme has a suppression effect on phase damping, bit flip and depolarizing noise under certain conditions. When the noise intensity is larger, the optimized efficiency is better.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129833090","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 : 1900-01-01DOI: 10.32604/jqc.2022.038358
Jintao Fu, Yong Zhou, Qian Qiu, Guangwei Xu, Neng Wan
{"title":"A Model Average Algorithm for Housing Price Forecast with Evaluation Interpretation","authors":"Jintao Fu, Yong Zhou, Qian Qiu, Guangwei Xu, Neng Wan","doi":"10.32604/jqc.2022.038358","DOIUrl":"https://doi.org/10.32604/jqc.2022.038358","url":null,"abstract":"","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130355169","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, with the maturity and popularity of Wi-Fi technology, wireless hotspots have been deployed on a large scale in public places. But at the same time, it brings many security issues that cannot be ignored. Among them, the fake access point attack is a very serious threat in wireless local area network. In this paper, we propose a method to detect fake access points in wireless local area network. First, our detection method is passive, which means there is almost no additional traffic will be generated during the program’s operation. Second, different from many existing methods, our method allows the detection device to change position, the move will be perceived and the fingerprint will be updated automatically. Third, we use a variety of features as fingerprints to describe an access point better and improve efficiency. At last, the method we propose is more in line with the actual scene and has been proved effective by experiments.
{"title":"A Position Self-Adaptive Method to Detect Fake Access Points","authors":"Ping Lu","doi":"10.32604/jqc.2020.09433","DOIUrl":"https://doi.org/10.32604/jqc.2020.09433","url":null,"abstract":": In recent years, with the maturity and popularity of Wi-Fi technology, wireless hotspots have been deployed on a large scale in public places. But at the same time, it brings many security issues that cannot be ignored. Among them, the fake access point attack is a very serious threat in wireless local area network. In this paper, we propose a method to detect fake access points in wireless local area network. First, our detection method is passive, which means there is almost no additional traffic will be generated during the program’s operation. Second, different from many existing methods, our method allows the detection device to change position, the move will be perceived and the fingerprint will be updated automatically. Third, we use a variety of features as fingerprints to describe an access point better and improve efficiency. At last, the method we propose is more in line with the actual scene and has been proved effective by experiments.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131030438","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 solve the problem of data island in the safety management of offshore oil and gas fields, take full advantage of data for subsequent analysis and development, and support production safety management of oil and gas fields, the MES, which is maturely applied in manufacturing and downstream production of CNOOC (China National Offshore Oil Corporation), is introduced by the petroleum administration at the eastern South China sea. The system adopts the real-time database and relational database to collect the scattered structured data, such as evidence information of offshore oil and gas production facilities personnel, on-site hidden danger information and incident investigation report. Then a unified secure data center platform is established for every operating area and production site, and the critical safety data of production sites can be centrally managed. This system has the functions of lawful real-time supervision of personnel qualification, online supervision and trend analysis of hidden dangers, and centralized management and sharing of incident investigation report. By applying the MES system in security management, the process of safety service becomes standardized and modularized, the management process becomes normalized, and the efficiency and effect of overall management is improved.
{"title":"T Application of MES System in the Safety Management of Offshore Oil and Gas Fields","authors":"Yongle Chen, Lei Cui, Chong Wang","doi":"10.32604/JQC.2019.06283","DOIUrl":"https://doi.org/10.32604/JQC.2019.06283","url":null,"abstract":"In order to solve the problem of data island in the safety management of offshore oil and gas fields, take full advantage of data for subsequent analysis and development, and support production safety management of oil and gas fields, the MES, which is maturely applied in manufacturing and downstream production of CNOOC (China National Offshore Oil Corporation), is introduced by the petroleum administration at the eastern South China sea. The system adopts the real-time database and relational database to collect the scattered structured data, such as evidence information of offshore oil and gas production facilities personnel, on-site hidden danger information and incident investigation report. Then a unified secure data center platform is established for every operating area and production site, and the critical safety data of production sites can be centrally managed. This system has the functions of lawful real-time supervision of personnel qualification, online supervision and trend analysis of hidden dangers, and centralized management and sharing of incident investigation report. By applying the MES system in security management, the process of safety service becomes standardized and modularized, the management process becomes normalized, and the efficiency and effect of overall management is improved.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117110869","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}
: Language detection models based on system calls suffer from certain false negatives and detection blind spots. Hence, the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window. To detect such behaviors, we extract a multidimensional time distribution feature matrix on the basis of statistical analysis. This matrix mainly includes multidimensional time distribution features, multidimensional word pair correlation features, and multidimensional word frequency distribution features. A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window. Experimental evaluation is conducted using the ADFA-LD dataset. Accuracy, precision, and recall are used as the measurement indicators of the model. An accuracy rate of 95.26% and a recall rate of 96.11% are achieved.
{"title":"Malware Detection Based on Multidimensional Time Distribution Features","authors":"Huizhong Sun, Guosheng Xu, Hewei Yu, Minyan Ma, Yanhui Guo, Ruijie Quan","doi":"10.32604/jqc.2021.017365","DOIUrl":"https://doi.org/10.32604/jqc.2021.017365","url":null,"abstract":": Language detection models based on system calls suffer from certain false negatives and detection blind spots. Hence, the normal behavior sequences of some malware applications for a short period can become malicious behavior within a certain time window. To detect such behaviors, we extract a multidimensional time distribution feature matrix on the basis of statistical analysis. This matrix mainly includes multidimensional time distribution features, multidimensional word pair correlation features, and multidimensional word frequency distribution features. A multidimensional time distribution model based on neural networks is built to detect the overall abnormal behavior within a given time window. Experimental evaluation is conducted using the ADFA-LD dataset. Accuracy, precision, and recall are used as the measurement indicators of the model. An accuracy rate of 95.26% and a recall rate of 96.11% are achieved.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129772322","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}
Yuehan Du, Ruoyu Zhang, Xu Zhang, Antai Ouyang, Xiaodong Zhang, Jinyong Cheng, Lu Wenpeng
The algorithm based on combination learning usually is superior to a single classification algorithm on the task of protein secondary structure prediction. However, the assignment of the weight of the base classifier usually lacks decision-making evidence. In this paper, we propose a protein secondary structure prediction method with dynamic self-adaptation combination strategy based on entropy, where the weights are assigned according to the entropy of posterior probabilities outputted by base classifiers. The higher entropy value means a lower weight for the base classifier. The final structure prediction is decided by the weighted combination of posterior probabilities. Extensive experiments on CB513 dataset demonstrates that the proposed method outperforms the existing methods, which can effectively improve the prediction performance.
{"title":"Protein Secondary Structure Prediction with Dynamic Self-Adaptation Combination Strategy Based on Entropy","authors":"Yuehan Du, Ruoyu Zhang, Xu Zhang, Antai Ouyang, Xiaodong Zhang, Jinyong Cheng, Lu Wenpeng","doi":"10.32604/JQC.2019.06063","DOIUrl":"https://doi.org/10.32604/JQC.2019.06063","url":null,"abstract":"The algorithm based on combination learning usually is superior to a single classification algorithm on the task of protein secondary structure prediction. However, the assignment of the weight of the base classifier usually lacks decision-making evidence. In this paper, we propose a protein secondary structure prediction method with dynamic self-adaptation combination strategy based on entropy, where the weights are assigned according to the entropy of posterior probabilities outputted by base classifiers. The higher entropy value means a lower weight for the base classifier. The final structure prediction is decided by the weighted combination of posterior probabilities. Extensive experiments on CB513 dataset demonstrates that the proposed method outperforms the existing methods, which can effectively improve the prediction performance.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128796923","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 spatial analysis, two problems of the scale effect and the spatial dependence have been plagued scholars, the first law of geography presented to solve the spatial dependence has played a good role in the guidelines, forming the Geographical Weighted Regression (GWR). Based on classic statistical techniques, GWR model has ascertain significance in solving spatial dependence and spatial non-uniform problems, but it has no impact on the integration of the scale effect. It does not consider the interaction between the various factors of the sampling scale observations and the numerous factors of possible scale effects, so there is a loss of information. Crossing a two-stage analysis of “return of regression” to establish the model of Hierarchical Geographically Weighted Regression (HGWR), the first layer of regression analysis reflects the spatial dependence of space samples and the second layer of the regression reflects the spatial relationships scaling. The combination of both solves the spatial scale effect analysis, spatial dependence and spatial heterogeneity of the combined effects.
{"title":"Hierarchical Geographically Weighted Regression Model","authors":"Fengchang Xue","doi":"10.32604/JQC.2019.05954","DOIUrl":"https://doi.org/10.32604/JQC.2019.05954","url":null,"abstract":"In spatial analysis, two problems of the scale effect and the spatial dependence have been plagued scholars, the first law of geography presented to solve the spatial dependence has played a good role in the guidelines, forming the Geographical Weighted Regression (GWR). Based on classic statistical techniques, GWR model has ascertain significance in solving spatial dependence and spatial non-uniform problems, but it has no impact on the integration of the scale effect. It does not consider the interaction between the various factors of the sampling scale observations and the numerous factors of possible scale effects, so there is a loss of information. Crossing a two-stage analysis of “return of regression” to establish the model of Hierarchical Geographically Weighted Regression (HGWR), the first layer of regression analysis reflects the spatial dependence of space samples and the second layer of the regression reflects the spatial relationships scaling. The combination of both solves the spatial scale effect analysis, spatial dependence and spatial heterogeneity of the combined effects.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123108460","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}
Chen Hailin, Gang Xu, Yuling Chen, Chen Xiubo, Yixian Yang, Fan Ruibin, Zhang Kaixiang, Huizhong Li
: Most existing blockchain schemes are based on the design concept “openness and transparency” to realize data security, which usually require transaction data to be presented in the form of plaintext. However, it inevitably brings the issues with respect to data privacy and operating performance. In this paper, we proposed a novel blockchain scheme called Cipherchain, which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed. Specifically in our scheme, transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search (mPECK), and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger. By introducing execution-consensus-update paradigm of transaction flow, Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext, but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work. In addition, Cipherchain is a promising scheme to realize the technology combination of “blockchain+cloud computing” and “permissioned blockchain+public blockchain”.
{"title":"Cipherchain: A Secure and Efficient Ciphertext Blockchain via mPECK","authors":"Chen Hailin, Gang Xu, Yuling Chen, Chen Xiubo, Yixian Yang, Fan Ruibin, Zhang Kaixiang, Huizhong Li","doi":"10.32604/jqc.2020.09291","DOIUrl":"https://doi.org/10.32604/jqc.2020.09291","url":null,"abstract":": Most existing blockchain schemes are based on the design concept “openness and transparency” to realize data security, which usually require transaction data to be presented in the form of plaintext. However, it inevitably brings the issues with respect to data privacy and operating performance. In this paper, we proposed a novel blockchain scheme called Cipherchain, which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed. Specifically in our scheme, transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search (mPECK), and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger. By introducing execution-consensus-update paradigm of transaction flow, Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext, but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work. In addition, Cipherchain is a promising scheme to realize the technology combination of “blockchain+cloud computing” and “permissioned blockchain+public blockchain”.","PeriodicalId":284655,"journal":{"name":"Journal of Quantum Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125268479","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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