Order-preserving submatrix （OPSM） has become important in modelling biologically meaningful subspace cluster, capturing the general tendency of gene expressions across a subset of conditions. With the advance of mic...Order-preserving submatrix （OPSM） has become important in modelling biologically meaningful subspace cluster, capturing the general tendency of gene expressions across a subset of conditions. With the advance of microarray and analysis techniques, big volume of gene expression datasets and OPSM mining results are produced. OPSM query can efficiently retrieve relevant OPSMs from the huge amount of OPSM datasets. However, improving OPSM query relevancy remains a difficult task in real life exploratory data analysis processing. First, it is hard to capture subjective interestingness aspects, e.g., the analyst＇s expectation given her/his domain knowledge. Second, when these expectations can be declaratively specified, it is still challenging to use them during the computational process of OPSM queries. With the best of our knowledge, existing methods mainly fo- cus on batch OPSM mining, while few works involve OPSM query. To solve the above problems, the paper proposes two constrained OPSM query methods, which exploit userdefined constraints to search relevant results from two kinds of indices introduced. In this paper, extensive experiments are conducted on real datasets, and experiment results demonstrate that the multi-dimension index （cIndex） and enumerating sequence index （esIndex） based queries have better performance than brute force search.展开更多
This paper proposes three different chaotic encryption methods using 1-D chaotic map known as Logistic map named as Logistic, NLFSR and Modified NLFSR according to the name of chaotic map and non-linear function invol...This paper proposes three different chaotic encryption methods using 1-D chaotic map known as Logistic map named as Logistic, NLFSR and Modified NLFSR according to the name of chaotic map and non-linear function involved in the scheme. The designed schemes have been crypt analyzed for five different methods for testing its strength. Cryptanalysis has been performed for various texts using various keys selected from domain of key space. Logistic and NLFSR methods are found to resist known plaintext attack for available first two characters of plaintext. Plaintext sensitivity of both methods is within small range along with medium key sensitivity. Identifiability for keys of first two of the scheme has not been derived concluding that methods may prove to be weak against brute-force attack. In the last modified scheme avalanche effect found to be improved compared to the previous ones and method is found to resist brute-force attack as it derives the conclusion for identifiability.展开更多
This paper approaches the problem of restoring a faulted area in an electric power distribution system after locating and isolating the faulted block and reconfiguring the system. Through this paper we are going to ex...This paper approaches the problem of restoring a faulted area in an electric power distribution system after locating and isolating the faulted block and reconfiguring the system. Through this paper we are going to explain the power system restoration technique using brute-force attack method (BFAM) and binary particle swarm optimization (BPSO). This is a technique based on the possible combination in mathematical analysis which is explained in the introduction. After isolating the fault, main concentration will be towards the reconfiguration of the restored system using BPSO. Here due to fault in the system near-by agent will be affected and become useless and will go in the non-working mode. Now in order to restore these near-by loads we will give a new connection called NO (Normally Open. Using these switch system will be restored with power availability. After restoration using the BFAM, the BPSO will be used in order to provide the stable configuration. The output of the BFAM will be used as input for the BPSO and then we will reconfigure our system in order to provide the stable configuration. The effectiveness of the proposed BFAM and BPSO is demonstrated by simulating tests in a proposed distribution network and verified the results using the Matlab and C programming.展开更多
We propose an efficient quantum private comparison protocol firstly based on one direction quantum walks.With the help of one direction quantum walk,we develop a novel method that allows the semi-honest third party to...We propose an efficient quantum private comparison protocol firstly based on one direction quantum walks.With the help of one direction quantum walk,we develop a novel method that allows the semi-honest third party to set a flag to judge the comparing result,which improves the qubit efficiency and the maximum quantity of the participants’secret messages.Besides,our protocol can judge the size of the secret messages,not only equality.Furthermore,the quantum walks particle is disentangled in the initial state.It only requires a quantum walks operator to move,making our proposed protocol easy to implement and reducing the quantum resources.Through security analysis,we prove that our protocol can withstand well-known attacks and brute-force attacks.Analyses also reveal that our protocol is correct and practical.展开更多
The classical autoregressive(AR)model has been widely applied to predict future data usingmpast observations over five decades.As the classical AR model required m unknown parameters,this paper implements the AR model...The classical autoregressive(AR)model has been widely applied to predict future data usingmpast observations over five decades.As the classical AR model required m unknown parameters,this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR model.We derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force technique.The performance of them-delay AR model was tested by comparing with the classical AR model.The results,obtained from Monte Carlo simulation using the monthly mean minimum temperature in PerthWestern Australia from the Bureau of Meteorology,are no significant difference compared to those obtained from the classical AR model.This confirms that the m-delay AR model is an effective model for time series analysis.展开更多
The rapid advancement of IT technology has enabled the quick discovery,sharing and collection of quality information,but has also increased cyberattacks at a fast pace at the same time.There exists no means to block t...The rapid advancement of IT technology has enabled the quick discovery,sharing and collection of quality information,but has also increased cyberattacks at a fast pace at the same time.There exists no means to block these cyberattacks completely,and all security policies need to consider the possibility of external attacks.Therefore,it is crucial to reduce external attacks through preventative measures.In general,since routers located in the upper part of a firewall can hardly be protected by security systems,they are exposed to numerous unblocked cyberattacks.Routers block unnecessary services and accept necessary ones while taking appropriate measures to reduce vulnerability,block unauthorized access,and generate relevant logs.Most logs created through unauthorized access are caused by SSH brute-force attacks,and therefore IP data of the attack can be collected through the logs.This paper proposes a model to detect SSH brute-force attacks through their logs,collect their IP address,and control access from that IP address.In this paper,we present a model that extracts and fragments the specific data required from the packets of collected routers in order to detect indiscriminate SSH input attacks.To do so,the model multiplies a user’s access records in each packet by weights and adds them to the blacklist according to a final calculated result value.In addition,the model can specify the internal IP of an attack attempt and defend against the first 29 destination IP addresses attempting the attack.展开更多
The diversity of Linux versions brings challenges to Linux memory analysis,which is an established technique in security and forensic investigations.During memory forensics,kernel data structures are essential informa...The diversity of Linux versions brings challenges to Linux memory analysis,which is an established technique in security and forensic investigations.During memory forensics,kernel data structures are essential information.Existing solutions obtain this information by analyzing debugging information or by decompiling kernel functions to handle a certain range of versions.In this paper,by collecting and analyzing a number of Linux versions,we characterize the properties of different Linux kernel versions and how struct offsets change between versions.Furthermore,the Linux kernel provides over 10,000 configurable features,which leads to different kernel structure layouts for the same kernel version.To deal with this problem,we propose a method of identifying kernel struct layout based on brute-force matching.By examining the relationships between kernel structures,common features are extracted and exploited for brute-force matching.The experimental results show that the proposed technology can deduce structure member offsets accurately and efficiently.展开更多
暴力破解攻击是入侵网络造成数据泄露的主要手段之一.随着互联网越发普及,其危害程度越来越大.校园网是整个互联网中相对开放的区域,学生、教职员工的信息更是被黑客虎视眈眈.与此同时,校园网内部业务系统错综复杂,导致学生、教职员工...暴力破解攻击是入侵网络造成数据泄露的主要手段之一.随着互联网越发普及,其危害程度越来越大.校园网是整个互联网中相对开放的区域,学生、教职员工的信息更是被黑客虎视眈眈.与此同时,校园网内部业务系统错综复杂,导致学生、教职员工的账号密码难以管理,为黑客进行暴力破解攻击留下了巨大的操作空间.本研究提出一种在大数据下,基于全流量采集的超文本传输协议(hypertext transfer protocol,HTTP)元数据的针对web暴力破解攻击的检测算法.实验表明,通过旁路采集网络全流量得到网络协议元数据,进一步清理后发送到大数据平台存储及分析,该方法能实时掌控整个校园网内的安全状态.展开更多
基金The authors thank the anonymous referees for their useful comments that greatly improved the quality of the paper. This work was supported in part by the National Basic Research Program 973 of China （2012CB316203）, the Natural Science Foundation of China （Grant Nos. 61033007, 61272121, 61332014, 61572367, 61332006, 61472321, and 61502390）, the National High Technology Research and Development Program 863 of China （2015AA015307）, the Fundational Research Funds for the Central Universities （3102015JSJ0011, 3102014JSJ0005, and 3102014JSJ0013）, and the Graduate Starting Seed Fund of Northwestern Polytechnical University （Z2012128）.
文摘Order-preserving submatrix （OPSM） has become important in modelling biologically meaningful subspace cluster, capturing the general tendency of gene expressions across a subset of conditions. With the advance of microarray and analysis techniques, big volume of gene expression datasets and OPSM mining results are produced. OPSM query can efficiently retrieve relevant OPSMs from the huge amount of OPSM datasets. However, improving OPSM query relevancy remains a difficult task in real life exploratory data analysis processing. First, it is hard to capture subjective interestingness aspects, e.g., the analyst＇s expectation given her/his domain knowledge. Second, when these expectations can be declaratively specified, it is still challenging to use them during the computational process of OPSM queries. With the best of our knowledge, existing methods mainly fo- cus on batch OPSM mining, while few works involve OPSM query. To solve the above problems, the paper proposes two constrained OPSM query methods, which exploit userdefined constraints to search relevant results from two kinds of indices introduced. In this paper, extensive experiments are conducted on real datasets, and experiment results demonstrate that the multi-dimension index （cIndex） and enumerating sequence index （esIndex） based queries have better performance than brute force search.
文摘This paper proposes three different chaotic encryption methods using 1-D chaotic map known as Logistic map named as Logistic, NLFSR and Modified NLFSR according to the name of chaotic map and non-linear function involved in the scheme. The designed schemes have been crypt analyzed for five different methods for testing its strength. Cryptanalysis has been performed for various texts using various keys selected from domain of key space. Logistic and NLFSR methods are found to resist known plaintext attack for available first two characters of plaintext. Plaintext sensitivity of both methods is within small range along with medium key sensitivity. Identifiability for keys of first two of the scheme has not been derived concluding that methods may prove to be weak against brute-force attack. In the last modified scheme avalanche effect found to be improved compared to the previous ones and method is found to resist brute-force attack as it derives the conclusion for identifiability.
文摘This paper approaches the problem of restoring a faulted area in an electric power distribution system after locating and isolating the faulted block and reconfiguring the system. Through this paper we are going to explain the power system restoration technique using brute-force attack method (BFAM) and binary particle swarm optimization (BPSO). This is a technique based on the possible combination in mathematical analysis which is explained in the introduction. After isolating the fault, main concentration will be towards the reconfiguration of the restored system using BPSO. Here due to fault in the system near-by agent will be affected and become useless and will go in the non-working mode. Now in order to restore these near-by loads we will give a new connection called NO (Normally Open. Using these switch system will be restored with power availability. After restoration using the BFAM, the BPSO will be used in order to provide the stable configuration. The output of the BFAM will be used as input for the BPSO and then we will reconfigure our system in order to provide the stable configuration. The effectiveness of the proposed BFAM and BPSO is demonstrated by simulating tests in a proposed distribution network and verified the results using the Matlab and C programming.
基金Project supported by the National Key R&D Program of China(Grant No.2020YFB1805405)the 111 Project(Grant No.B21049)+1 种基金the Foundation of Guizhou Provincial Key Laboratory of Public Big Data(Grant No.2019BDKFJJ014)the Fundamental Research Funds for the Central Universities,China(Grant No.2020RC38)。
文摘We propose an efficient quantum private comparison protocol firstly based on one direction quantum walks.With the help of one direction quantum walk,we develop a novel method that allows the semi-honest third party to set a flag to judge the comparing result,which improves the qubit efficiency and the maximum quantity of the participants’secret messages.Besides,our protocol can judge the size of the secret messages,not only equality.Furthermore,the quantum walks particle is disentangled in the initial state.It only requires a quantum walks operator to move,making our proposed protocol easy to implement and reducing the quantum resources.Through security analysis,we prove that our protocol can withstand well-known attacks and brute-force attacks.Analyses also reveal that our protocol is correct and practical.
文摘The classical autoregressive(AR)model has been widely applied to predict future data usingmpast observations over five decades.As the classical AR model required m unknown parameters,this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR model.We derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force technique.The performance of them-delay AR model was tested by comparing with the classical AR model.The results,obtained from Monte Carlo simulation using the monthly mean minimum temperature in PerthWestern Australia from the Bureau of Meteorology,are no significant difference compared to those obtained from the classical AR model.This confirms that the m-delay AR model is an effective model for time series analysis.
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2019S1A5C2A04083374).
文摘The rapid advancement of IT technology has enabled the quick discovery,sharing and collection of quality information,but has also increased cyberattacks at a fast pace at the same time.There exists no means to block these cyberattacks completely,and all security policies need to consider the possibility of external attacks.Therefore,it is crucial to reduce external attacks through preventative measures.In general,since routers located in the upper part of a firewall can hardly be protected by security systems,they are exposed to numerous unblocked cyberattacks.Routers block unnecessary services and accept necessary ones while taking appropriate measures to reduce vulnerability,block unauthorized access,and generate relevant logs.Most logs created through unauthorized access are caused by SSH brute-force attacks,and therefore IP data of the attack can be collected through the logs.This paper proposes a model to detect SSH brute-force attacks through their logs,collect their IP address,and control access from that IP address.In this paper,we present a model that extracts and fragments the specific data required from the packets of collected routers in order to detect indiscriminate SSH input attacks.To do so,the model multiplies a user’s access records in each packet by weights and adds them to the blacklist according to a final calculated result value.In addition,the model can specify the internal IP of an attack attempt and defend against the first 29 destination IP addresses attempting the attack.
文摘The diversity of Linux versions brings challenges to Linux memory analysis,which is an established technique in security and forensic investigations.During memory forensics,kernel data structures are essential information.Existing solutions obtain this information by analyzing debugging information or by decompiling kernel functions to handle a certain range of versions.In this paper,by collecting and analyzing a number of Linux versions,we characterize the properties of different Linux kernel versions and how struct offsets change between versions.Furthermore,the Linux kernel provides over 10,000 configurable features,which leads to different kernel structure layouts for the same kernel version.To deal with this problem,we propose a method of identifying kernel struct layout based on brute-force matching.By examining the relationships between kernel structures,common features are extracted and exploited for brute-force matching.The experimental results show that the proposed technology can deduce structure member offsets accurately and efficiently.
文摘暴力破解攻击是入侵网络造成数据泄露的主要手段之一.随着互联网越发普及,其危害程度越来越大.校园网是整个互联网中相对开放的区域,学生、教职员工的信息更是被黑客虎视眈眈.与此同时,校园网内部业务系统错综复杂,导致学生、教职员工的账号密码难以管理,为黑客进行暴力破解攻击留下了巨大的操作空间.本研究提出一种在大数据下,基于全流量采集的超文本传输协议(hypertext transfer protocol,HTTP)元数据的针对web暴力破解攻击的检测算法.实验表明,通过旁路采集网络全流量得到网络协议元数据,进一步清理后发送到大数据平台存储及分析,该方法能实时掌控整个校园网内的安全状态.
