Sample Generation for Security Region Boundary Identification Based on Topological Features of Historical Operation Data

Since the scale and uncertainty of the power system have been rapidly increasing,the computation efficiency of constructing the security region boundary(SRB)has become a prominent problem.Based on the topological features of historical operation data,a sample generation method for SRB identification is proposed to generate evenly distributed samples,which cover dominant security modes.The boundary sample pair(BSP)composed of a secure sample and an unsecure sample is defined to describe the feature of SRB.The resolution,sampling,and span indices are designed to evaluate the coverage degree of existing BSPs on the SRB and generate samples closer to the SRB.Based on the feature of flat distribution of BSPs over the SRB,the principal component analysis(PCA)is adopted to calculate the tangent vectors and normal vectors of SRB.Then,the sample distribution can be expanded along the tangent vector and corrected along the normal vector to cover different security modes.Finally,a sample set is randomly gen-erated based on the IEEE standard example and another new sample set is generated by the proposed method.The results indicate that the new sample set is closer to the SRB and covers different security modes with a small calculation time cost.

A Novel Provable Data Possession Scheme Based on Geographic Location Attribute

Increment of mobile cloud video motivates mobile users to utilize cloud storage service to address their demands, cloud storage provider always furnish a location-independent platform for managing user＇s data. However, mobile users wonder if their cloud video data leakage or dynamic migration to illegal service providers. In this paper, we design a novel provable data possession protocol based on data geographic location attribute, which allows data owner to auditing the integrity of their video data, which put forward an ideal choice for remote data possession checking in the mobile cloud storage. In our proposed scheme, we check out whether the video data dynamic migrate to an unspecified location （such as： overseas） by adding data geographic location attribute tag into provable data possession protocol. Moreover, we make sure the security of our proposed scheme under the Computational Diffic-Hellman assumption. The analysis and experiment results demonstrate that our proposed scheme is provably secure and efficient.

Orbiting Optimization Model for Tracking Voltage Security Region Boundary in Bulk Power Grids

A voltage security region(VSR)is a powerful tool for monitoring the voltage security in bulk power grids with high penetration of renewables.It can prevent cascading failures in wind power integration areas caused by serious over or low voltage problems.The bottlenecks of a VSR for practical applications are computational efficiency and accuracy.To bridge these gaps,a general optimization model for tracking a voltage security region boundary(VSRB)in bulk power grids is developed in this paper in accordance with the topological characteristics of the VSRB.First,the initial VSRB point on the VSRB is examined with the traditional OPF by using the base case parameters as initial values.Then,the rest of the VSRB points on the VSRB are tracked one after another,with the proposed optimization model,by using the parameters of the tracked VSRB point as the initial value to explore its adjacent VSRB point.The proposed approach can significantly improve the computational efficiency of the VSRB tracking over the existing algorithms,and case studies,in the WECC 9-bus and the Polish 2736-bus test systems,demonstrate the high accuracy and efficiency of the proposed approach on exploring the VSRB.

Fast Multi-Pattern Matching Algorithm on Compressed Network Traffic

Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.

Research on active defense decision-making method for cloud boundary networks based on reinforcement learning of intelligent agent

The cloud boundary network environment is characterized by a passive defense strategy,discrete defense actions,and delayed defense feedback in the face of network attacks,ignoring the influence of the external environment on defense decisions,thus resulting in poor defense effectiveness.Therefore,this paper proposes a cloud boundary network active defense model and decision method based on the reinforcement learning of intelligent agent,designs the network structure of the intelligent agent attack and defense game,and depicts the attack and defense game process of cloud boundary network;constructs the observation space and action space of reinforcement learning of intelligent agent in the non-complete information environment,and portrays the interaction process between intelligent agent and environment;establishes the reward mechanism based on the attack and defense gain,and encourage intelligent agents to learn more effective defense strategies.the designed active defense decision intelligent agent based on deep reinforcement learning can solve the problems of border dynamics,interaction lag,and control dispersion in the defense decision process of cloud boundary networks,and improve the autonomy and continuity of defense decisions.