The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-inpu...The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.展开更多
After the digital revolution, the power system security becomes an important issue and it urges the power producers to maintain a well secured system in order to supply a quality power to the end users. This paper pre...After the digital revolution, the power system security becomes an important issue and it urges the power producers to maintain a well secured system in order to supply a quality power to the end users. This paper presents an integrated Corrective Security Constrained Optimal Power Flow (CSCOPF) with Flexible Transmission Line Impedance (FTLI) to enhance the power system security. The corrective approach of SCOPF is chosen, because it allows the corrective equipment to bring back the system to a stable operating point and hence, it offers high flexibility and better economics. The concept of FTLI arises from the ability of FACTS devices such as Thyristor Controlled Series Capacitor (TCSC), which can vary the line reactance to a certain extent. An enhanced security can be achieved by incorporating FTLI into the CSCOPF problem, since the power flow in a system is highly dependent on the line reactance. FTLI based CSCOPF can reduce the amount of rescheduling of generators, but it will result in an increased number of variables and thus, the complexity to the optimization process is increased. This highly complex problem is solved by using nonlinear programming. The AC based OPF model is preferred, since the corrective security actions require highly accurate solutions. IEEE 30 bus system is used to test the proposed scheme and the results are compared with the traditional CSCOPF. It can be seen that the proposed idea provides a notable improvement in the reduction of cost incurred for restoring the system security.展开更多
We devise a model for security investment that reflects dynamic interaction between a defender, who faces uncertainty, and an attacker, who repeatedly targets the weakest link. Using the model, we derive and compare o...We devise a model for security investment that reflects dynamic interaction between a defender, who faces uncertainty, and an attacker, who repeatedly targets the weakest link. Using the model, we derive and compare optimal security investment over multiple periods, exploring the delicate balance between proactive and reactive security investment. We show how the best strategy depends on the defender’s knowledge about prospective attacks and the recoverability of costs when upgrading defenses reactively. Our model explains why security under-investment is sometimes rational even when effective defenses are available and can be deployed independently of other parties’ choices. Finally, we connect the model to real-world security problems by examining two case studies where empirical data are available: computers compromised for use in online crime and payment card security.展开更多
The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential...The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of traffic.As IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT serves.In this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS attacks.The CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)methods.The proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in real-time.This involvesemploying the best-performing ML algorithmfor detection and the integration of warning mechanisms.We believe this approach will significantly enhance the field of security research and continue to refine it based on future insights and developments.展开更多
The ecological and environmental effects caused by land use change have attracted global attention.Huaihai Economic Zone, as the core of the Huaihe River ecological economic belt, has experienced a reciprocal evolutio...The ecological and environmental effects caused by land use change have attracted global attention.Huaihai Economic Zone, as the core of the Huaihe River ecological economic belt, has experienced a reciprocal evolution of land use, ecological security and regional economic development. Based on multi-stage land use data extracted by Google Earth Engine(GEE), the spatio-temporal differentiation characteristics of ecosystem service value(ESV) evolution in Huaihai Economic Zone from 1998 to 2018 were analyzed with the help of ESV assessment and a minimum accumulated resistance model(MCR), and the regional ecological security pattern(ESP) was optimized. The results show that ESV intensity has obvious spatial differentiation, which is higher in northeastern China and lower in southwestern China. The median ESV area accounted for the largest proportion, while the high and low ESV areas accounted for a small proportion. The characteristics of EVS temporal and spatial differentiation show decreasing and increasing grades. From the perspective of development period, the ESV grade changes show a positive trend. In the optimization of the ecological security pattern, 26 important ecological sources, 22main landscape ecological corridors, and 65 ecological strategic nodes were optimized and identified, and the middle-level ecological security zone accounted for the largest proportion. The main reasons for the changes in the ESV and ESP are closely related to the changes in local natural resources and the changes and adjustments in government protection policies. These research results can provide a reference for inter-provincial territorial space protection and the formulation of a sustainable development strategy.展开更多
With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secur...With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secure operation.Aiming at the SCC limitations,we use multiple back-toback voltage source converter based(B2B VSC)systems to separate a large-scale AC power grid into two asynchronous power grids.A multi-objective robust optimal secure operation model of large-scale power grid with multiple B2B VSC systems considering the SCC limitation is established based on the AC power flow equations.The decision variables include the on/off states of synchronous generators,power output,terminal voltage,transmission switching,bus sectionalization,and modulation ratios of B2B VSC systems.The influence of inner current sources of renewable energy generators on the system SCC is also considered.To improve the computational efficiency,a mixedinteger convex programming(MICP)framework based on convex relaxation methods including the inscribed N-sided approximation for the nonlinear SCC limitation constraints is proposed.Moreover,combined with the column-and-constraint generation(C&CG)algorithm,a method to directly solve the compromise optimal solution(COS)of the multi-objective robust optimal secure operation model is proposed.Finally,the effectiveness and computational efficiency of the proposed solution method is demonstrated by an actual 4407-bus provincial power grid and the modified IEEE 39-bus power grid,which can reduce the consumed CPU time of solving the COS by more than 90%and obtain a better COS.展开更多
Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and c...Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and complex.IEDS is the focus of regional energy internet research and development at home and abroad.Compared with the traditional power distribution system,IEDS through the multi-energy coupling link comprehensive utilization,effectively improve the distribution system economy,safety,reliability,flexibility and toughness,but also to ease the regional energy system environmental pressure.IEDS is an important direction for the future development of energy systems,and its related research and practice on China’s energy system development also has important practical and strategic significance.This paper summarizes the related researches of the IEDS and explores the energy operation characteristics and coupling mechanisms.What’s more,the integrated model of IEDS is summarized.On these bases,this paper discusses and prospects some key issues such as joint planning,optimization control and security analysis,state estimation and situational awareness and generalized demand side management.展开更多
文摘The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.
文摘After the digital revolution, the power system security becomes an important issue and it urges the power producers to maintain a well secured system in order to supply a quality power to the end users. This paper presents an integrated Corrective Security Constrained Optimal Power Flow (CSCOPF) with Flexible Transmission Line Impedance (FTLI) to enhance the power system security. The corrective approach of SCOPF is chosen, because it allows the corrective equipment to bring back the system to a stable operating point and hence, it offers high flexibility and better economics. The concept of FTLI arises from the ability of FACTS devices such as Thyristor Controlled Series Capacitor (TCSC), which can vary the line reactance to a certain extent. An enhanced security can be achieved by incorporating FTLI into the CSCOPF problem, since the power flow in a system is highly dependent on the line reactance. FTLI based CSCOPF can reduce the amount of rescheduling of generators, but it will result in an increased number of variables and thus, the complexity to the optimization process is increased. This highly complex problem is solved by using nonlinear programming. The AC based OPF model is preferred, since the corrective security actions require highly accurate solutions. IEEE 30 bus system is used to test the proposed scheme and the results are compared with the traditional CSCOPF. It can be seen that the proposed idea provides a notable improvement in the reduction of cost incurred for restoring the system security.
文摘We devise a model for security investment that reflects dynamic interaction between a defender, who faces uncertainty, and an attacker, who repeatedly targets the weakest link. Using the model, we derive and compare optimal security investment over multiple periods, exploring the delicate balance between proactive and reactive security investment. We show how the best strategy depends on the defender’s knowledge about prospective attacks and the recoverability of costs when upgrading defenses reactively. Our model explains why security under-investment is sometimes rational even when effective defenses are available and can be deployed independently of other parties’ choices. Finally, we connect the model to real-world security problems by examining two case studies where empirical data are available: computers compromised for use in online crime and payment card security.
文摘The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber threats.Among the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of traffic.As IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT serves.In this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS attacks.The CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)methods.The proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in real-time.This involvesemploying the best-performing ML algorithmfor detection and the integration of warning mechanisms.We believe this approach will significantly enhance the field of security research and continue to refine it based on future insights and developments.
基金The National Natural Science Foundation of China (41971175)。
文摘The ecological and environmental effects caused by land use change have attracted global attention.Huaihai Economic Zone, as the core of the Huaihe River ecological economic belt, has experienced a reciprocal evolution of land use, ecological security and regional economic development. Based on multi-stage land use data extracted by Google Earth Engine(GEE), the spatio-temporal differentiation characteristics of ecosystem service value(ESV) evolution in Huaihai Economic Zone from 1998 to 2018 were analyzed with the help of ESV assessment and a minimum accumulated resistance model(MCR), and the regional ecological security pattern(ESP) was optimized. The results show that ESV intensity has obvious spatial differentiation, which is higher in northeastern China and lower in southwestern China. The median ESV area accounted for the largest proportion, while the high and low ESV areas accounted for a small proportion. The characteristics of EVS temporal and spatial differentiation show decreasing and increasing grades. From the perspective of development period, the ESV grade changes show a positive trend. In the optimization of the ecological security pattern, 26 important ecological sources, 22main landscape ecological corridors, and 65 ecological strategic nodes were optimized and identified, and the middle-level ecological security zone accounted for the largest proportion. The main reasons for the changes in the ESV and ESP are closely related to the changes in local natural resources and the changes and adjustments in government protection policies. These research results can provide a reference for inter-provincial territorial space protection and the formulation of a sustainable development strategy.
基金supported by the National Natural Science Foundation of China(No.51977080).
文摘With the load growth and the power grid expansion,the problem of short-circuit current(SCC)exceeding the secure limit in large-scale power grids has become more serious,which poses great challenge to the optimal secure operation.Aiming at the SCC limitations,we use multiple back-toback voltage source converter based(B2B VSC)systems to separate a large-scale AC power grid into two asynchronous power grids.A multi-objective robust optimal secure operation model of large-scale power grid with multiple B2B VSC systems considering the SCC limitation is established based on the AC power flow equations.The decision variables include the on/off states of synchronous generators,power output,terminal voltage,transmission switching,bus sectionalization,and modulation ratios of B2B VSC systems.The influence of inner current sources of renewable energy generators on the system SCC is also considered.To improve the computational efficiency,a mixedinteger convex programming(MICP)framework based on convex relaxation methods including the inscribed N-sided approximation for the nonlinear SCC limitation constraints is proposed.Moreover,combined with the column-and-constraint generation(C&CG)algorithm,a method to directly solve the compromise optimal solution(COS)of the multi-objective robust optimal secure operation model is proposed.Finally,the effectiveness and computational efficiency of the proposed solution method is demonstrated by an actual 4407-bus provincial power grid and the modified IEEE 39-bus power grid,which can reduce the consumed CPU time of solving the COS by more than 90%and obtain a better COS.
基金This work was supported by the National High Technology Research and Development Program(863 Program)of China(2015AA050403)Natural Science Foundation of Tianjin(17JCQNJC06600)+2 种基金Independent Innovation Foundation of Tianjin University(Research on Key Technology of Distributed Demand Response)Ocean Engineering Equipment and Technical Think Tank Joint Project of Qingdao(201707071003)the Distributed Energy and Microgrid Project conducted in collaboration with APPLIED ENERGY UNiLAB-DEM.
文摘Integrated energy distribution system(IEDS)is one of the integrated energy and power system forms,which involves electricity/gas/cold/heat and other various energy forms.The energy coupling relationship is close and complex.IEDS is the focus of regional energy internet research and development at home and abroad.Compared with the traditional power distribution system,IEDS through the multi-energy coupling link comprehensive utilization,effectively improve the distribution system economy,safety,reliability,flexibility and toughness,but also to ease the regional energy system environmental pressure.IEDS is an important direction for the future development of energy systems,and its related research and practice on China’s energy system development also has important practical and strategic significance.This paper summarizes the related researches of the IEDS and explores the energy operation characteristics and coupling mechanisms.What’s more,the integrated model of IEDS is summarized.On these bases,this paper discusses and prospects some key issues such as joint planning,optimization control and security analysis,state estimation and situational awareness and generalized demand side management.
