Industrial control systems （ICSs） are widely used in critical infrastructures, making them popular targets for attacks to cause catastrophic physical damage. As one of the most critical components in ICSs, the progr...Industrial control systems （ICSs） are widely used in critical infrastructures, making them popular targets for attacks to cause catastrophic physical damage. As one of the most critical components in ICSs, the programmable logic controller （PLC） controls the actuators directly. A PLC executing a malicious program can cause significant property loss or even casualties. The number of attacks targeted at PLCs has increased noticeably over the last few years, exposing the vulnerability of the PLC and the importance of PLC protection. Unfortunately, PLCs cannot be protected by traditional intrusion detection systems or antivirus software. Thus, an effective method for PLC protection is yet to be designed. Motivated by these concerns, we propose a non-invasive power- based anomaly detection scheme for PLCs. The basic idea is to detect malicious software execution in a PLC through analyzing its power consumption, which is measured by inserting a shunt resistor in series with the CPU in a PLC while it is executing instructions. To analyze the power measurements, we extract a discriminative feature set from the power trace, and then train a long short-term memory （LSTM） neural network with the features of normal samples to predict the next time step of a normal sample. Finally, an abnormal sample is identified through comparing the predicted sample and the actual sample. The advantages of our method are that it requires no software modification on the original system and is able to detect unknown attacks effectively. The method is evaluated on a lab testbed, and for a trojan attack whose difference from the normal program is around 0.63%, the detection accuracy reaches 99.83%.展开更多
Different programming languages can be used for discrete, abstract and process-oriented programming. Depending on the application, there exist additional requirements, which are not fulfilled by every programming lang...Different programming languages can be used for discrete, abstract and process-oriented programming. Depending on the application, there exist additional requirements, which are not fulfilled by every programming language. Flexible programming and maintainability are especially important requirements for process engineers. In this paper, the programming languages Activity Diagram, State Chart Diagram and Sequential Function Chart are compared and evaluated with regard to these requirements. This evaluation is based on the principles of cognitive effectiveness and cognitive dimensions. The aim of this paper is to identify the programming language suited best for controlling sequential processes, e.g. thermomechanical or batch processes.展开更多
Cyberattacks on the Industrial Control System(ICS)have recently been increasing,made more intelligent by advancing technologies.As such,cybersecurity for such systems is attracting attention.As a core element of contr...Cyberattacks on the Industrial Control System(ICS)have recently been increasing,made more intelligent by advancing technologies.As such,cybersecurity for such systems is attracting attention.As a core element of control devices,the Programmable Logic Controller(PLC)in an ICS carries out on-site control over the ICS.A cyberattack on the PLC will cause damages on the overall ICS,with Stuxnet and Duqu as the most representative cases.Thus,cybersecurity for PLCs is considered essential,and many researchers carry out a variety of analyses on the vulnerabilities of PLCs as part of preemptive efforts against attacks.In this study,a vulnerability analysis was conducted on the XGB PLC.Security vulnerabilities were identified by analyzing the network protocols and memory structure of PLCs and were utilized to launch replay attack,memory modulation attack,and FTP/Web service account theft for the verification of the results.Based on the results,the attacks were proven to be able to cause the PLC to malfunction and disable it,and the identified vulnerabilities were defined.展开更多
基金Project supported by the National Basic Research Program(973)of China(No.2015AA050202)
文摘Industrial control systems （ICSs） are widely used in critical infrastructures, making them popular targets for attacks to cause catastrophic physical damage. As one of the most critical components in ICSs, the programmable logic controller （PLC） controls the actuators directly. A PLC executing a malicious program can cause significant property loss or even casualties. The number of attacks targeted at PLCs has increased noticeably over the last few years, exposing the vulnerability of the PLC and the importance of PLC protection. Unfortunately, PLCs cannot be protected by traditional intrusion detection systems or antivirus software. Thus, an effective method for PLC protection is yet to be designed. Motivated by these concerns, we propose a non-invasive power- based anomaly detection scheme for PLCs. The basic idea is to detect malicious software execution in a PLC through analyzing its power consumption, which is measured by inserting a shunt resistor in series with the CPU in a PLC while it is executing instructions. To analyze the power measurements, we extract a discriminative feature set from the power trace, and then train a long short-term memory （LSTM） neural network with the features of normal samples to predict the next time step of a normal sample. Finally, an abnormal sample is identified through comparing the predicted sample and the actual sample. The advantages of our method are that it requires no software modification on the original system and is able to detect unknown attacks effectively. The method is evaluated on a lab testbed, and for a trojan attack whose difference from the normal program is around 0.63%, the detection accuracy reaches 99.83%.
文摘Different programming languages can be used for discrete, abstract and process-oriented programming. Depending on the application, there exist additional requirements, which are not fulfilled by every programming language. Flexible programming and maintainability are especially important requirements for process engineers. In this paper, the programming languages Activity Diagram, State Chart Diagram and Sequential Function Chart are compared and evaluated with regard to these requirements. This evaluation is based on the principles of cognitive effectiveness and cognitive dimensions. The aim of this paper is to identify the programming language suited best for controlling sequential processes, e.g. thermomechanical or batch processes.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT:Ministry of Science and ICT)(Nos.NRF-2016M2A8A4952280 and NRF-2020R1A2C1012187).
文摘Cyberattacks on the Industrial Control System(ICS)have recently been increasing,made more intelligent by advancing technologies.As such,cybersecurity for such systems is attracting attention.As a core element of control devices,the Programmable Logic Controller(PLC)in an ICS carries out on-site control over the ICS.A cyberattack on the PLC will cause damages on the overall ICS,with Stuxnet and Duqu as the most representative cases.Thus,cybersecurity for PLCs is considered essential,and many researchers carry out a variety of analyses on the vulnerabilities of PLCs as part of preemptive efforts against attacks.In this study,a vulnerability analysis was conducted on the XGB PLC.Security vulnerabilities were identified by analyzing the network protocols and memory structure of PLCs and were utilized to launch replay attack,memory modulation attack,and FTP/Web service account theft for the verification of the results.Based on the results,the attacks were proven to be able to cause the PLC to malfunction and disable it,and the identified vulnerabilities were defined.
