A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning....A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning. The new approach was proposed to decompose behavior into sub-behaviors that are easier to recognize using a saliency-based visual attention model. New representation of behavior was introduced, in which the sub-behavior and the associated time characteristic of sub-behavior were used to represent behavior case. In the process of case-based reasoning, apart from considering the similarity of basic sub-behaviors,order factor was proposed to measure the similarity of a time order among the sub-behaviors and span factor was used to measure the similarity of duration time of each sub-behavior, which makes the similarity calculations more rational and comprehensive.Experimental results show the effectiveness of the proposed method in comparison with other related works and can run in real-time for the recognition of suspicious behaviors.展开更多
In recent years,unmanned air vehicles(UAVs)are widely used in many military and civilian applications.With the big amount of UAVs operation in air space,the potential security and privacy problems are arising.This can...In recent years,unmanned air vehicles(UAVs)are widely used in many military and civilian applications.With the big amount of UAVs operation in air space,the potential security and privacy problems are arising.This can lead to consequent harm for critical infrastructure in the event of these UAVs being used for criminal or terrorist purposes.Therefore,it is crucial to promptly identify the suspicious behaviors from the surrounding UAVs for some important regions.In this paper,a novel fuzzy logic based UAV behavior detection system has been presented to detect the different levels of risky behaviors of the incoming UAVs.The heading velocity and region type are two input indicators proposed for the risk indicator output in the designed fuzzy logic based system.The simulation has shown the effective and feasible of the proposed algorithm in terms of recall and precision of the detection.Especially,the suspicious behavior detection algorithm can provide a recall of 0.89 and a precision of 0.95 for the high risk scenario in the simulation.展开更多
The rapid advancement in technology and the increased number of web applications with very short turnaround time caused an increased need for protection from vulnerabilities that grew due to decision makers overlookin...The rapid advancement in technology and the increased number of web applications with very short turnaround time caused an increased need for protection from vulnerabilities that grew due to decision makers overlooking the need to be protected from attackers or software developers lacking the skills and experience in writing secure code. Structured Query Language (SQL) Injection, cross-site scripting (XSS), Distributed Denial of service (DDos) and suspicious user behaviour are some of the common types of vulnerabilities in web applications by which the attacker can disclose the web application sensitive information such as credit card numbers and other confidential information. This paper proposes a framework for the detection and prevention of web threats (WTDPF) which is based on preventing the attacker from gaining access to confidential data by studying his behavior during the action of attack and taking preventive measures to reduce the risks of the attack and as well reduce the consequences of such malicious action. The framework consists of phases which begin with the input checking phase, signature based action component phase, alert and response phases. Additionally, the framework has a logging functionality to store and keep track of any action taking place and as well preserving information about the attacker IP address, date and time of the attack, type of the attack, and the mechanism the attacker used. Moreover, we provide experimental results for different kinds of attacks, and we illustrate the success of the proposed framework for dealing with and preventing malicious actions.展开更多
基金Project(50808025)supported by the National Natural Science Foundation of ChinaProject(2013GK3012)supported by the Science and Technology Project of Hunan Province,China
文摘A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning. The new approach was proposed to decompose behavior into sub-behaviors that are easier to recognize using a saliency-based visual attention model. New representation of behavior was introduced, in which the sub-behavior and the associated time characteristic of sub-behavior were used to represent behavior case. In the process of case-based reasoning, apart from considering the similarity of basic sub-behaviors,order factor was proposed to measure the similarity of a time order among the sub-behaviors and span factor was used to measure the similarity of duration time of each sub-behavior, which makes the similarity calculations more rational and comprehensive.Experimental results show the effectiveness of the proposed method in comparison with other related works and can run in real-time for the recognition of suspicious behaviors.
基金supported by the Fundamental Research Funds for the Central Universities(No.NJ20160015)
文摘In recent years,unmanned air vehicles(UAVs)are widely used in many military and civilian applications.With the big amount of UAVs operation in air space,the potential security and privacy problems are arising.This can lead to consequent harm for critical infrastructure in the event of these UAVs being used for criminal or terrorist purposes.Therefore,it is crucial to promptly identify the suspicious behaviors from the surrounding UAVs for some important regions.In this paper,a novel fuzzy logic based UAV behavior detection system has been presented to detect the different levels of risky behaviors of the incoming UAVs.The heading velocity and region type are two input indicators proposed for the risk indicator output in the designed fuzzy logic based system.The simulation has shown the effective and feasible of the proposed algorithm in terms of recall and precision of the detection.Especially,the suspicious behavior detection algorithm can provide a recall of 0.89 and a precision of 0.95 for the high risk scenario in the simulation.
文摘The rapid advancement in technology and the increased number of web applications with very short turnaround time caused an increased need for protection from vulnerabilities that grew due to decision makers overlooking the need to be protected from attackers or software developers lacking the skills and experience in writing secure code. Structured Query Language (SQL) Injection, cross-site scripting (XSS), Distributed Denial of service (DDos) and suspicious user behaviour are some of the common types of vulnerabilities in web applications by which the attacker can disclose the web application sensitive information such as credit card numbers and other confidential information. This paper proposes a framework for the detection and prevention of web threats (WTDPF) which is based on preventing the attacker from gaining access to confidential data by studying his behavior during the action of attack and taking preventive measures to reduce the risks of the attack and as well reduce the consequences of such malicious action. The framework consists of phases which begin with the input checking phase, signature based action component phase, alert and response phases. Additionally, the framework has a logging functionality to store and keep track of any action taking place and as well preserving information about the attacker IP address, date and time of the attack, type of the attack, and the mechanism the attacker used. Moreover, we provide experimental results for different kinds of attacks, and we illustrate the success of the proposed framework for dealing with and preventing malicious actions.
