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Jeremy Bryans, Lin Shen Liew, Hoang Nga Nguyen, Giedre Sabaliauskaite and Siraj Ahmed Shaikh
Systems that integrate cyber and physical aspects to create cyber-physical systems (CPS) are becoming increasingly complex, but demonstrating the security of CPS is hard and security is frequently compromised. These compromises can lead to safety failure...
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Yuxin Zhang, Shumian Yang, Lijuan Xu, Xin Li and Dawei Zhao
As the amount of malware has grown rapidly in recent years, it has become the most dominant attack method in network security. Learning execution behavior, especially Application Programming Interface (API) call sequences, has been shown to be effective ...
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Dapeng Lang, Deyun Chen, Sizhao Li and Yongjun He
The deep model is widely used and has been demonstrated to have more hidden security risks. An adversarial attack can bypass the traditional means of defense. By modifying the input data, the attack on the deep model is realized, and it is imperceptible ...
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Giuseppe Granato, Alessio Martino, Andrea Baiocchi and Antonello Rizzi
Network traffic analysis, and specifically anomaly and attack detection, call for sophisticated tools relying on a large number of features. Mathematical modeling is extremely difficult, given the ample variety of traffic patterns and the subtle and vari...
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Ammar Jamil Odeh,Ismail Keshta,Eman Abdelfattah
Pág. pp. 22 - 31
Phishing is a type of Internet fraud that aims to acquire the credential of users via scamming websites. In this paper, a novel approach is utilized that uses a Neural Network with a multilayer perceptron to detect the scam URL. The proposed system impro...
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Andrei Brazhuk
Pág. 38 - 41
This paper discusses the problem of extracting and using knowledge of public directories of software attacks and vulnerabilities to build semantic threat models. The possible purpose of such models is using as a core of a knowledge managem...
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