20,957 research outputs found

    A High-confidence Cyber-Physical Alarm System: Design and Implementation

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    Most traditional alarm systems cannot address security threats in a satisfactory manner. To alleviate this problem, we developed a high-confidence cyber-physical alarm system (CPAS), a new kind of alarm systems. This system establishes the connection of the Internet (i.e. TCP/IP) through GPRS/CDMA/3G. It achieves mutual communication control among terminal equipments, human machine interfaces and users by using the existing mobile communication network. The CPAS will enable the transformation in alarm mode from traditional one-way alarm to two-way alarm. The system has been successfully applied in practice. The results show that the CPAS could avoid false alarms and satisfy residents' security needs.Comment: IEEE/ACM Internet of Things Symposium (IOTS), in conjunction with GreenCom 2010, IEEE, Hangzhou, China, December 18-20, 201

    SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach

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    This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank's control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naive Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environmentsComment: E-Preprin
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