Biblio
The algorithm of causal anomaly detection in industrial control physics is proposed to determine the normal cloud line of industrial control system so as to accurately detect the anomaly. In this paper, The causal modeling algorithm combining Maximum Information Coefficient and Transfer Entropy was used to construct the causal network among nodes in the system. Then, the abnormal nodes and the propagation path of the anomaly are deduced from the structural changes of the causal network before and after the attack. Finally, an anomaly detection algorithm based on hybrid differential cumulative is used to identify the specific anomaly data in the anomaly node. The stability of causality mining algorithm and the validity of locating causality anomalies are verified by using the data of classical chemical process. Experimental results show that the anomaly detection algorithm is better than the comparison algorithm in accuracy, false negative rate and recall rate, and the anomaly location strategy makes the anomaly source traceable.
Device-to-device communication is widely used for mobile devices and Internet of Things. Authentication and key agreement are critical to build a secure channel between two devices. However, existing approaches often rely on a pre-built fingerprint database and suffer from low key generation rate. We present GeneWave, a fast device authentication and key agreement protocol for commodity mobile devices. GeneWave first achieves bidirectional initial authentication based on the physical response interval between two devices. To keep the accuracy of interval estimation, we eliminate time uncertainty on commodity devices through fast signal detection and redundancy time cancellation. Then, we derive the initial acoustic channel response for device authentication. We design a novel coding scheme for efficient key agreement while ensuring security. Therefore, two devices can authenticate each other and securely agree on a symmetric key. GeneWave requires neither special hardware nor pre-built fingerprint database, and thus it is easyto-use on commercial mobile devices. We implement GeneWave on mobile devices (i.e., Nexus 5X and Nexus 6P) and evaluate its performance through extensive experiments. Experimental results show that GeneWave efficiently accomplish secure key agreement on commodity smartphones with a key generation rate 10× faster than the state-of-the-art approach.