Biblio

Protecting Cyber-physical Systems (CPSs) is highly important for preserving sensitive information and detecting cyber threats. Developing a robust privacy-preserving anomaly detection method requires physical and network data about the systems, such as Supervisory Control and Data Acquisition (SCADA), for protecting original data and recognising cyber-attacks. In this paper, a new privacy-preserving anomaly detection framework, so-called PPAD-CPS, is proposed for protecting confidential information and discovering malicious observations in power systems and their network traffic. The framework involves two main modules. First, a data pre-processing module is suggested for filtering and transforming original data into a new format that achieves the target of privacy preservation. Second, an anomaly detection module is suggested using a Gaussian Mixture Model (GMM) and Kalman Filter (KF) for precisely estimating the posterior probabilities of legitimate and anomalous events. The performance of the PPAD-CPS framework is assessed using two public datasets, namely the Power System and UNSW-NB15 dataset. The experimental results show that the framework is more effective than four recent techniques for obtaining high privacy levels. Moreover, the framework outperforms seven peer anomaly detection techniques in terms of detection rate, false positive rate, and computational time.

The market of wearable healthcare monitoring devices has exploded in recent years as healthcare consciousness has increased. These types of devices usually consist of several biosensors, which can be worn on human bodies, such as the head, arms, and feet. The health status of a user can be analyzed according to the user's real-time vital signs that are collected from different biosensors. Due to personal medical data being transmitted through a wireless network, the data have to be encrypted. In this paper, a key agreement protocol for biosensors within Wireless Body Sensor Networks (WBSN) has been proposed based on the n-Party Diffie-Hellman key exchange protocol. In order to prevent the man-in-the-middle attacks, we have used Advance Encryption Standard (AES) encryption with Electrocardiography-based (ECG-based) keys to secure the key exchange procedures. The security and performance analysis show the feasibility of the proposed method.