Probability-Guaranteed Distributed Secure Estimation for Nonlinear Systems Over Sensor Networks Under Deception Attacks on Innovations

Abstract

This paper studies the distributed secure state estimation problem for a class of general nonlinear systems over sensor networks under unknown deception attacks on innovations. At each sensing node, an estimator is designed to generate the state estimate by making use of the local measurements in combination with the neighbours' information shared via the communication network. During the transmission of innovations among nodes, the data are maliciously falsified by adversaries in a random way. A neural-network-based mechanism is put forward to approximate the unknown falsified innovations with the aim to mitigate the effects on the estimation performance. The objective of the addressed problem is to develop a distributed estimation approach to jointly estimate the system states as well as the unknow deception attacks, ensuring that the state estimation errors at each sensing node reside within required ellipsoidal regions with a pre-specified probability. With the help of certain convex optimization methods, we obtain sufficient conditions for the solvability of the addressed problem and the desired estimator gains can be iteratively computed by solving a series of matrix inequalities. On basis of the proposed framework, some optimization problems are presented to determine sub-optimal estimator parameters from different perspectives. Finally, the applicability of the developed algorithms is validated via a numerical simulation example.

Deception Attacks against Android-Based Smart Bracelets

“…Since the main function of the fake app is to obtain sensitive/health data and control the smart bracelet without authentication, the corresponding functional module should weaken the authentication process so that we can get the sensitive/health information and control the smart bracelet more directly. Hence, compared with the ofcial app, the functions and interfaces of the fake app are simpler [10,[24][25][26]. Te following are the concrete steps of the development process, and critical procedures together with the related code are shown in Figure 5:…”

“…For the distributed security state estimation under unknown spoofng attacks [10], a neural network-based mechanism is put forward to approximate the unknown falsifed innovations with the aim to mitigate the efects on the estimation performance [11]. Te Internet of Tings (IoT) is a paradigm that connects objects to the Internet as a whole and enables them to work together to achieve common objectives, such as innovative home automation.…”

Encryption–decryption‐based event‐triggered consensus control for nonlinear MASs under DoS attacks

“…On another research front, along with the extensive application of networked systems, the issue of network security has recently started to gain attention from many communities. 31,32 Up to now, most of the research on network security problems has mainly focused on cyberattacks, such as replay attack, 33,34 deception attack, 35,36 bias injection attacks 37 and denial-of-service (DoS) attack. [38][39][40] In particular, the DoS attack has captured a special interest because of its simple operation and destructive consequences, see, for example, References 41-43.…”

Distributed robust cooperative tracking against multiple maneuvering targets based on random finite set

“…The distributed estimation for maneuvering target based on mobile sensor network has been proposed for many years, such as [11][12][13][14]. Distributed Kalman filter algorithm for state estimation of linear dynamic target model is proposed by Olfati-Saber et al [15].…”