Optimal energy allocation for remote state estimate under Denial‐of‐Service attack

Abstract

This paper considers an energy‐constrained sensor power allocation problem for remote estimation under Denial‐of‐Service attack. Due to power constraints, the sensor needs to make a decision on how much power it should employ to optimise the state estimation performance under Denial‐of‐Servic attacks without using real‐time acknowledgment information. Different from the existing works concerning non‐zero power value with discrete values or one power value, the authors consider the multilevel continuous‐valued energy allocation policy containing zero power value in this work. By analysing the effects on performance index under different energy allocation policies, an optimal off‐line power scheduling policy with non‐decreasing structure is derived. To obtain the optimal power scheduling sequences, the authors formulate the problem as non‐linear programming after analysing the probability distribution of the estimation error covariance matrix. Moreover, the two power values energy allocation policy is investigated as a special case. At last, simulation examples are presented to verify the effectiveness of their theoretical results.

Interaction network‐based resilient consensus of connected vehicles against cyber‐attacks

“…For example, power transmission networks may be attacked and disrupted by controlling electrical facilities [14]. Typical cyber attacks include: denial of service (DoS) attacks [15][16][17], replay attacks [18,19], and deception attacks [20][21][22][23]. Network attacks are very dangerous and have become a critical threat to network control systems (NCSs) [24] and cyber physical systems (CPSs) [25].…”