6 research outputs found
Distributed watermarking for secure control of microgrids under replay attacks
The problem of replay attacks in the communication network between
Distributed Generation Units (DGUs) of a DC microgrid is examined. The DGUs are
regulated through a hierarchical control architecture, and are networked to
achieve secondary control objectives. Following analysis of the detectability
of replay attacks by a distributed monitoring scheme previously proposed, the
need for a watermarking signal is identified. Hence, conditions are given on
the watermark in order to guarantee detection of replay attacks, and such a
signal is designed. Simulations are then presented to demonstrate the
effectiveness of the technique
Towards Distributed Accommodation of Covert Attacks in Interconnected Systems
The problem of mitigating maliciously injected signals in interconnected
systems is dealt with in this paper. We consider the class of covert attacks,
as they are stealthy and cannot be detected by conventional means in
centralized settings. Distributed architectures can be leveraged for revealing
such stealthy attacks by exploiting communication and local model knowledge. We
show how such detection schemes can be improved to estimate the action of an
attacker and we propose an accommodation scheme in order to mitigate or
neutralize abnormal behavior of a system under attack
Dynamic Quantized Consensus of General Linear Multi-agent Systems under Denial-of-Service Attacks
In this paper, we study multi-agent consensus problems under
Denial-of-Service (DoS) attacks with data rate constraints. We first consider
the leaderless consensus problem and after that we briefly present the analysis
of leader-follower consensus. The dynamics of the agents take general forms
modeled as homogeneous linear time-invariant systems. In our analysis, we
derive lower bounds on the data rate for the multi-agent systems to achieve
leaderless and leader-follower consensus in the presence of DoS attacks, under
which the issue of overflow of quantizer is prevented. The main contribution of
the paper is the characterization of the trade-off between the tolerable DoS
attack levels for leaderless and leader-follower consensus and the required
data rates for the quantizers during the communication attempts among the
agents. To mitigate the influence of DoS attacks, we employ dynamic
quantization with zooming-in and zooming-out capabilities for avoiding
quantizer saturation
Fault diagnosis for uncertain networked systems
Fault diagnosis has been at the forefront of technological developments for several decades. Recent advances in many engineering fields have led to the networked interconnection of various systems. The increased complexity of modern systems leads to a larger number of sources of uncertainty which must be taken into consideration and addressed properly in the design of monitoring and fault diagnosis architectures. This chapter reviews a model-based distributed fault diagnosis approach for uncertain nonlinear large-scale networked systems to specifically address: (a) the presence of measurement noise by devising a filtering scheme for dampening the effect of noise; (b) the modeling of uncertainty by developing an adaptive learning scheme; (c) the uncertainty issues emerging when considering networked systems such as the presence of delays and packet dropouts in the communication networks. The proposed architecture considers in an integrated way the various components of complex distributed systems such as the physical environment, the sensor level, the fault diagnosers, and the communication networks. Finally, some actions taken after the detection of a fault, such as the identification of the fault location and its magnitude or the learning of the fault function, are illustrated