8 research outputs found
Poisoning Attacks Against Data-Driven Predictive Control
Data-driven predictive control (DPC) is a feedback control method for systems
with unknown dynamics. It repeatedly optimizes a system's future trajectories
based on past input-output data. We develop a numerical method that computes
poisoning attacks which inject additive perturbations to the output data to
change the trajectories optimized by DPC. This method is based on implicitly
differentiating the solution map of the trajectory optimization in DPC. We
demonstrate that the resulting attacks can cause an output tracking error one
order of magnitude higher than random perturbations in numerical experiments
Attack-Resilient Supervisory Control of Discrete-Event Systems
In this work, we study the problem of supervisory control of discrete-event
systems (DES) in the presence of attacks that tamper with inputs and outputs of
the plant. We consider a very general system setup as we focus on both
deterministic and nondeterministic plants that we model as finite state
transducers (FSTs); this also covers the conventional approach to modeling DES
as deterministic finite automata. Furthermore, we cover a wide class of attacks
that can nondeterministically add, remove, or rewrite a sensing and/or
actuation word to any word from predefined regular languages, and show how such
attacks can be modeled by nondeterministic FSTs; we also present how the use of
FSTs facilitates modeling realistic (and very complex) attacks, as well as
provides the foundation for design of attack-resilient supervisory controllers.
Specifically, we first consider the supervisory control problem for
deterministic plants with attacks (i) only on their sensors, (ii) only on their
actuators, and (iii) both on their sensors and actuators. For each case, we
develop new conditions for controllability in the presence of attacks, as well
as synthesizing algorithms to obtain FST-based description of such
attack-resilient supervisors. A derived resilient controller provides a set of
all safe control words that can keep the plant work desirably even in the
presence of corrupted observation and/or if the control words are subjected to
actuation attacks. Then, we extend the controllability theorems and the
supervisor synthesizing algorithms to nondeterministic plants that satisfy a
nonblocking condition. Finally, we illustrate applicability of our methodology
on several examples and numerical case-studies
On the Control of Microgrids Against Cyber-Attacks: A Review of Methods and Applications
Nowadays, the use of renewable generations, energy storage systems (ESSs) and microgrids (MGs) has been developed due to better controllability of distributed energy resources (DERs) as well as their cost-effective and emission-aware operation. The development of MGs as well as the use of hierarchical control has led to data transmission in the communication platform. As a result, the expansion of communication infrastructure has made MGs as cyber-physical systems (CPSs) vulnerable to cyber-attacks (CAs). Accordingly, prevention, detection and isolation of CAs during proper control of MGs is essential. In this paper, a comprehensive review on the control strategies of microgrids against CAs and its defense mechanisms has been done. The general structure of the paper is as follows: firstly, MGs operational conditions, i.e., the secure or insecure mode of the physical and cyber layers are investigated and the appropriate control to return to a safer mode are presented. Then, the common MGs communication system is described which is generally used for multi-agent systems (MASs). Also, classification of CAs in MGs has been reviewed. Afterwards, a comprehensive survey of available researches in the field of prevention, detection and isolation of CA and MG control against CA are summarized. Finally, future trends in this context are clarified
Computer Aided Verification
This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency
Computer Aided Verification
This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency