116 research outputs found
Local pinning of networks of multi-agent systems with transmission and pinning delays
We study the stability of networks of multi-agent systems with local pinning
strategies and two types of time delays, namely the transmission delay in the
network and the pinning delay of the controllers. Sufficient conditions for
stability are derived under specific scenarios by computing or estimating the
dominant eigenvalue of the characteristic equation. In addition, controlling
the network by pinning a single node is studied. Moreover, perturbation methods
are employed to derive conditions in the limit of small and large pinning
strengths.Numerical algorithms are proposed to verify stability, and simulation
examples are presented to confirm the efficiency of analytic results.Comment: 6 pages, 3 figure
Pinning Complex Networks by a Single Controller
In this paper, without assuming symmetry, irreducibility, or linearity of the
couplings, we prove that a single controller can pin a coupled complex network
to a homogenous solution. Sufficient conditions are presented to guarantee the
convergence of the pinning process locally and globally. An effective approach
to adapt the coupling strength is proposed. Several numerical simulations are
given to verify our theoretical analysis
A Stochastic Model of Active Cyber Defense Dynamics
The concept of active cyber defense has been proposed for years. However,
there are no mathematical models for characterizing the effectiveness of active
cyber defense. In this paper, we fill the void by proposing a novel Markov
process model that is native to the interaction between cyber attack and active
cyber defense. Unfortunately, the native Markov process model cannot be tackled
by the techniques we are aware of. We therefore simplify, via mean-field
approximation, the Markov process model as a Dynamic System model that is
amenable to analysis. This allows us to derive a set of valuable analytical
results that characterize the effectiveness of four types of active cyber
defense dynamics. Simulations show that the analytical results are inherent to
the native Markov process model, and therefore justify the validity of the
Dynamic System model. We also discuss the side-effect of the mean-field
approximation and its implications
Active Cyber Defense Dynamics Exhibiting Rich Phenomena
The Internet is a man-made complex system under constant attacks (e.g.,
Advanced Persistent Threats and malwares). It is therefore important to
understand the phenomena that can be induced by the interaction between cyber
attacks and cyber defenses. In this paper, we explore the rich phenomena that
can be exhibited when the defender employs active defense to combat cyber
attacks. To the best of our knowledge, this is the first study that shows that
{\em active cyber defense dynamics} (or more generally, {\em cybersecurity
dynamics}) can exhibit the bifurcation and chaos phenomena. This has profound
implications for cyber security measurement and prediction: (i) it is
infeasible (or even impossible) to accurately measure and predict cyber
security under certain circumstances; (ii) the defender must manipulate the
dynamics to avoid such {\em unmanageable situations} in real-life defense
operations.Comment: Proceedings of 2015 Symposium on the Science of Security (HotSoS'15
Characterizing the Power of Moving Target Defense via Cyber Epidemic Dynamics
Moving Target Defense (MTD) can enhance the resilience of cyber systems
against attacks. Although there have been many MTD techniques, there is no
systematic understanding and {\em quantitative} characterization of the power
of MTD. In this paper, we propose to use a cyber epidemic dynamics approach to
characterize the power of MTD. We define and investigate two complementary
measures that are applicable when the defender aims to deploy MTD to achieve a
certain security goal. One measure emphasizes the maximum portion of time
during which the system can afford to stay in an undesired configuration (or
posture), without considering the cost of deploying MTD. The other measure
emphasizes the minimum cost of deploying MTD, while accommodating that the
system has to stay in an undesired configuration (or posture) for a given
portion of time. Our analytic studies lead to algorithms for optimally
deploying MTD.Comment: 12 pages; 4 figures; Hotsos 14, 201
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