128,163 research outputs found
Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems
The first-ever Ukraine cyberattack on power grid has proven its devastation
by hacking into their critical cyber assets. With administrative privileges
accessing substation networks/local control centers, one intelligent way of
coordinated cyberattacks is to execute a series of disruptive switching
executions on multiple substations using compromised supervisory control and
data acquisition (SCADA) systems. These actions can cause significant impacts
to an interconnected power grid. Unlike the previous power blackouts, such
high-impact initiating events can aggravate operating conditions, initiating
instability that may lead to system-wide cascading failure. A systemic
evaluation of "nightmare" scenarios is highly desirable for asset owners to
manage and prioritize the maintenance and investment in protecting their
cyberinfrastructure. This survey paper is a conceptual expansion of real-time
monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework
that emphasizes on the resulting impacts, both on steady-state and dynamic
aspects of power system stability. Hypothetically, we associate the
combinatorial analyses of steady state on substations/components outages and
dynamics of the sequential switching orders as part of the permutation. The
expanded framework includes (1) critical/noncritical combination verification,
(2) cascade confirmation, and (3) combination re-evaluation. This paper ends
with a discussion of the open issues for metrics and future design pertaining
the impact quantification of cyber-related contingencies
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
BioNessie - a grid enabled biochemical networks simulation environment
The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations
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'BioNessie(G) - a grid enabled biochemical networks simulation environment
The simulation of biochemical networks provides insight and
understanding about the underlying biochemical processes and pathways
used by cells and organisms. BioNessie is a biochemical network simulator
which has been developed at the University of Glasgow. This paper
describes the simulator and focuses in particular on how it has been
extended to benefit from a wide variety of high performance compute resources
across the UK through Grid technologies to support larger scale
simulations
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