17,120 research outputs found
Self-Adaptive Role-Based Access Control for Business Processes
© 2017 IEEE. We present an approach for dynamically reconfiguring the role-based access control (RBAC) of information systems running business processes, to protect them against insider threats. The new approach uses business process execution traces and stochastic model checking to establish confidence intervals for key measurable attributes of user behaviour, and thus to identify and adaptively demote users who misuse their access permissions maliciously or accidentally. We implemented and evaluated the approach and its policy specification formalism for a real IT support business process, showing their ability to express and apply a broad range of self-adaptive RBAC policies
Meta-dynamical adaptive systems and their applications to a fractal algorithm and a biological model
In this article, one defines two models of adaptive systems: the
meta-dynamical adaptive system using the notion of Kalman dynamical systems and
the adaptive differential equations using the notion of variable dimension
spaces. This concept of variable dimension spaces relates the notion of spaces
to the notion of dimensions. First, a computational model of the Douady's
Rabbit fractal is obtained by using the meta-dynamical adaptive system concept.
Then, we focus on a defense-attack biological model described by our two
formalisms
Life-Space Foam: a Medium for Motivational and Cognitive Dynamics
General stochastic dynamics, developed in a framework of Feynman path
integrals, have been applied to Lewinian field--theoretic psychodynamics,
resulting in the development of a new concept of life--space foam (LSF) as a
natural medium for motivational and cognitive psychodynamics. According to LSF
formalisms, the classic Lewinian life space can be macroscopically represented
as a smooth manifold with steady force-fields and behavioral paths, while at
the microscopic level it is more realistically represented as a collection of
wildly fluctuating force-fields, (loco)motion paths and local geometries (and
topologies with holes). A set of least-action principles is used to model the
smoothness of global, macro-level LSF paths, fields and geometry. To model the
corresponding local, micro-level LSF structures, an adaptive path integral is
used, defining a multi-phase and multi-path (multi-field and multi-geometry)
transition process from intention to goal-driven action. Application examples
of this new approach include (but are not limited to) information processing,
motivational fatigue, learning, memory and decision-making.Comment: 25 pages, 2 figures, elsar
Optimization of Trading Physics Models of Markets
We describe an end-to-end real-time S&P futures trading system. Inner-shell
stochastic nonlinear dynamic models are developed, and Canonical Momenta
Indicators (CMI) are derived from a fitted Lagrangian used by outer-shell
trading models dependent on these indicators. Recursive and adaptive
optimization using Adaptive Simulated Annealing (ASA) is used for fitting
parameters shared across these shells of dynamic and trading models
An Adaptive, Kink-Based Approach to Path Integral Calculations
A kink-based expression for the canonical partition function is developed
using Feynman's path integral formulation of quantum mechanics and a discrete
basis set. The approach is exact for a complete set of states. The method is
tested on the 3x3 Hubbard model and overcomes the sign problem seen in
traditional path integral studies of fermion systems. Kinks correspond to
transitions between different N-electron states, much in the same manner as
occurs in configuration interaction calculations in standard ab initio methods.
The different N-electron states are updated, based on which states occur
frequently during a Monte Carlo simulation, giving better estimates of the true
eigenstates of the Hamiltonian.Comment: 24 pages, to be published in J. Chem. Phy
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