In this paper, we consider the optimal design of interlinks for an interdependent system networks. contrast to existing literature, explicitly exploit information intra-layer node degrees structures such that their robustness against cascading failures, triggered by randomized attacks, is maximized. Utilizing percolation theory-based equations relating network its degree sequence, characterize one-to-one structure, with complete interdependence and partial interdependence, under attack. We...

We consider the problem of interlink optimization in multilayer interdependent networks under cost constraints, with objective maximizing robustness network against component (node) failures. Diverting from popular approaches branching process based analysis failure cascades or using a supra-adjacency matrix representation and employing classical metrics, this work, we present surrogate metric framework for constructing interlinks to maximize robustness. In particular, focus on three...

We consider a partially interdependent network and develop mathematical equations relating the fractional size of connected component network, surviving cascading failure, to intra-layer degree distribution nodes. show that these system can be mathematically analyzed closed form expressions for metrics robustness obtained Erdos-Renyi (ER) model random graph generation. have described application our analysis technique networks with general distributions. In analysis, we two extremes attack...

In this work we consider the optimal design of interconnection links for an interdependent system networks. contrast to existing literature, explicitly exploit information intra- layer node degrees more robust interdependency structure against cascading failures triggered by random attacks. Built on solid mathematical models, characterize one-to-one structure, with complete interdependence and partial interdependence. We also extend study one-to-many targeted attack model. Simulation results...

Deployment of femtocells to facilitate mobile data offloading from macro/micro cell is considered in 4th Generation (4G) and beyond broadband wireless systems, specifically Long Term Evolution (LTE). Traffic offloaded the reduces spectrum usage cell. The macrocell bandwidth saved this way can be used add extra new users into system. co-channel deployment increases frequency reuse by several folds; thereby improving overall Area Spectral Efficiency (ASE). In work, capacity increase due...

In this work, we focus on the problem of obtaining optimal interlink structures, which maximizes robustness networks against random node failures, in a cost constrained setting. Using percolation theory based system equations, have formulated our objective as optimization and designed algorithms serving two key purposes: i) budget limits, B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sub> xmlns:xlink="http://www.w3.org/1999/xlink">u</sub>...

Mixup is a procedure for data augmentation that trains networks to make smoothly interpolated predictions between datapoints. Adversarial training strong form of optimizes worst-case in compact space around each data-point, resulting neural much more robust predictions. In this paper, we bring these ideas together by adversarially probing the datapoints, using projected gradient descent (PGD). The fundamental approach work leverage backpropagation through mixup interpolation during optimize...

In this work we consider the optimal design of interconnection links for an interdependent system networks. contrast to existing literature, explicitly exploit information intra- layer node degrees more robust interdependency structure against cascading failures triggered by random attacks. Built on solid mathematical models, characterize one-to-one structure, with complete interdependence and partial interdependence. We also extend study one-to-many targeted attack model. Simulation results...

We study the optimal design of interdependent networks against cascading failures with node protections. Different from existing literature which only considers interdependency link design, we also take protection strategy into account, where attacked nodes have a fixed probability surviving. The system designer is armed finite resources and wants to maximize number survival after initial attacks subsequent failures. Based on well-adopted analytical models for networks, propose near-optimal...

Machine Learning (ML) algorithms are susceptible to adversarial attacks and deception both during training deployment.Automatic reverse engineering of the toolchains behind these machine learning will aid in recovering tools processes used attacks.In this paper, we present two techniques that support automated identification attribution ML attack using Co-occurrence Pixel statistics Laplacian Residuals.Our experiments show proposed can identify parameters generate samples.To best our...

Recent research on epidemic spreading in networks has uncovered the phenomena of metastable infection patterns, where epidemics can be sustained localized regions activity, contrast to classical dichotomy between a quick extinction infections and network-wide global infection. Our objective this work is leverage state achieve <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">controlled</i> multilayer via intelligent design interlink structure...

Machine Learning (ML) algorithms are susceptible to adversarial attacks and deception both during training deployment. Automatic reverse engineering of the toolchains behind these machine learning will aid in recovering tools processes used attacks. In this paper, we present two techniques that support automated identification attribution ML attack using Co-occurrence Pixel statistics Laplacian Residuals. Our experiments show proposed can identify parameters generate samples. To best our...