Download e-book for iPad: Intentional Risk Management through Complex Networks by Victor Chapela, Regino Criado, Santiago Moral, Miguel

By Victor Chapela, Regino Criado, Santiago Moral, Miguel Romance

ISBN-10: 3319264214

ISBN-13: 9783319264219

ISBN-10: 3319264230

ISBN-13: 9783319264233

​​This e-book combines online game concept and intricate networks to ascertain intentional technological possibility via modeling. As details defense dangers are in consistent evolution, the methodologies and instruments to regulate them needs to evolve to an ever-changing setting. a proper international technique is defined during this publication, which can learn hazards in cyber defense in response to complicated community types and concepts extracted from the Nash equilibrium. A threat administration method for IT severe infrastructures is brought which gives assistance and research on selection making versions and genuine occasions. This version manages the chance of succumbing to a electronic assault and assesses an assault from the subsequent 3 variables: source of revenue acquired, price had to perform an assault, and the aptitude outcomes for an assault. Graduate scholars and researchers drawn to cyber defense, advanced community functions and intentional hazard will locate this booklet valuable because it is full of a few versions, methodologies and cutting edge examples. ​

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Extra info for Intentional Risk Management through Complex Networks Analysis

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The incidence matrix of G is a n×m matrix I(G) = (bij ) defined by the conditions bij = 1 if 0 if i∈ j i∈ / j. , if there exists an edge ij between the nodes i and j implicitly we have assumed the existence of the edge ji = ij . But this situation does not apply in the general case. This may be the situation if, for example, a link represents geographical proximity (if a node A is close to another node B, then B is also close to A). However, in many cases the connections between nodes are asymmetric since the edge runs only in one direction.

Hence if dj,k denotes the distance between j and k in the network then BE = 1 1 ∑ |E| j,k∈X njk = 1 1 ∑ |E| j,k∈X njk = 1 1 ∑ njk |E| j,k∈X ∑ njk ( ) ∈E ∑ ∑ ωg ( ) g∈Pjk ∈E ∑ g∈Pjk dj,k = n(n − 1) L(G) |E| and therefore BE (G) measures essentially the same global properties than the characteristic path length L(G). 10 Degree Distributions The degree distribution of a network G = (X, E) is a function P(k) which give us the probability of finding a node in G with degree k. In other words, P(k) is referred to the fraction of nodes having degree k.

The graph K3 is called a triangle. 2 Given a network G = (X, E) where X = {1, . . , n} and E = { 1 , . . , m }, it is n(n − 1) obvious that the number of edges of G is at most . The link density of G is 2 defined by the equation Δ= 2m . 3) Obviously, the link density of a network takes values within the interval [0, 1], where Δ 1 means the network is sparse, Δ 1 means the network is dense, and Δ = 1 means the network is the complete network of n nodes. A bipartite network is a network whose nodes can be divided into two disjoint sets U and V, X = U ∪ V such that every link connects a node in U to one in V.

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Intentional Risk Management through Complex Networks Analysis by Victor Chapela, Regino Criado, Santiago Moral, Miguel Romance


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