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Optimal serverless networks
attacks, complexity and
some approximate
algorithms
Carlos Aguirre Maeso
Escuela Politécnica Superior
Universidad Autónoma de Madrid
Network attacks● An attack is a set of objects of a network
(nodes and/or edges) that are disabled removed (from the graph).
● The goal of a given attack is to produce the maximum possible damage in terms of connectivity.
Network attacks● The connectivity (resistance) of the graph after
the attack can be measured in different ways.• Number of nodes that are disconnected from a given
source node (server networks) (Aura et al.)
• Size of the biggest connected component (Albert-
Barabasi).
● The efficiency (damage) of an attack algorithm
for a given graph is the inverse of the resistance
of the graph to the attack
Model of communication network
●
V={v1⋯v∣V∣}is the set of nodes
E={e1⋯e∣E∣}:V×V {0,1}is the set of edges
c :V∪E Z∢∪{∞}is a cost function
s : V [ 0,1 ] is a significance function
We model a communication network as a cuadruple
CN={V,E,c,s}:
Network attacks● The cost function indicates how much costs
to a possible enemy to disable the element
● The relevance function indicates the
importance of the element, and therefore
how bad is that other nodes of the network
become disconnected with this node
Network attacks● The cost of a given attack is the sum of the
costs of the elements that are removed
from the graph.
● The relevance of a set of nodes is the sum
of the relevances of the nodes in the set.
Network attacks● For a given graph, we define the core of the
graph as the connected component with the
highest importance.
● We define the damage produced over a
communication network as the sum of the
significances of the elements that do not belong
to the core after the attack.
● The resistence of the network to the attack is
defined as the size of the core.
Optimal network attacks● Now, the problem op the optimal attack can
be stablished in the following terms:● Problem OPT_ATTACK: Given a serverless
communication network CN and two fixed
values C and D, does there exist an attack A
such as C(A) <= C and $D(A) >= D ?
Optimal network attacks● We look for attacks that produce the
maximal damage with the minimum cost.
● The problem of finding such attack is NP-
Complete (Aguirre et al.) even in the easier
case of bidirectional links, unbreakable
edges (nodes), identical cost for all nodes
(edges) and indentical importance for all
the nodes.
NP-Completness● NP-Complete problems are problems that
verify two conditions● It is very hard to find a solution.
● But If we are presented a possible solution it is
easy to check if this solution meets the
conditions of the problem.
● This conditions makes this problems very
suitable for approximate algorithms.
NP● In the OPT_ATTACK problem is very easy to check
is a possible solution meets the conditions of the
problem● We count the cost of the attack O(|E|)
● We find the connected components after the attack O(|E|+|
V|log|V|)
● We find the biggest connected component O(|V|)
● The damage now can be computed in O(|V|)
● To check if a possible solution meets the condition of
the problem takes a time O(|E|+|V|log|V|).
Completness● To show the completness of the problem, we stablish
a polynomical reduction of this problem to other
known complete problem.
● For the OPT_ATTACK problem we stablish a
polynomical reduction with the problem of the
bisection of a graph.
● As the bisection problem is complete, our problem is
also complete.
CompletnessLemma: The original graph G has a bisection of size B <= |V|2/4
if and only if the serverles communication network G' has an
attack A with D(A)>= 1/2(|V|3/4+|V|)+|V|/2 and
C(A) <= 1/2(|V|3/4+|V|)+B.
Sketch of the proof:
For the only if part take as attack the edges of the bisection plus
the edges of the paths from the extra node to one of the sides of
G.
For the if part show that is such attacks exists the numbers of
nodes that are discconected from the extra node s cant not be
higher that |V|/2 or lower than |V|/2.
CompletnessThe same theorem can be stablished for attacks where only
edges can be attacked. For a graph G consider the following
graph G'
where only the white nodes can be attacked and apply the
previous theorem.
Approximate Algorithms for Attacks
● Random Walks, Brownian methods.
● Minimal Cuts (Shamir)
● Random Failure (Albert-Barabasi)
● Maximal node degree (Albert-Barabasi)
● Minimal All-Paths (Newman).
● Minimal Single Path (Aguirre et al.)
Random Attack (Failure)
Failure
j= 1
while j < n
node=aleat(V)
V = V - node
j++
End Failure
Failure has a computational complexity O(n)
Degree Based Attack
AttackDegree
j= 1
while j < n
node=MostConected(V)
V = V - node
j++
End Attack
● AttackDegree has a computational complexity O(n2)
MinPath Based AttackAttackMinPath
j= 1
while j < n
For each u in V
ind[u]=0
For each u,v in V
C = minimal path from u to v
for each node k in C
ind[k]++
node= k such as the value ind[k] is maximum
V = V - node
j++
End AttackMinPath
MinPath has a computational complexity O(n3), this order can be reduced by selecting only a subset of the set of pairs of nodes in the graph
Graph topologies
● A given attack algorithm has different efficiencies in
different kinds of graphs.
● This means that before selecting an attack algorithm is
usually a good idea to know what kind of graph is going
to be attacked and select the best attack algorithm for
that graph.
● The graphs are classified using their intrinsic metrics
Metrics
● Esparsity (E/V)
● Node degree distribution
● Average degree (<k>)
● Cluster Coefficient (C)
● Characteristic Path (L)
● Number of biconnected components (B)
1830.7518.77HIERARCHIC
NETW. 4280.05615.808POWER GRID
60.0043.89RANDOM
10.01863.409SCALE-FREE
10.1573.744MIXED
10.62614.2SMALL-WORLD
10.643125.438RING-LATTICE
BCL
Network models
● Random Networks
● Regular Networks (Rings, grids)
● Small-World
● Scale Free
● Hierarchical networks
● Real Networks