ANALYSIS OF WORM INTERACTIONS

Motivated by War of the worms , we propose a worm
interaction approach that relies upon automated
beneficial worm generation to alleviate problems of
worm propagations in such networks. We also propose a
new set of metrics to quantify effectiveness of one
worm terminating other worm. To understand the
dynamics of worm interactions and their performance,
we mathematically model worm interactions based on
major worm interaction factors including worm
interaction types, network characteristics, and node
characteristics using ordinary differential equations
and analyze their effects on our proposed metrics.
Our study provides the first work to characterize and
investigate worm interactions of random-scan worms in
multi-hop networks.For encounter-based worm, we
validate our proposed model using extensive synthetic
and trace-driven simulations.We find that, all worm
interaction factors significantly affect the pattern
of worm propagations. For example, immunization
linearly decreases the infection of susceptible nodes
while on-off behavior only impacts the duration of
infection.

Autorentext

Sapon Tanachaiwiwat holds a B.S. in Electrical Engineering from
the Mahidol University,Bangkok; a M.S. in Electrical Engineering,
and a Ph.D. in Computer Engineering, both from the University of
Southern California. His main research interests are in
modeling,designing algorithms and protocols for large-scaled
simulation and real-time systems

Klappentext

Motivated by "War of the worms", we propose a worm
interaction approach that relies upon automated
beneficial worm generation to alleviate problems of
worm propagations in such networks. We also propose a
new set of metrics to quantify effectiveness of one
worm terminating other worm. To understand the
dynamics of worm interactions and their performance,
we mathematically model worm interactions based on
major worm interaction factors including worm
interaction types, network characteristics, and node
characteristics using ordinary differential equations
and analyze their effects on our proposed metrics.
Our study provides the first work to characterize and
investigate worm interactions of random-scan worms in
multi-hop networks.For encounter-based worm, we
validate our proposed model using extensive synthetic
and trace-driven simulations.We find that, all worm
interaction factors significantly affect the pattern
of worm propagations. For example, immunization
linearly decreases the infection of susceptible nodes
while on-off behavior only impacts the duration of
infection.