  We investigate the use of autonomically created small-world graphs as a
framework for the long term storage of digital objects on the Web in a
potentially hostile environment. We attack the classic Erdos - Renyi random,
Barab'asi and Albert power law, Watts - Strogatz small world and our
Unsupervised Small-World (USW) graphs using different attacker strategies and
report their respective robustness. Using different attacker profiles, we
construct a game where the attacker is allowed to use a strategy of his choice
to remove a percentage of each graph's elements. The graph is then allowed to
repair some portion of its self. We report on the number of alternating attack
and repair turns until either the graph is disconnected, or the game exceeds
the number of permitted turns. Based on our analysis, an attack strategy that
focuses on removing the vertices with the highest betweenness value is most
advantageous to the attacker. Power law graphs can become disconnected with the
removal of a single edge; random graphs with the removal of as few as 1% of
their vertices, small-world graphs with the removal of 14% vertices, and USW
with the removal of 17% vertices. Watts - Strogatz small-world graphs are more
robust and resilient than random or power law graphs. USW graphs are more
robust and resilient than small world graphs. A graph of USW connected web
objects (WOs) filled with data could outlive the individuals and institutions
that created the data in an environment where WOs are lost due to random
failures or directed attacks.
