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Papers on Network Analysis
- Archipelago: A Network Security Analysis Tool
Proceedings of the Seventeenth Systems Administration Conference
(LISA XVII) (USENIX Association: Berkeley, CA), page 149-158, 2003
Archipelago is system analysis and visualization tool which implements
several methods of automated resource and security analysis for
human-computer networks; this includes physical networks, social
networks, knowledge networks and networks of clues in a forensic
analysis. Access control, intrusions and social engineering can be
discussed in the framework of graphical and information theoretical
relationships. Groups of users and shared objects, such as files or
conversations, provide communications channels for the spread of both
authorized and un-authorized information. We present a Java based
analysis tool that evaluates numerical criteria for the security of
such systems and implements algorithms for finding the vulnerable
points.
- A graph theoretical model of computer security: from file access to social engineering
International Journal of Information Security, 3, p.70-85 (2004)
We describe a model of computer security that applies results
from the statistical properties of graphs to human-computer systems.
The model attempts to determine a safe threshold of interconnectivity
in a human-computer system by ad hoc network analyses. The results
can be applied to physical networks, social networks and to networks
of clues in a forensic analysis. Access control, intrusions and
social engineering can also be discussed as graphical and information
theoretical relationships. Groups of users and shared objects, such as
files or conversations, provide communications channels for the spread
of both authorized and un-authorized information. We present
numerical criteria for measuring the security of such systems and
algorithms for finding the vulnerable points.
- Mining Topological Importance From The Eigenvectors Of Directed Graphs
Submitted Data Mining and Knowledge Discovery
We study methods for extracting importance scores for nodes on a
directed graph, using only the topology of the graph as a guide. Such
ranking has many applications in directed networks. Our strategy is
to find an eigenvector, which is positive everywhere on the graph and
can be in interpreted as a global importance function for its
topological content, avoiding significant modification of the graph
topology. We review some alternative adjacency operators and show
that, for a general reducible graph, there is no globally obtainable
importance function without graph augmentation. Two new methods of
augmenting graphs are then proposed to allow such a global ranking to
be computed. Preliminary tests are shown to perform favourably
alongside other well-known approaches that do make large
modifications. Our work has applications to all fields where directed
graphs are used. We discuss briefly some example applications, in
particular World Wide Web page ranking.
(Keywords: Graph mining, web searches, node ranking, HITS, link analysis)
- Local and Global Trust Based on the Concept of Promises
(submitted) 2006
We use the notion of a promise to define local trust between
agents possessing autonomous decision-making. An agent is trustworthy if it
is expected that it will keep a promise. This definition satisfies
most commonplace meanings of trust. Reputation is an estimation
of value that is passed on from agent to agent.
Our definition distinguishes types of trust, for different
behaviours, and decouples the concept of agent reliability from the
behaviour on which the judgement is based. We show, however, that
trust is fundamentally heuristic, as it provides insufficient
information for agents to make a rational judgement. A global
trustworthiness, or {\em community trust} can be defined by a
proportional, self-consistent voting process, as a weighted
eigenvector-centrality function of the promise theoretical graph.
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