The behavior of both botnets and worms in peer-to-peer networks have been empirically examined and models or simulations of their behavior have been attempted, and the manner in which different nodes in peer-to-peer networks develop in and of themselves and in terms of their relationships with other nodes -- the very architecture of the network itself, in other words, which is necessarily dynamic in a peer-to-peer network -- makes it easier for these threats to spread and evolve undetected due to this architecture and to the patterns of information flow over such networks (Fan, 2011; Xu et al., 2011). When it comes to worms propagating in peer-to-eer networks, the activity of the worm itself has been demonstrated to be the most necessary knowledge in terms of tracking and preventing the continued spread and damage of such a threat, while botnets generally show more "robustness" an are better impacted by shifts in the network itself, specifically by decentralizing nodes in an attempt to isolate and eliminate the botnet (Fan, 2011; Xu et al., 2011). Both of these threats are more difficult to track and eliminate when unstructured in nature and/or environment.
As the research into peer-to-peer network shows, the less structured a network is the more vulnerable it is to unstructured attacks, and thus ultimately to unstructured attacks as well. When networks are created on the fly or "ad hoc," they become that much more unstructured; even if they are implemented for a specific purpose the very nature of an ad hoc network means that it is built not form an explicit plan and method of resource acquisition, but simply growing in whatever manner it is possible to grow in order to achieve the needs of the network users/architects (Yang et al., 2010). Pattern recognition becomes more difficult when the network does not have dependable data for normal usage, making threat detection incredibly difficult especially for unstructured threats that do not necessarily attempt to adversely affect network performance or inappropriately utilize or access sensitive data (Yang et al., 2010). Given the potential for a seemingly innocuous unstructured attack to suddenly achieve real and drastic damaging effects these threats are still important to counter, but the difficulty of detection can make this all but impossible (Yang et al., 2010). Several approaches to threat detection have been developed, of course, but the appropriate detection and reaction method is dictated both by certain network features and by features of the potential or actual threat/attack, and thus the issue remains complex and often very difficult to deal with even fro experienced network security monitors (Yang et al., 2010).
One attempt to more effectively model behaviors and relationships in unstructured networks and unstructured threats or attacks has been to use some of the relationships and mechanisms defined and described in game theory as a means of predicting actions taken by network users and would-be attackers in unstructured scenarios (Manshaei et al., 2011). The authors of this particular piece of research claim to have made some headway in terms of describing threats and attacks from this perspective, yet they themselves are not able to identify any clear solutions from their preliminary findings and instead simply suggest that further research is required in this area (Manshaei et al., 2011). In truth, it is not entirely clear that the game theory perspective will prove to be an adequate approach to the problems of unstructured threats and attacks, and indeed there are other frameworks that appear to provide more direct, coherent, and consistent results. Developing new perspectives for network architecture and alert signaling using more traditional frameworks for threat definition and prediction could prove ore effective than trying to rebuild the very manner in which threats are predicted, and indeed there has been some experimental success demonstrated with specific new architectures and signaling triggers when it comes to unstructured attack detection and prevention (Colajanni et al., 2010). Practical efforts built on existing theory, even when those theories are based on the limited knowledge available to researchers in the area and real-world network security monitors, appear to be more effective than changes in underlying theory and modeling (Colajanni et al., 2010; Manshaei et al., 2011).
Discussion
As the current research shows, being able to define, predict, and respond to unstructured threats is still a very significant problem in network security monitoring, and one that is in need of further research before it can be considered adequately addressed and properly understood. There are both general and specific problems when it comes to unstructured threats and attacks on a network, from the lack of direct harm that many unstructured attacks might have, at least initially, to the psychological rather than mathematical/rational...
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