Defense against node compromise in sensor network security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Defense Against Node Compromise in Sensor Network Security

Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

Herbivore and nutrient impact on primary producer assemblages in a tropical marine environment

Globally, human populations are increasing and coastal ecosystems are becoming increasingly impacted by anthropogenic stressors. As eutrophication and exploitation of coastal resources increases, primary producer response to these drivers becomes a key indicator of ecosystem stability. Despite the importance of monitoring primary producers such as seagrasses and macroalgae, detailed studies on the response of these benthic habitat components to drivers remain relatively sparse. Utilizing a multi-faceted examination of turtle-seagrass and sea urchin-macroalgae consumer and nutrient dynamics, I elucidate the impact of these drivers in Akumal, Quintana Roo, Mexico. In Yal Ku Lagoon, macroalgae bioindicators signified high nutrient availability, which is important for further studies, but did not consistently follow published trends reflecting decreased δ 15N content with distance from suspected source. In Akumal Bay, eutrophication and grazing by turtles and fishes combine to structure patches within the seagrass beds. Grazed seagrass patches had higher structural complexity and productivity than patches continually grazed by turtles and fishes. Results from this study indicate that patch abandonment may follow giving-up density theory, the first to be recorded in the marine environment. As Diadema antillarum populations recover after their massive mortality thirty years ago, the role these echinoids will have in reducing macroalgae cover and altering ecosystem state remains to be clear. Although Diadema antillarum densities within the coral reef ecosystem were comparable to other regions within the Caribbean, the echinoid population in Akumal Bay was an insufficient driver to prevent dominance of a turf-algal-sediment (TAS) state. After a four year study, declining coral cover coupled with increased algal cover suggests that the TAS-dominated state is likely to persist over time despite echinoid recovery. Studies on macroalgal diversity and nutrients within this same region of echinoids indicated diversity and nutrient content of macroalgae increased, which may further increase the persistence of the algal-dominated state. This study provides valuable insight into the variable effects of herbivores and nutrients on primary producers within a tropical coastal ecosystem. Results from this work challenge many of the currently accepted theories on primary producer response to nutrients and herbivory while providing a framework for further studies into these dynamics.