Biblio
Filters: Keyword is black-hole attacks [Clear All Filters]
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2018. An Approach for Black-hole Attack Mitigation in Disruption-tolerant Ad-hoc Smartphone Networks. Proceedings of the 13th Workshop on Challenged Networks. :19–24.
When cellular networks collapse (e.g. due to disaster scenarios), it is vital to quickly establish new communication channels. The worldwide spread of smartphones, which support multiple communication standards, offers a great potential to solve this problem with commodity hardware. On the software side, Disruption-tolerant Network technologies may be leveraged to transmit messages between devices, even if there is no direct connection between them. However, DTNs are vulnerable to black-hole attacks. Therefore, mechanisms have to be available to address this problem in order to provide reliable networks. In this paper, we present a concept for an ad-hoc smartphone-based DTN which is robust against packet drop attacks as network nodes are able to identify attackers and exclude them from the network. The overall concept has been practically evaluated using an implementation for the Android platform. Our results show that the approach is capable to mitigate black-hole attacks effectively with high detection rate and short convergency time.
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2018. A trust model based on evidence-based subjective logic for securing wireless mesh networks. 2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN). :1–5.
Wireless Mesh Network (WMN) is a promising networking technology, which is cost effective, robust, easily maintainable and provides reliable service coverage. WMNs do not rely on a centralized administration and have a distributed nature in which nodes can participate in routing packets. Such design and structure makes WMNs vulnerable to a variety of security threats. Therefore, to ensure secure route discovery in WMNs, we propose a trust model which is based on Evidence- Based Subjective Logic (EBSL). The proposed trust model computes trust values of individual nodes and manages node reputation. We use watchdog detection mechanism to monitor selfish behavior in the network. A node's final trust value is calculated by aggregating the nodes direct and recommendation trust information. The proposed trust model ensures secure routing of packets by avoiding paths with untrusted nodes. The trust model is able to detect selfish behavior such as black-hole and gray-hole attacks.