PurposeThe purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.Design/methodology/approachThis paper introduces a tractable guarantee network model that captures the invulnerability of the network in terms of cascade-based attack. Furthermore, the equilibrium points are introduced for banks to determine loan origination.FindingsThe proposed approach not only develops equilibrium analysis as an extended perspective in the guarantee network, but also applies cascading failure method to construct the guarantee network. The equilibrium points are examined by simulating experiment. The invulnerability of the guarantee network is quantified by the survival of firms in the simulating progress.Research limitations/implicationsThere is less study in equilibrium analysis of the guarantee network. Additionally, cascading failure model is expressed in the presented approach. Moreover, agent-based model can be extended in generating the guarantee network in the future study.Originality/valueThe approach of this paper presents a framework to analyze the equilibrium of the guarantee network. For this, the systemic risk of the whole guarantee network and each node's contribution are measured to predict the probability of default on cascading failure. Focusing on cascade failure process based on equilibrium point, the invulnerability of the guarantee network can be quantified.
Due to the lack of security mechanisms and sensor resources, the IPv6 Routing Protocol for Low power and Lossy networks (RPL) is vulnerable to various attacks, among which Sybil attack has received a lot of attention. This paper proposes a novel scheme based on coarse‐grained localization and fine‐grained isolation (CLFI) for defending Sybil attack. In CLFI, normal neighbor nodes are identified based on received signal strength indicator (RSSI). To further identify Sybil nodes, a physical address identifier called
is defined, which is calculated as the difference of RSSI at two different receivers when they are receiving the same packet. In order to facilitate the calculation of
, a set of anchor nodes are deployed to broadcast the received RPL control packets. Then Sybil behaviors can be detected by comparing the physical address identifier with the logical address embedded in the received packets. The proposed CLFI scheme has been completely implemented in the Contiki operating system. The extensive evaluation in comparison with the state‐of‐the‐art scheme indicates that CLFI can quickly localize and isolate Sybil nodes.
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