Grouping-Based Resilient Statistical En-Route Filtering for Sensor Networks

Abstract

In sensor networks, the adversaries can inject false data reports from compromising nodes. Previous approaches for filtering false reports, notably statistical en-route filtering, adopt a simple strategy for grouping sensor nodes that requires redundant groups and thus decrease the filtering effectiveness. Worse still, they either suffer a threshold problem, which may lead to complete breakdown of the security protection when the threshold is exceeded, or are dependent on sink stationarity and specific routing protocols, which cannot work with mobile sinks and various routing protocols. In response to these, this paper proposes a scheme, referred to as Grouping-based Resilient Statistical En-route Filtering (GRSEF), in which nodes are grouped once deployed without requiring redundant groups and a location-aware approach based on terrain division along multiple axes is proposed for key derivation. The design of GRSEF, which is independent of sink stationarity and routing protocols, provides a well suitable en-routing filtering solution for sensor networks with mobile sinks. Analytical and simulation results verify that the scheme significantly improves the filtering effectiveness and efficiently achieves the resiliency against node compromise.

False Data Filtering in Wireless Sensor Networks

“…Therefore network security is good location of the key technology [9], elliptic curve key technology [10], DRA mechanism [13] interference polynomial technology [16] and network authentication node assignment strategy [20]; high adaptability is DSF mechanism [18] and network authentication node assignment strategy [20]; large overhead is MAC authentication mechanism [1], one-way hash chain technology [5] (storage overhead is too large), PVFS mechanism [6], location of the key technology [9], elliptic curve key technology [10] and multi path routing filtering mechanism, especially elliptic curve key technology of network for large low density and mobility [10]; assumptions it is the location of the key technology of [9], time synchronization technology [17] proposed technology.…”

“…It is the classic filtering schemes, MAC authentication [4], PVFS mechanism [5][6], SIEF mechanism [7] and so on, because their resistance to false data ability strong.…”

“…As illustrated in Figure. 1, we assume that six nodes ） （ The filtering mechanism based on SEF mainly includes IHA [4], GRSEF [5], MDSEF [6] and AERF [7] and so on. Zhu et al firstly have suggested a step-by-step authentication mechanism (called IHA).…”

“…By using the algorithm in [20], the cluster head node set v CH replaces node set V as input, which constructed the cluster head tree to maximize the network life cycle, as shown in Figure 4.…”

Constrained Function-Based Message Authentication for Sensor Networks

“…With the sophisticated use of one-way hash chains in clustered sensor networks, DEF [43] has improved filtering power over SEF [49]. Using the proposed multiple-axis technique, GREF [45] is designed to support en-route filtering in the networks with multiple data sinks. LBRS [50], LTE [52], and LEDS [35] take advantage of location information to enhance the resilience to node compromises.…”