Wireless sensor networks (WSNs) have unprecedented environment-monitoring capabilities with low cost, small size, and limited energy. In security protocols, the general approach for energy efficiency is to reduce the number of attacks while underlying routing protocols are often ignored. In this paper, we present an energy-aware routing and filtering node (ERF) selection to extend network lifetime in commutative cipher-based en-route filtering (CCEF). In addition to distance to the destination, the residual energy is considered for forwarding node selection. In a given path, filtering nodes are carefully selected based on attack information, presence of witness key ( ), and current state of a node in sensor network. Results demonstrate the validity of our simple approach to significantly prolong the network lifetime by balancing network energy consumption.

Wireless sensor networks are widely deployed and implicitly characterized by stringent energy and computation constraints. Sensor nodes are vulnerable to false positive and false negative attacks that inject false data through compromised nodes. Such attacks cause false alarms with energy drain and information loss. Although several en-route filtering schemes have been designed to detect the attacks, they focus on saving energy through early filtering or continuous delivery of data in accordance with verification records; they cannot exclude compromised nodes. In this paper, we propose a scheme that effectively identifies the compromised nodes and copes with new attacks using a context-aware architecture. In addition, the proposed scheme improves the security strength and energy efficiency of the network. Simulation results validate that the proposed scheme provides energy savings of up to 45 percent and allows fewer attack successes than the existing scheme.

Generally, simulation models are constructed to replicate and predict the behavior of real systems that currently exist or are expected to exist in the future. Once a simulation model is implemented, the model can be connected to a real system for which the model has been built through sensors or networks so that important activities in the real system can be monitored indirectly through the model. This article proposes a modeling formalism BM-DEVS (Behavior Monitor-DEVS) that defines simulation models capable of monitoring the desired behavior patterns within the models so that the target system’s behavior can be monitored indirectly. In BM-DEVS, an extension of classic Discrete Event System Specification (DEVS), the behavior to be monitored is expressed as a set of temporal logic (TL) production rules within a multi-component model that consists of multiple component models to be monitored. An inference engine module for reasoning with the TL rules is designed based on the abstract simulator that carries out instructions in the BM-DEVS models to perform the simulation process. The major application of BM-DEVS is in the design and implementation of the context-aware architecture needed for various intelligent systems as a core constituent. Essentially all systems where some form of behavior monitoring is required are candidate applications of BM-DEVS. This research is motivated by the view that there exists symmetry between the real-world and the cyber world, in that the problems in both environments should be expressed with the same basic constituents of time and space; this naturally leads to adopting spatiotemporal variables composed of simulation models and developing a problem solver that exploits these variables.

In wireless sensor networks, sensors are extremely vulnerable to false positive and false negative attacks due to their stringent energy and computational constraints. Several en-route filtering schemes mainly focus on saving energy through early detection of false data within a short distance against these attacks; however, they cannot immediately block the false data injected by compromised nodes. A security scheme uses context-aware architecture for a probabilistic voting–based filtering scheme to detect the compromised nodes and block the injection of false data, unlike security protocols. Although these schemes effectively obstruct the false data forwarding, they cannot make any detour around the compromised node to avoid it during data forwarding. In this article, we propose a discrete event simulation–based energy efficient path determination scheme that takes a detour around the compromised node against the attacks. Our proposed scheme extracts candidate paths considering the network status and selects a path with the highest energy efficiency from among the candidates using discrete event simulation. Simulation results indicate that the proposed scheme provides energy savings of up to 12% while maintaining the security strength against the two attacks compared to the existing schemes.