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There is a growing interest in the use of video sensor networks insurveillance applications in order to detect intruders with low cost. Theessential concern of such networks is whether or not a specified target canpass or intrude the monitored region without being detected. This concern formsa serious challenge to wireless video sensor networks of weak computation andbattery power.  In this paper, our aim is to prolong the whole network lifetime whilefulfilling the surveillance application needs. We present a novel schedulingalgorithm where only a subset of video nodes contribute significantly to detectintruders and prevent malicious attacker to predict the behavior of the networkprior to intrusion. Our approach is chaos-based, where every node based on itslast detection, a hash value and some pseudo-random numbers easily computes adecision function to go to sleep or active mode. We validate the efficiency ofour approach through theoretical analysis and demonstrate the benefits of ourscheduling algorithm by simulations. Results show that in addition of beingable to increase the whole network lifetime and to present comparable resultsagainst random attacks (low stealth time), our scheme is also able to withstandmalicious attacks due to its fully unpredictable behavior.

Low Cost Monitoring and Intruders Detection using Wireless Video Sensor Networks