LEADER 02586oam 2200433zu 450 001 9910140800703321 005 20241212220014.0 010 $a9781424469215 010 $a142446921X 035 $a(CKB)2670000000046377 035 $a(SSID)ssj0000452684 035 $a(PQKBManifestationID)12139205 035 $a(PQKBTitleCode)TC0000452684 035 $a(PQKBWorkID)10472490 035 $a(PQKB)10939945 035 $a(NjHacI)992670000000046377 035 $a(EXLCZ)992670000000046377 100 $a20160829d2010 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$a2010 IEEE International Conference on Fuzzy Systems 210 31$a[Place of publication not identified]$cI E E E$d2010 215 $a1 online resource $cillustrations 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781424469192 311 08$a1424469198 330 $aThe effect of advances in the fields of ubiquitous computing, wireless communications and embedded system design has seen a corresponding rapid improvement of wireless sensor technology. Sensor networks have emerged as a platform for deployment and sustenance of critical applications that require real-time sensing and data acquisition for decision-making purposes. A significant number of malicious attacks against the security of such networks have been identified in recent times. Considering the untrusted environments of operations of such networks, the threat of distributed attacks against constrained sensory resources i.e. sensor power, computation and communication capabilities cannot be overlooked. In this paper, we propose a fuzzy logic-based approach towards achieving demarkation in the values of specific parameters of an attack detection scheme for detecting distributed node-exhaustion attacks in wireless sensor networks. Using the Unified And-Or (UAO) aggregation operator, we model and formulate a mechanism to achieve a tradeoff between frequent attack detection and sensor node energy utilization. Simulation results prove the effectiveness of our approach in addressing the issue of computing the optimal parameter values for achieving a reasonable tradeoff between attack detection rate and sensor node energy utilization rate. 606 $aFuzzy systems$vCongresses 615 0$aFuzzy systems 676 $a003.7 702 $aIEEE Staff 801 0$bPQKB 906 $aPROCEEDING 912 $a9910140800703321 996 $a2010 IEEE International Conference on Fuzzy Systems$92545901 997 $aUNINA