Wireless Sensor Networks (WSNs) have been recognized for their utility in a variety of different fields including military sensing and tracking, environmental monitoring, patient monitoring and tracking smart environments. The more scientists try to develop further cost and energy efficient computing devices and algorithms for WSNs, the more challenging it becomes to fit the security of WSNs into such a constrained environment. Thus, familiarity with the security aspects of WSNs is essential before designing WSN systems. In order to provide effective integrity, confidentiality, and authentication during communication, the need for additional security measures in WSNs emerges. In this paper, the authors review the security requirements for WSNs, the different kinds of possible attacks, and security mechanisms used to overcome these attacks. The authors also present some statistical data for such attacks in WSN and some tables that indicate a comparison between different security mechanisms.

Abstract-We are interested in rainfall events evaluation by applying adaptive neural-fuzzy inference System. Four parameters: Temperature, relative humidity, total cloud cover and due point are the input variables for our model, each has 121 membership functions. The data is six years METAR data for Mashhad city [2007][2008][2009][2010][2011][2012]. Different models for Mashhad city stations were constructed depending on the available data sets. Among the overall 25 possibilities one model with one hundred twenty one fuzzy IF-THEN rules has chosen. The output variable is 0 (no rainfall event) or 1 (rainfall event). With comparing trained data with actual data, we could evaluate rainfall events about 90.5 percent. The results are in high agreement with the recorded data for the station with increasing in values towards the real time rain events. All implementation are done with MATLAB.