In wireless environment researches on security issues in various layering level of the networks are focused recent times. One of the major issue is denial of service attacks. This paper mainly deals with the detection of syn flooding attacks which is one form of denial of service attacks in wireless sensor networks. It is a type of attack done by the attacker to a specific server to down them by flooding the requests. So, the server will be busy waiting for the requests created by the attacker. In view to this attack an efficient routing approach by distance-2 dominating set is proposed to exhibit the plan of clustering the nodes in the network for effective data transmission. The traffic limit method is used to monitor the bandwidth usage of the nodes concerned in the network to find the flooding attacks in real time event detection environment. The test cases are implemented using network simulation tool. The outcomes discussed about here are to demonstrate the packet delivery ratio, end-to-end delay and the bandwidth usage by the malicious nodes which will be high of the various other authorized nodes in the system.

We live in a world where technology embraces us and makes our lives easier. With increasing technological advances we feel the need for smart robotic assistants/companions to reduce the manual efforts taken by humans in day-to-day tasks and providing the necessary knowledge. In this paper, we develop a smart self companion robot that runs using human voice commands using some standard way of speech and this voice is converted into standard text form which is, in turn, converted into instructions and is fed to the robot, which further performs the necessary actions. The companion is fully automated with the capability of movement based on object tracking and voice response based on facial expression. The three main modules of this work are facial detection, emotion detection, and voice recognition. The bot is a wireless vehicle that will move along the human, interact with them depending on his/their emotions.