Analysis on Intrusion Detection Techniques in Visual Sensor Network and its Applications

Developments in image and video technologies enabled easy access to a new type of sensor- based networks called Visual Sensor Networks (VSN). Sensor nodes are able to collect large volumes of images, process them and send extracted data to each other and to the base station for further analysis. Visual sensor networks (VSNs) are extraordinarily vulnerable to attacks due to their open deployment in possibly unattended environments. To enhance the network security of VSNs, an intrusion detection system (IDS) is an effective countermeasure. Different intrusion detection techniques are used in VSN. First method is a multimedia intrusion detection application which appears as a promising application of multi-tier Wireless Multimedia Sensor Networks, where the lower tier can detect the intruder using scalar sensors, and the higher tier camera nodes will be woken up to send real time video sequences from the detected area. Forward Error Correction (FEC) can be regarded as a best solution to improve video quality level from the user point-of- view. Quality of Experience (QoE)-aware FEC mechanism for WMSNs, creates redundant packets based on impact of the frame on the user experience. The QoE aware FEC mechanism is applied on a big data analytic architecture. This method uses a three layered big data analytic architecture which is designed to analyze the data generated and detection of the intruder using camera sensors. Aim of this paper is to analyze various intrusion detection techniques in VSN.