Background/Objectives: IoT developmental background: IoT, which is the key technology in the fourth industrial revolution, utilizes the Internet. Particularly, the growth of convergence products that utilize it has been constant with the demands of IoT services using the network of the Internet.Methods/Statistical analysis: IoT network consists of products equipped with various sensors to communicate; sensor nodes are made up of low volume memory, low performance CPU, and battery when they are used in the network. There has been the demand of secure transmission of information measured by a sensor node to the IoT platform. We conduct a study on how we can improve security in the IoT environment.Findings: Generally, sensor nodes are applied with basic security provided by IoT communication protocol rather than their own encryption. Therefore, sensor nodes are vulnerable in terms of security and the IoT platform that utilizes information collected by them would process distorted information.In order to draw a strategy to prevent security breach, we analyze security threat and the type of attacks.Improvements/Applications: We suggest a countermeasure to deal with security threat of sensor nodes and situations in which sensor nodes are vulnerable in IoT environment. To secure integrity of communication and transaction between a sensor node and an IoT platform in the future, the application of block chain technology into the IoT environment is necessary.

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The Electronic Support System collects and analyzes the received radar signals in order to cope with the electronic attack in real-time. The radar-pulse clustering system classifies the radar signals that are considered to be emitted by a single source. This paper proposed a radar-pulse clustering algorithm based on four kinds of features: the direction, frequency, pulse width, and the difference of arrival time between two successive pulses. The experiment results show that the proposing algorithm could trace the moving emitter and classify the timely separated signals into different classes.