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K-means algorithm could be used in intrusion detection, and selection of initial cluster centers was one of the most important factor that influenced the clustering performance, traditional method had a certain degree of randomness in dealing with this problem, therefore, information entropy was introduced into the process of cluster centers selection, and a fusion algorithm combining with information entropy and K-means algorithm was proposed, information entropy value was used to measure the similarity degree among records, it could help to choose a least similar record to be a cluster center. Comparison results show that the detection ratio and false alarm ratio of the proposed method is better than traditional K-means algorithm.

Abstract. The Internet of Things, as an emerging global Internet-based technical architecture, facilitates the exchange of goods and services in global supply chain networks. The phrase Internet of Things (IoT) heralds a vision of the future Internet where connecting physical things, from banknotes to bicycles, through a network will let them take an active part in the Internet, exchanging information about themselves and their surroundings. The IoT industry is still in an early stage of development, whose technologies, standards, product and the market still need to be improved, and whose related areas also need to be studied and discussed. This paper presents detailed analysis and comparison about a misunderstanding of the current awareness: IoT = Internet + WSN, which enable people to understand IoT more thoroughly. The IoT is a network of connecting objects, whose architecture is different from that of the traditional network, which can not simply described by the use of layered network architecture. In this paper, based on the IoT itself, the three dimensions architecture is researched and found, which is the most suitable architecture of IoT.Keywords: the Internet of Things, architecture analysis, wireless sensor network, the three dimensions architecture.

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