Traffic classification seeks to assign packet flows to an appropriate quality of service(QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

In this paper, we propose a Cooperative Transmission Strategy using Entropy-based Relay Selection in Mobile Ad-hoc Wireless Sensor Networks(MAWSN) with Rayleigh Fading Environments. The main features and contributions of the proposed cooperative transmission strategy are as follows. First, entropy-based relay selection is used to improve data transmission reliability from a source node to a destination node. Second, we present a theoretical analysis model for the proposed cooperative transmission strategy with the outage probability of the end-to-end performance. The performance of our protocol is evaluated using analysis and simulation.

The demand for services using digital technology is constantly increasing as new developments in digital consumer electronics and the Internet are made. This is especially true in terms of the demand for IPTV utilizing high speed Internet networks. Research on IPTV threats is important for facilitating financial transactions via IPTV and preventing illegal use or copying of digital content. Thus, this paper analyzes IPTV threats via the IPTV value chain. That is, the distribution system for IPTV service is analyzed along with the components of the value chain and corresponding IPTV security requirements or security technologies, in order to perform a threat analysis and research suitable for the IPTV service environment. This paper has a greater focus on the value chain of the IPTV business than the approach in previous research, in order to analyze security requirements and technologies that are more applicable to the business environment.

Current group key agreement protocols(often tree-based) involve unnecessary delays because members with low-performance computer systems can join group key computation. These delays are caused by the computations needed to balance a key tree after membership changes. An alternate approach to group key generation that reduces delays is the dynamic prioritizing mechanism of filtering low performance members in group key generation. This paper presents an efficient tree-based group key agreement protocol and the results of its performance evaluation. The proposed approach to filtering of low performance members in group key generation is scalable and it requires less computational overhead than conventional tree-based protocols.

In this paper, we introduce a grid-based key pre-distribution scheme in wireless sensor networks, which aims to improve the connectivity and resiliency while maintaining a reasonable overhead. We consider simplification of the key establishment logic and enhancement of the connectivity via plat polynomial assignment on a three-dimensional grid for node allocation and keying material assignment. We demonstrate that our scheme results in improvements via a detailed discussion on the connectivity, resource usage, security features and resiliency. A comparison with other relevant works from the literature along with a demonstrated implementation on typical sensor nodes shows the feasibility of the introduced scheme and its applicability for large networks.

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.