Biblio

Reliability analysis of concurrent data based on Botnet modeling is conducted in this paper. At present, the detection methods for botnets are mainly focused on two aspects. The first type requires the monitoring of high-privilege systems, which will bring certain security risks to the terminal. The second type is to identify botnets by identifying spam or spam, which is not targeted. By introducing multi-dimensional permutation entropy, the impact of permutation entropy on the permutation entropy is calculated based on the data communicated between zombies, describing the complexity of the network traffic time series, and the clustering variance method can effectively solve the difficulty of the detection. This paper is organized based on the data complex structure analysis. The experimental results show acceptable performance.

The globalization of trade is due to the transportation possibilities and the standardization (containerization of freight). The dependency of the economy to the sea and to the merchant navy has increase this last decade. This process forms a worldwide maritime network between the different locations of production and consumption. This network, representing between 80 % and 90% of world traffic is a major economic concern, including freight distribution, raw materials or energy. Rodrigue demonstrates[1] the economic dependency of energy is increasing in the industrialized countries (North America, Europe, East Asia). The inter-regional trade of oil was 31 million bbl/day in 2002 and is expected to grow up to 57 bbl/day in 2030 [2]. Most of the international traffic use a maritime way, where may occur disruptions. For example, the Suez crisis (1956-1957) caused a closure of the canal, reducing the throughput capacity of transportation. This disruption cost a 2 millions of barrels lost per day. This article focuses on vulnerability of the energy supply, and proposes a methodology to formalize and assess the vulnerability of the network by taking into account the spatial structure of maritime territories.