Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所 > 中科院长春光机所知识产出

	Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion
	Song, Y. Z.
刊名	China Communications
	2015
卷号	12 期号:2 页码:107-117
英文摘要	Towards the problems of existing detection methods, a novel real-time detection method (DMFIF) based on fractal and information fusion is proposed. It focuses on the intrinsic macroscopic characteristics of network, which reflect not the "unique" abnormalities of P2P botnets but the "common" abnormalities of them. It regards network traffic as the signal, and synthetically considers the macroscopic characteristics of network under different time scales with the fractal theory, including the self-similarity and the local singularity, which don't vary with the topology structures, the protocols and the attack types of P2P botnet. At first detect traffic abnormalities of the above characteristics with the nonparametric CUSUM algorithm, and achieve the final result by fusing the above detection results with the Dempster-Shafer evidence theory. Moreover, the side effect on detecting P2P botnet which web applications generated is considered. The experiments show that DMFIF can detect P2P botnet with a higher degree of precision.
收录类别	SCI
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/55402]
专题	长春光学精密机械与物理研究所_中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Song, Y. Z.. Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion[J]. China Communications,2015,12(2):107-117.
APA	Song, Y. Z..(2015).Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion.China Communications,12(2),107-117.
MLA	Song, Y. Z.."Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion".China Communications 12.2(2015):107-117.