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Design and implementation of cloud resource monitoring system based on bionics
SUN Peng, XU Han, CHEN Jingjing, CAO Xudong
Journal of Computer Applications    2016, 36 (7): 2051-2055.   DOI: 10.11772/j.issn.1001-9081.2016.07.2051
Abstract368)      PDF (811KB)(280)       Save
Concerning the problems of heavy network traffic, which is caused by the excessive load of master node, bad expansibility and poor ability to handle node failure in existing monitoring system, a novel Cloud Monitoring System based on Bionic autonomic nervous system (B-CMS) was proposed. Firstly, B-CMS imported hierarchical storage and batch-wise report mechanism to upload the monitoring information, which can decrease the network traffic at any moment to ensure monitor system's stability. In addition, the use of similar Dynamic Host Configuration Protocol (DHCP) and polling-driven heartbeat checking mechanism enabled the monitor system to get the self-organizing and self-repairing ability which is similar to Bionic Autonomic Nervous System (BANS) when adding new node and handling node failure in autonomic way. The experimental results show that B-CMS achieves self-organizing and self-repairing, and effectively decreases network traffic. In some special moment, the network traffic is only one-third of the original system.
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Anti-fingerprinting model of operation system based on network deception
CAO Xu, FEI Jinlong, ZHU Yuefei
Journal of Computer Applications    2016, 36 (3): 661-664.   DOI: 10.11772/j.issn.1001-9081.2016.03.661
Abstract607)      PDF (767KB)(415)       Save
Since traditional host operating system anti-fingerprinting technologies is lack of the ability of integration defense, a Network Deception based operating system Anti-Fingerprinting model (NDAF) was proposed. Firstly, basic working principle was introduced. The deception server made the fingerprint deception template. Each host dynamically changed the protocol stack fingerprint according to the fingerprint deception template, therefore the process of operating system fingerprinting by attacker was misguided. Secondly, a trust management mechanism was proposed to improve the system efficiency. Based on the different degree of threat, different deception strategies were carried out. Experiments show that NDAF makes certain influence on network efficiency, about 11% to 15%. Comparing experiments show that the anti-fingerprinting ability of NDAF is better than typical operating system anti-fingerprinting tools (OSfuscatge and IPmorph). NDAF can effectively increase the security of target network by integration defense and deception defense.
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