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Gaining a better knowledge of one's own network is crucial to effectively manage and secure today's large, diverse campus and enterprise networks. Because of the large number of IP addresses (or hosts) and the prevalent use of dynamic IP addresses, profiling and tracking individual hosts within such large networks may not be effective nor scalable. In this paper, we develop a novel methodology for...
The ever-increasing complexity and diversity of the Internet pose several challenges to network operators and administrators and, in general, Internet users. More specifically, because of the diversity in applications and usage patterns; the prevalence of dynamic IP addresses and applications that do not conform to standard configuration (e.g. VoIP to bypass firewalls), monitoring and securing networks...
As a key approach to securing large networks, existing anomaly detection techniques focus primarily on network traffic data. However, the sheer volume of such data often renders detailed analysis very expensive and reduces the effectiveness of these tools. In this paper, we propose a light-weight anomaly detection approach based on unproductive DNS traffic, namely, the failed DNS queries, with a novel...
Today's large campus and enterprise networks are characterized by their complexity, i.e. containing thousands of hosts, and diversity, i.e. with various applications and usage patterns. To effectively manage and secure such networks, network operators and system administrators are faced with the challenge of characterizing, profiling and tracking activity patterns passing through their networks. Because...
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