Abstract
Per-flow connection state monitoring is crucial for detecting malicious traffic or anomalies in networks. The monitoring is extremely challenging in high-speed networks, and would involve high computation and memory costs. We propose a novel stateful Bloom filter (stateBF) to enable a highly compact, low-overhead, and accurate flow-state storage service for the monitoring of the per-flow connection states. Unlike the standard Bloom filter and its various extensions, we design a special cell-based data structure for stateBF instead of bit array to track both the state value and the number of times the same state value is inserted to stateBF. We further design four stateBF operations for advanced flow-state management. To enable efficient stateBF operations, they are designed to be bitwise for the simple implementation. We have done extensive simulations with data traces from public MAWI and from a university campus. Our performance results demonstrate that stateBF can support per-flow state storage services in high speed networks with low storage space, and high querying speed and accuracy.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Network Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
