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i n this paper, we propose a stream mining architecture which is based on a single-puss approach. Our approach can be used to develop efficient, effective, and active intrusion detection mechanisms which satisfy the near real-time requirements of processing data strenms an a network with minimal overhead. The key idea is that new patterns can now be detected on-the-fly. They areflagged as network attacks or labeled as normal trafsic, based on the current network trend, thus reducing the false alarm rates prevalent in active network intrusion systems and increasing the low detection rate which characterizes passive approaches.

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