Search

We propose an adaptive cyber security monitoring system that integrates a number of component techniques to collect time-series situation information, perform intrusion detection, and characterize and identify security events so corresponding defense actions can be taken in a timely and effective manner. We employ a decision fusion algorithm with analytically proven performance guarantee for intrusion detection based on local votes from distributed sensors. The security events in the proposed system are represented as forms of correlation networks using random matrix theory and identified through the computation of network similarity measurement. Extensive simulation results on event identification illustrate the efficacy of the proposed system.

The significance of high-performance dedicated networks has been well recognized due to the rapidly increasing number of large-scale applications that require high-speed data transfer. Efficient algorithms are needed for path computation and bandwidth scheduling in dedicated networks to improve the utilization of network resources and meet diverse user requests. We consider two periodic bandwidth scheduling problems: multiple data transfer allocation (MDTA) and multiple fixed-slot bandwidth reservation (MFBR), both of which schedule a number of user requests accumulated in a certain period. MDTA is to assign multiple data transfer requests on several pre-specified network paths to minimize the total data transfer end time, while MFBR is to satisfy multiple bandwidth reservation requests, each of which specifies a bandwidth and a time slot. For MDTA, we design an optimal algorithm and provide its correctness proof; for MFBR, we prove it to be NP-complete and propose a heuristic algorithm, Minimal Bandwidth and Distance Product Algorithm (MBDPA). Extensive simulation results illustrate the performance superiority of the proposed MBDPA over a greedy heuristic approach and provide valuable insight into the advantage of periodic bandwidth scheduling over instant bandwidth scheduling.