Abstract:Voltage collapse and blackout can occur in an electric power system when load powers vary so that the system loses stability in a saddle node bifurcation. We propose new iterative and direct methods to compute load powers a t which bifurcation occurs and which are locally closest to the current operating load powers. The distance in load power parameter space to this locally closest bifurcation is an index of voltage collapse. The pattern of load power increase need not be predicted; instead the index is a worst cage load power margin. The computations are illustrated in the 6 dimensional load power parameter space of a 5 bus power system. The normal vector and curvature of a hypersurface' of critical load powers a t which bifurcation occurs are also computed. The sensitivity of the index to parameters and controls is easily obtained from the normal vector.
When a generator of a heavily loaded electric power system reaches a reacthe power limit, the system can become immediately unstable and a dynamic voltage collapse leading to blackout may follow.We study the statics and dynamics of this mechanism for voltage collapse by example and by the generic theory of saddle node and transcritical bifurcations. Load power margin calculations can be misleading if the immediate instability phenomenon is neglected.
We consider website fingerprinting over encrypted and proxied channel. It has been shown that information on packet sizes is sufficient to achieve good identification accuracy. Recently, traffic morphing [1] was proposed to thwart website fingerprinting by changing the packet size distribution so as to mimic some other website, while minimizing bandwidth overhead. In this paper, we point out that packet ordering information, though noisy, can be utilized to enhance website fingerprinting. In addition, traces of the ordering information remain even under traffic morphing and they can be extracted for identification. When web access is performed over OpenSSH and 2000 profiled websites, the identification accuracy of our scheme reaches 81%, which is 11% better than Liberatore and Levine's scheme presented in CCS'06 [2]. We are able to identify 78% of the morphed traffic among 2000 websites while Liberatore and Levine's scheme identifies only 52%. Our analysis suggests that an effective countermeasure to website fingerprinting should not only hide the packet size distribution, but also aggressively remove the ordering information.
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