Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

The Blackett Memorial Lecture, 1991: Chemical Insights into High-Temperature Superconductors

The high-temperature superconductors are complex oxides, generally containing two-dimensional CuO2 sheets. Various families of the cuprate superconductors are described, paying special attention to aspects related to oxygen stoichiometry, phase stability, synthesis and chemical manipulation of charge carriers. Other aspects discussed are chemical applications of cuprates, possibly as gas sensors and copper-free oxide superconductors. All but the substituted Nd and Pr cuprates are hole-superconductors. Several families of cuprates show a nearly constant n(h) at maximum T(c). Besides this universality, the cuprates exhibit a number of striking common features. Based on Cu(2p) photoemission studies, it is found that the Cu-O charge-transfer energy, DELTA, and the Cu(3d)-O(2p) hybridization strength, t(pd), are key factors in the superconductivity of cuprates. The relative intensity of the satellite in the Cu(2p) core-level spectra, the polarizability of the CuO2 sheets as well as the hole concentration are related to DELTA/t(pd). These chemical bonding factors have to be explicitly taken into account in any model for superconductivity of the cuprates.

Studies on reactivation of regressing bonnet monkey corpus luteum on day 1 of menses: A pilot study

Studies on functional characteristics of the regressing primate corpus luteum (CL) to luteotrophic stimulus on day 1 of the non-fertile menstrual cycle are scarce. Recombinant human luteinizing hormone (rhLH) (20 IU/Kg BW; n = 10) or human chorionic gonadotropin (hCG) (180 IU; n = 6) were administered intravenously to female bonnet monkeys on day 1 of menses. Exogenous treatment of rhLH or hCG caused a significant increase in circulating progesterone (P4) levels 2-4 hours post treatment (P < 0.05). Lutectomy prior to onset of menses confirmed that CL is the site of the increased P4 concentrations. Increased levels of phosphorylated P44/42 MAPK, MKK3/6 activation and concomitant histological changes were observed within 4 hours in CL of monkeys receiving hCG treatment. The results from this study demonstrate the acute progesterone synthesizing capacity of regressing monkey CL after LH or hCG challenge. This has potential implications for interpreting the steroidogenic response after gonadotropin stimulation tests in the early follicular phase of the normal ovulatory and anovulatory women undergoing controlled ovarian stimulation protocols as part of assisted reproductive technology (ART) and in women with polycystic ovarian syndrome.