Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, ...Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.展开更多
Based on multiple proxies from the Southern Hemisphere, an austral summer (December-January-February: DJF) Antarctic Oscillation Index (AAO) since 1500 A.D. was reconstructed with a focus on interannual to interdecada...Based on multiple proxies from the Southern Hemisphere, an austral summer (December-January-February: DJF) Antarctic Oscillation Index (AAO) since 1500 A.D. was reconstructed with a focus on interannual to interdecadal variability (<50 a). By applying a multivariate regression method, the observational AAO-proxy relations were calibrated and cross-validated for the period of 1957 89. The regressions were employed to compute the DJF-AAO index for 1500 1956. To verify the results, the authors checked the explained variance (r 2 ), the reduction of error (RE), and the standard error (SE). Cross-validation was performed by applying a leave-one-out validation method. Over the entire reconstruction period, the mean values of r 2 , RE, and SE are 59.9%, 0.47, and 0.67, respectively. These statistics indicate that the DJF-AAO reconstruction is relatively skillful and reliable for the last ～460 years. The reconstructed AAO variations on the interannual and interdecadal timescales compare favorably with those of several shorter sea level pressure (SLP)-based AAO indices. The leading periods of the DJF-AAO index over the last 500 years are ～2.4, ～2.6, ～6.3, ～24.1, and ～37.6 years, all of which are significant at the 95% level as estimated by power spectral analysis.展开更多
基金supported by the Sharing and Diffusion of National R&D Outcome funded by the Korea Institute of Science and Technology Information
文摘Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.
基金supported by the National Natural Science Foundation of China (Grant No. 40675035)the National High Technology Research and Development Program of China (Grant No. 2008AA121704)the National Key Technologies R&D Program of China (Grant No. 2009BAC51B05)
文摘Based on multiple proxies from the Southern Hemisphere, an austral summer (December-January-February: DJF) Antarctic Oscillation Index (AAO) since 1500 A.D. was reconstructed with a focus on interannual to interdecadal variability (<50 a). By applying a multivariate regression method, the observational AAO-proxy relations were calibrated and cross-validated for the period of 1957 89. The regressions were employed to compute the DJF-AAO index for 1500 1956. To verify the results, the authors checked the explained variance (r 2 ), the reduction of error (RE), and the standard error (SE). Cross-validation was performed by applying a leave-one-out validation method. Over the entire reconstruction period, the mean values of r 2 , RE, and SE are 59.9%, 0.47, and 0.67, respectively. These statistics indicate that the DJF-AAO reconstruction is relatively skillful and reliable for the last ～460 years. The reconstructed AAO variations on the interannual and interdecadal timescales compare favorably with those of several shorter sea level pressure (SLP)-based AAO indices. The leading periods of the DJF-AAO index over the last 500 years are ～2.4, ～2.6, ～6.3, ～24.1, and ～37.6 years, all of which are significant at the 95% level as estimated by power spectral analysis.
