VQ codebook design using modified K-means algorithm with feature classification and grouping based initialization

Multimedia Tools and Applications - Vector quantization (VQ) has been successfully used in data compression and feature extraction areas. Codebook design is the essential step of VQ. The K-means...     

E-Replacement: Efficient scanner data collection method in P4-based software-defined networks

Internet of things (IoT) botnets such as Mirai are rampant in the past years. Port scanning is a well-known behavior of botnets for searching targets in networks. To detect port scanning, a detector requires network statistics with high discriminatory power. In P4-based software-defined network (SDN), switches take charge of recording characteristics about scanning behaviors, and controllers pull the statistics from the switches periodically for anomaly detection. Given storage resources in switches are limited, we proposed a scanner data collection method, 0-Replacement, in P4-based SDN to efficiently collect scanner data and improve the detection rate. 0-Replacement, however, does not consider performance degradation caused by the hash collision. In this paper, we combine the conception of Hashpipe with 0-Replacement and propose a new scanner data collection method named E-Replacement. By leveraging the conception of Hashpipe, E-Replacement can mitigate the performance degradation caused by the hash collision. Through simulations, we show that E-Replacement improves the detection rate by up to 6.73% and 210.82% compared to 0-Replacement and the traditional sample and hold method, respectively. Besides, E-Replacement improves the precision by around 528.2% compared to the count-min sketch and k-ary sketch methods. The memory usage in E-Replacement is the same as 0-Replacement. In simulations, E-Replacement can detect around 93.4% of scanners in a class B network with only 4.02-Mb SRAM. After implementing E-Replacement on a software P4 switch, BMv2, we observe the extra forwarding latency for E-Replacement is not greater than a millisecond.     

中国被毛孢降解黄曲霉毒素B1的特性研究

目的 分析中国被毛孢（Hirsutella sinensis）8#菌株降解黄曲霉毒素B1 (AFB1)的能力。方法 考察该菌株培养液、菌丝体悬液和上清液去除AFB1的能力;利用洗脱和萃取法区分生物降解和可逆吸附AFB1;研究不同初始AFB1浓度、温度、pH和金属离子对其降解能力的影响;对AFB1降解液进行高效液相色谱和薄层色谱分析。结果 H.sinensis培养液和菌体降解效果显著（P<0.05）,96 h后对初始浓度100 ng/mL的AFB1降解率分别是96.90%±4.39% 和 97.93%±2.92%。磷酸盐缓冲液洗脱液和甲醇萃取液均未检测到AFB1,证实了该菌生物降解AFB1。菌株AFB1降解效果与初始浓度密切相关。当反应温度25 ℃,pH 7.0时,培养液作用72 h后降解率为99.90%±0.18%。同时,反应液中加入Fe2+有利于降解,而Mg2+却起到了抑制作用。高效液相色谱和薄层层析对产物分析表明,该菌株可将AFB1降解为至少为1种产物。结论 中国被毛孢8#菌株对AFB1有良好的降解作用,可用于生物降解真菌毒素的潜力菌株。     

激光敌我识别及进展

介绍了激光敌我识别的最新进展和在战争中的重要作用。讨论了激光敌我识别的原理和存在技术难题。并提出了设计激光敌我识别系统需要考虑的一些问题。