Outliers and Missing Gait_Human, IDS, JavaScript vulnerability Datasets

Human Gait Dataset (CASIA-A) [1] is available at: http://www.cbsr.ia.ac.cn/english/Gait\%20Databases.asp, JavaScript vulnerabilitydataset is publicly available at [2] and KDD CUP 99 dataset is publicly available at [3]. [1] Wang L, Tan T, Ning H, Hu W. Silhouette analysis-based gait recognition forhuman identification. IEEE transactions on pattern analysis and machineintelligence. 2003;25(12):1505–1518 [2] Ferenc R, Heged ̋us P, Gyimesi P, Antal G, B ́an D, Gyim ́othy T. Challengingmachine learning algorithms in predicting vulnerable javascript functions. In:2019 IEEE/ACM 7th International Workshop on Realizing Artificial IntelligenceSynergies in Software Engineering (RAISE). IEEE; 2019. p. 8–14. [3] Tavallaee M, Bagheri E, Lu W, Ghorbani AA. A detailed analysis of the KDDCUP 99 data set. In: 2009 IEEE symposium on computational intelligence forsecurity and defense applications. Ieee; 2009. p. 1–6.人类步态数据集（CASIA-A）[1] 的获取地址为：http://www.cbsr.ia.ac.cn/english/Gait%20Databases.asp；JavaScript漏洞数据集可通过文献[2]公开获取，KDD CUP 99数据集可通过文献[3]公开获取。 [1] Wang L, Tan T, Ning H, Hu W. 基于轮廓分析的步态识别用于人员身份识别. IEEE模式分析与机器智能汇刊. 2003;25(12):1505–1518 [2] Ferenc R, Hegedűs P, Gyimesi P, Antal G, Bán D, Gyimóthy T. 面向JavaScript漏洞函数预测的挑战性机器学习算法研究. 收录于：2019年IEEE/ACM第7届人工智能与软件工程协同实现国际研讨会（RAISE）论文集. 电气电子工程师学会; 2019. 第8–14页 [3] Tavallaee M, Bagheri E, Lu W, Ghorbani AA. KDD CUP 99数据集的详细分析. 收录于：2009年IEEE安全与防御应用计算智能研讨会论文集. 电气电子工程师学会; 2009. 第1–6页