[1]薛见新, 王星凯, 张润滋, 等. 基于异构属性图的自动化攻击行为语义识别方法[J]. 信息安全研究, 2022, 8(3): 292300[2]He P, Zhu J, Zheng Z, et al. Drain: An online log parsing approach with fixed depth tree[C] Proc of IEEE Int Conf on Web Services. New York: IEEE, 2017: 3340[3]吴其, 黄小红, 马严, 等. 复合型日志的模板提取方法[J]. 浙江大学学报: 工学版, 2020, 54(8): 15571561[4]Du M, Li F. Spell: Streaming parsing of system event logs[C] Proc of IEEE International Conf on Data Mining. New York: IEEE, 2016: 859864[5]Xu W, Huang L, Fox A, et al. Detecting largescale system problems by mining console logs[C] Proc of IEEE International Conf on Machine Learning. New York: IEEE, 2009: 117132[6]Makanju A A O, ZincirHeywood A N, Milios E E. Clustering event logs using iterative partitioning[C] Proc of ACM SIGKDD Int Conf on Knowledge Discovery and Data Mining. New York: ACM, 2009: 12551264[7]Mizutani M. Incremental mining of system log format[C] Proc of IEEE Int Conf on Services Computing. New York: IEEE, 2013: 595602[8]He P, Zhu J, He S, et al. Towards automated log parsing for largescale log data analysis[J]. IEEE Trans on Dependable and Secure Computing, 2017, 15(6): 931944[9]Shima K. Length Matters: Clustering system log messages using length of words[EBOL]. 2023 [20161110]. https:arxiv.orgabs1611.03213[10]Zhu J, He S, Liu J, et al. Tools and benchmarks for automated log parsing[C] Proc of IEEE Int Conf on Software Engineering: Software Engineering in Practice. New York: IEEE, 2019: 121130
|