DATA-DRIVEN FIELD MAPPING OF SECURITY LOGS FOR INTEGRATED MONITORING

被引:0
|
作者
Choi, Seungoh [1 ]
Kim, Yesol [1 ]
Yun, Jeong-Han [1 ]
Min, Byung-Gil [1 ]
Kim, Hyoung-Chun [1 ]
机构
[1] Affiliated Inst ETRI, Daejeon, South Korea
来源
关键词
Security; event logs; integrated system monitoring;
D O I
10.1007/978-3-030-34647-8_13
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As industrial control system vulnerabilities and attacks increase, security controls must be applied to operational technologies. The growing demand for security threat monitoring and analysis techniques that integrate information from security logs has resulted in enterprise security management systems giving way to security information and event management systems. Nevertheless, it is vital to implement some form of pre-processing to collect, integrate and analyze security events efficiently. Operators still have to manually check entire security logs or write scripts or parsers that draw on domain knowledge, tasks that are time-consuming and error-prone. To address these challenges, this chapter focuses on the data-driven mapping of security logs to support the integrated monitoring of operational technology systems. The characteristics of security logs from security appliances used in critical infrastructure assets are analyzed to create a tool that maps different security logs to field categories to support integrated system monitoring. The tool reduces the effort needed by operators to manually process security logs even when the logged data generated by security appliances has new or modified formats.
引用
收藏
页码:253 / 268
页数:16
相关论文
共 50 条
  • [41] Adversarial Security Verification of Data-Driven FDC Systems
    Zhuo, Yue
    Ge, Zhiqiang
    IEEE TRANSACTIONS ON RELIABILITY, 2023, 72 (04) : 1580 - 1593
  • [42] Data-driven Software Security and its Hardware Support
    Erlingsson, Ulfar
    PROCEEDINGS OF THE 2017 WORKSHOP ON ATTACKS AND SOLUTIONS IN HARDWARE SECURITY (ASHES'17), 2017, : 3 - 3
  • [43] Data-Driven Security Assessment of the Electric Power System
    Meghdadi, Seyedali
    Tack, Guido
    Liebman, Ariel
    2019 9TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS (ICPES), 2019,
  • [44] A Pipeline for Integrated Theory and Data-Driven Modeling of Biomedical Data
    Raghu, Vineet K.
    Ge, Xiaoyu
    Balajiee, Arun
    Shirer, Daniel J.
    Das, Isha
    Benos, Panayiotis, V
    Chrysanthis, Panos K.
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2021, 18 (03) : 811 - 822
  • [45] Data-Driven Business Process Simulation: From Event Logs to Tools and Techniques
    Lopez-Pintado, Orlenys
    Chapela-Campa, David
    ADVANCED INFORMATION SYSTEMS ENGINEERING, CAISE 2024, 2024, 14663 : 631 - 632
  • [46] OLAP on Search Logs: An Infrastructure Supporting Data-Driven Applications in Search Engines
    Zhou, Bin
    Jiang, Daxin
    Pei, Jian
    Li, Hang
    KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2009, : 1395 - 1403
  • [47] INDRNN-BASED DATA-DRIVEN MODELING INTEGRATED WITH PHYSICAL KNOWLEDGE FOR ENGINE PERFORMANCE MONITORING
    Xiao, Dasheng
    Xiao, Hong
    Wang, Zhanxue
    PROCEEDINGS OF ASME TURBO EXPO 2024: TURBOMACHINERY TECHNICAL CONFERENCE AND EXPOSITION, GT2024, VOL 4, 2024,
  • [48] IndRNN-Based Data-Driven Modeling Integrated With Physical Knowledge for Engine Performance Monitoring
    Xiao, Dasheng
    Xiao, Hong
    Wang, Zhanxue
    JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, 2025, 147 (02):
  • [49] A data-driven approach for optimal design of integrated air quality monitoring network in a chemical cluster
    Zhu, Zhengqiu
    Chen, Bin
    Qiu, Sihang
    Wang, Rongxiao
    Wang, Yiping
    Ma, Liang
    Qiu, Xiaogang
    ROYAL SOCIETY OPEN SCIENCE, 2018, 5 (09):
  • [50] Data-Driven Radial Compressor Design Space Mapping
    Brind, J.
    JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 2025, 147 (02):