TY - GEN
T1 - A Centralized System for Detecting Attacks from Windows Event Logs
AU - Visoottiviseth, Vasaka
AU - Moonkhaen, Vatcharanun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Although Microsoft released Windows 10 and 11, many personal computers worldwide are still running the old Windows 7 version without installing security patches. This leads attackers to be able to exploit them. In this paper, we propose a lightweight system called SHIRO to detect Windows attacks from the Windows event logs. It aims to detect attacks on Windows 7 clients by focusing on three most critical Common Vulnerabilities Exposures (CVEs), which are CVE 2017-0143 (EternalBlue), CVE 2017-0199 (HTA), and CVE 2019-0708 (BlueKeep). To validate our proposed system, we emulate various attacks and generate datasets on each attack type. Then the log server collects Windows event logs from each client. We identify attacks by comparing logs obtained during attacks and logs obtained during normal operations. Then we develop detection signatures for each CVE from specific event IDs. Once SHIRO finds the attack signatures in the records, it identifies the attack type and alerts to the administrator. Our experiments based on both pre-generated datasets and the real-time attacks confirm that SHIRO can detect three types of attacks accurately. The experiment results prove that SHIRO is useful for the administrator to find the compromised Windows machines efficiently.
AB - Although Microsoft released Windows 10 and 11, many personal computers worldwide are still running the old Windows 7 version without installing security patches. This leads attackers to be able to exploit them. In this paper, we propose a lightweight system called SHIRO to detect Windows attacks from the Windows event logs. It aims to detect attacks on Windows 7 clients by focusing on three most critical Common Vulnerabilities Exposures (CVEs), which are CVE 2017-0143 (EternalBlue), CVE 2017-0199 (HTA), and CVE 2019-0708 (BlueKeep). To validate our proposed system, we emulate various attacks and generate datasets on each attack type. Then the log server collects Windows event logs from each client. We identify attacks by comparing logs obtained during attacks and logs obtained during normal operations. Then we develop detection signatures for each CVE from specific event IDs. Once SHIRO finds the attack signatures in the records, it identifies the attack type and alerts to the administrator. Our experiments based on both pre-generated datasets and the real-time attacks confirm that SHIRO can detect three types of attacks accurately. The experiment results prove that SHIRO is useful for the administrator to find the compromised Windows machines efficiently.
KW - Anomaly Detection
KW - Centralized Log System
KW - Cybersecurity
KW - Windows Event Log
UR - https://www.scopus.com/pages/publications/85162974509
U2 - 10.1109/iEECON56657.2023.10126899
DO - 10.1109/iEECON56657.2023.10126899
M3 - Conference contribution
AN - SCOPUS:85162974509
T3 - Proceeding - 2023 International Electrical Engineering Congress, iEECON 2023
SP - 367
EP - 371
BT - Proceeding - 2023 International Electrical Engineering Congress, iEECON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Electrical Engineering Congress, iEECON 2023
Y2 - 8 March 2023 through 10 March 2023
ER -