• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.401-410
• /
• 2021

Recently, as cyber attacks targeting industrial control systems increase, various studies are being conducted on the detection of abnormalities in industrial processes. Considering that the industrial process is deterministic and regular, It is appropriate to determine abnormality by comparing the predicted value of the detection model from which normal data is trained and the actual value. In this paper, HAI Datasets 20.07 and 21.03 are used. In addition, an ensemble model is created by combining models that have applied different time steps to Gated Recurrent Units. Then, the detection performance of the single model and the ensemble recurrent neural networks model were compared through various performance evaluation analysis, and It was confirmed that the proposed model is more suitable for abnormal detection in industrial control systems.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.4
• /
• pp.691-708
• /
• 2022

As the technology of machine learning and deep learning became common, it began to be applied to research on anomaly(abnormal) detection of industrial control systems. In Korea, the HAI dataset was developed and published to activate artificial intelligence research for abnormal detection of industrial control systems, and an AI contest for detecting industrial control system security threats is being conducted. Most of the anomaly detection studies have been to create a learning model with improved performance through the ensemble model method, which is applied either by modifying the existing deep learning algorithm or by applying it together with other algorithms. In this study, a study was conducted to improve the performance of anomaly detection with a post-processing method that detects abnormal data and corrects the labeling results, rather than the learning algorithm and data pre-processing process. Results It was confirmed that the results were improved by about 10% or more compared to the anomaly detection performance of the existing model.

• Journal of Information Technology Services
• /
• v.21 no.5
• /
• pp.65-79
• /
• 2022

The smart factory has spread to small and mid-size enterprises (SMEs) under the leadership of the government. Smart factory consists of a work area, an operation management area, and an industrial control system (ICS) area. However, each site is combined with the IT system for reasons such as the convenience of work. As a result, various breaches could occur due to the weakness of the IT system. This study seeks to discover the items and vulnerabilities that SMEs who have difficulties in information security due to technology limitations, human resources, and budget should first diagnose and check. First, to compare the existing domestic and foreign smart factory vulnerability classification systems and improve the current classification system, the latest smart factory vulnerability information is collected from NVD, CISA, and OWASP. Then, significant keywords are extracted from pre-processing, co-occurrence network analysis is performed, and the relationship between each keyword and vulnerability is discovered. Finally, the improvement points of the classification system are derived by mapping it to the existing classification system. Therefore, configuration and maintenance, communication and network, and software development were the items to be diagnosed and checked first, and vulnerabilities were denial of service (DoS), lack of integrity checking for communications, inadequate authentication, privileges, and access control in software in descending order of importance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.774-777
• /
• 2011

산업제어시스템(ICS: Industrial Control System)은 전력 생산, 댐 운영, 가스 생산, 수자원 관리, 원자력 발전 설비 등의 운영을 제어하고 관리하는 시스템이다. 대부분의 국가 기반 시설은 이러한 제어시스템에 의해 관리되고 있으며, 정보통신 기술이 발전하면서 업무망과 제어시스템망을 나누워 구축하며 점차 개방화되어 가고 있다. 이로 인한 IT측면에서 발생하는 사이버 공격이 비교적 폐쇄적인 제어 시스템 망으로 언제든지 이루어질 수 있으며, 실제 국내에서 독립적인 네트워크를 사용함에도 불구하고 금융권의 전산망이 마비되는 사태가 발생하였다. 또한 국외에서는 이란의 원자력 발전소 제어 시스템을 목적으로 하는 'Stuxnet' 악성코드로 인해 발전소 운용이 중단돼는 사례도 발생하였다. 산업용 시스템의 목적과 특성상 사이버 침해사고 발생 시 국가적 손실 및 생명에도 위협을 받을 수 있다. 본 논문은 과거에 보안을 고려하지 않고 구축되었던 제어시스템을 사이버 침해로부터 보호하기 위해 제어시스템을 위한 통신 프로토콜 암호화 및 화이트리스트보안 기술을 이용한 시스템 적용 방안을 소개하며, 네트워크 접속시 인가된 산업용 PC의 안전성을 평가하기 위해 요구되는 보안 플렛폼 설계를 한다.

• Journal of Korean Society of Disaster and Security
• /
• v.6 no.1
• /
• pp.47-53
• /
• 2013

Standard Incident Command System in Korea is that Incident Command System for Emergency Rescue Operation, which is commanded only by Fire Fighting Agencies. However, in the event of a disaster such as the flood, storm, or landslide disaster, there are many disaster response activities performed by the General Public Officers at the disaster on-scene. Yet, there isn't an Natural Disaster Command System for the General Public Officers in Korea. Thus, we have studied the response activities needed cooperation among agencies and proposed some considerations of the Natural Disaster Command System for General Public Officers. The system will be useful to response and recover disaster rapidly, seamlessly, and cooperatively among General Public Officers and the related agencies.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.6
• /
• pp.1351-1364
• /
• 2019

When SCADA is exposed to cyber threats and attacks, serious disasters can occur throughout society. This is because various security threats have not been considered when building SCADA. The bigger problem is that it is difficult to patch vulnerabilities quickly because of its availability. Digital forensics procedures and techniques need to be used to analyze and investigate vulnerabilities in SCADA systems in order to respond quickly against cyber threats and to prevent incidents. This paper addresses SCADA forensics taxonomy and research trends for effective digital forensics investigation on SCADA system. As a result, we have not been able to find any research that goes far beyond traditional digital forensics on procedures and methodologies. But it is meaningful to develop an approach methodology using the characteristics of the SCADA system, or an exclusive tool for SCADA. Analysis techniques mainly focused on PLC and SCADA network protocol. It is because the cyber threats and attacks targeting SCADA are mostly related to PLC or network protocol. Such research seems to continue in the future. Unfortunately, there is lack of discussion about the 'Evidence Capability' such as the preservation or integrity of the evidence extracting from SCADA system in the past researches.

• Journal of Software Assessment and Valuation
• /
• v.16 no.1
• /
• pp.65-79
• /
• 2020

As Programmable Logic Controllers (PLCs), popular components in industrial control systems (ICS), are incorporated with the technologies such as micro-controllers, real-time operating systems, and communication capabilities. As the latest PLCs have been connected to the Internet, they are becoming a main target of cyber threats. This paper proposes two sanitizers that improve the security of uC/OS-II based firmware for a PLC. That is, we devise BU sanitizer for detecting out-of-bounds accesses to buffers and UaF sanitizer for fixing use-after-free bugs in the firmware. They can sanitize the binary firmware image generated in a desktop PC before downloading it to the PLC. The BU sanitizer can also detect the violation of control flow integrity using both call graph and symbols of functions in the firmware image. We have implemented the proposed two sanitizers as a prototype system on a PLC running uC/OS-II and demonstrated the effectiveness of them by performing experiments as well as comparing them with the existing sanitizers. These findings can be used to detect and mitigate unintended vulnerabilities during the firmware development phase.