• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.3
• /
• pp.429-438
• /
• 2021

The mandatory installation of the ECDIS (Electronic Chart Display and Information System) became an important navigational equipment for navigation officer. In addition, ECDIS is a key component of the ship's digitalization in conjunction with various navigational equipment. Meanwhile, cyber-attacks emerge as a new threat along with digitalization. Damage caused by cyber-attacks is also reported in the shipping sector, and IMO recommends that cybersecurity guidelines be developed and included in International Security Management (ISM). This study analyzed the cybersecurity hazards of ECDIS, where various navigational equipment are connected. To this end, Importance-Performance Analysis (IPA) was conducted on navigation officer using ECDIS. As a result, the development of technologies for cyber-attack detection and prevention should be priority. In addition, policies related to 'Hardware and Software upgrade', 'network access control', and 'data backup and recovery' were analyzed as contents to be maintained. This paper is significant in deriving risk factors from the perspective of ECDIS users and analyzing their priorities, and it is necessary to analyze various cyber-attacks that may occur on ships in the future.

• Convergence Security Journal
• /
• v.16 no.3_2
• /
• pp.33-42
• /
• 2016

While evolving information-oriented society provides a lot of benefits to the human life, new types of threats have been increasing. Particularly, cyber terrorism, happen on the network that is composed of a computer system and information communication network, and the mean and scale of damage has reached a serious level. In other words, it is hard to locate cyber terror since it occurs in the virtual space, not in the real world, so identifying "Who is attacking?" (Non-visibility, non-formulas), or "Where the attack takes place?" (trans-nation) are hard. Hackers, individuals or even a small group of people, who carried out the cyber terror are posing new threats that could intimidate national security and the pace and magnitude of threats keep evolving. Scale and capability of North Korea's cyber terrorism are assessed as world-class level. Recently, North Korea is focusing on strengthen their cyber terrorism force. So improving a response system for cyber terror is a key necessity as North Korea's has emerged as a direct threat to South Korean security. Therefore, Korea has to redeem both legal and institutional systems immediately to perform as a unified control tower for preemptive response to cyber terrors arise from North Korea and neighboring countries.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.291-294
• /
• 2017

최근 국내에서 신 변종 공격이 대량으로 발생함에 따라, 한정적인 보안전문 인력과 기존의 장비로 분석 및 대응하는데 어려움이 있다. 본 논문에서는, 대량으로 발생하는 침해사고에 대해 분석 우선순위를 확인하고자, 침해사고에 활용된 침해지표들의 위협을 분석하고 이를 정량적인 값인 침해지표 위협수준(TL_IoC, Threat Level of IoC)로 도출하는 방안을 제안한다. 이를 통해, 침해지표의 위협수준을 직관적으로 확인함으로써 침해사고의 대응수준을 신속하게 판단하고, 위협수준이 높은 침해사고에 대해 능동적으로 빠르게 분석함으로써 대량의 침해사고를 효율적으로 대응할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.3
• /
• pp.428-434
• /
• 2020

Recently, due to the development of ICT technology, changes to the convergence service platform of information systems are accelerating. Convergence services expanded to cyber systems with 5G communication, IoT, AI, and cloud are being reflected in the real world. However, the field of cybersecurity audit for responding to cyber attacks and security threats and strengthening security technology is insufficient. In this paper, we analyze the international standard analysis of information security management system, security audit analysis and security of related systems according to the expansion of 5G communication, IoT, AI, Cloud based information system security. In addition, we design and study cybersecurity audit checklists and contents for expanding security according to cyber attack and security threat of information system. This study will be used as the basic data for audit methods and audit contents for coping with cyber attacks and security threats by expanding convergence services of 5G, IoT, AI, and Cloud based systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.6
• /
• pp.287-294
• /
• 2016

APT attack aimed at the interruption of information and communication facilities and important information leakage of companies. it performs an attack using zero-day vulnerabilities, social engineering base on collected information, such as IT infra, business environment, information of employee, for a long period of time. Fragmentary response to cyber threats such as malware signature detection methods can not respond to sophisticated cyber-attacks, such as APT attacks. In this paper, we propose a cyber intrusion detection model for countermeasure of APT attack by utilizing heterogeneous system log into big-data. And it also utilizes that merging pattern-based detection methods and abnormality detection method.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.177-189
• /
• 2023

Malware detection is an increasingly important operational focus in cyber security, particularly given the fast pace of such threats (e.g., new malware variants introduced every day). There has been great interest in exploring the use of machine learning techniques in automating and enhancing the effectiveness of malware detection and analysis. In this paper, we present a deep recurrent neural network solution as a stacked Long Short-Term Memory (LSTM) with a pre-training as a regularization method to avoid random network initialization. In our proposal, we use global and short dependencies of the inputs. With pre-training, we avoid random initialization and are able to improve the accuracy and robustness of malware threat hunting. The proposed method speeds up the convergence (in comparison to stacked LSTM) by reducing the length of malware OpCode or bytecode sequences. Hence, the complexity of our final method is reduced. This leads to better accuracy, higher Mattews Correlation Coefficients (MCC), and Area Under the Curve (AUC) in comparison to a standard LSTM with similar detection time. Our proposed method can be applied in real-time malware threat hunting, particularly for safety critical systems such as eHealth or Internet of Military of Things where poor convergence of the model could lead to catastrophic consequences. We evaluate the effectiveness of our proposed method on Windows, Ransomware, Internet of Things (IoT), and Android malware datasets using both static and dynamic analysis. For the IoT malware detection, we also present a comparative summary of the performance on an IoT-specific dataset of our proposed method and the standard stacked LSTM method. More specifically, of our proposed method achieves an accuracy of 99.1% in detecting IoT malware samples, with AUC of 0.985, and MCC of 0.95; thus, outperforming standard LSTM based methods in these key metrics.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.4
• /
• pp.15-23
• /
• 2021

In most hacking attacks, hackers intrudes inside for a long period of time and attempts to communicate with the outside using a circumvent connection to achieve purpose. research in response to advanced and intelligent cyber threats has been mainly conducted with signature-based detection and blocking methods, but recently it has been extended to threat hunting methods. attacks from organized hacking groups are advanced persistent attacks over a long period of time, and bypass remote attacks account for the majority. however, even in the intrusion detection system using intelligent recognition technology, it only shows detection performance of the existing intrusion status. therefore, countermeasures against targeted bypass rwjqthrwkemote attacks still have limitations with existing detection methods and threat hunting methods. in this paper, to overcome theses limitations, we propose a model that can detect the targeted circumvent connection remote attack threat of an organized hacking group. this model designed a threat hunting process model that applied the method of verifying the origin IP of the remote circumvent connection, and verified the effectiveness by implementing the proposed method in actual defense information system environment.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.2
• /
• pp.267-280
• /
• 2023

With development of computing and communications technologies, IoT environments based on high-speed networks have been extending rapidly. Especially, from home to an office or a factory, applications of IoT devices with sensing environment and performing computations are increasing. Unfortunately, IoT devices which have limited hardware resources can be vulnerable to cyber attacks. Hence, there is a concern that an IoT botnet can give rise to information leakage as a national cyber security crisis arising from abuse as a malicious waypoint or propagation through connected networks. In order to response in advance from unknown cyber threats in IoT networks, in this paper, We firstly define four types of We firstly define four types of characteristics by analyzing darknet traffic accessed from an IoT botnet. Using the characteristic, a suspicious IP address is filtered quickly. Secondly, the filtered address is identified by Cyber Threat Intelligence (CTI) or Open Source INTelligence (OSINT) in terms of an unknown suspicious host. The identified IP address is finally fingerprinted to determine whether the IP is a malicious host or not. To verify a validation of the proposed method, we apply to a Darknet on real-world SOC. As a result, about 1,000 hosts who are detected and blocked preemptively by the proposed method are confirmed as real IoT botnets.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.187-189
• /
• 2023

IoT(Internet of Things), 빅데이터, AI(Artificial Intelligence), 클라우드와 같은 ICT(Information and Communications Technology) 기술이 발전함에 따라 ICT와 제조기술이 융합된 스마트팩토리가 발전하고 있다. 이는 2개의 영역과 5개의 계층으로 구성되어 기타 환경들과 상이한 구조를 가지고 있으며, 각 영역·계층별 발생 가능한 보안위협도 상이하다. 또한, 각 영역과 계층이 연결됨에 따라 발생 가능한 보안위협이 증가하고 있으며, 이에 대한 효율적인 대응을 위하여 스마트팩토리 영역·계층별 환경을 고려한 대응체계 마련이 필요한 실정이다. 따라서, 본 논문에서는 스마트팩토리 영역·계층별 발생 가능한 보안위협을 분석하고, 이에 대응하기 위한 대응체계 도출 기법을 제안한다.

• Convergence Security Journal
• /
• v.19 no.2
• /
• pp.59-72
• /
• 2019

In this day and age physical and cyber boundaries have converged due to the development of new technologies, such as the Internet of Things (IoT) and the Cyber Physical System (CPS). As the relationship between physical system and cyber technology strengthens, more diverse and complex forms of risk emerge. As a result, it is becoming difficult for single organization or government to fully handle this situation alone and cooperation based on information sharing and the strengthening of active defense systems are needed. Shifting to a system in which information suitable for various entities can be shared and automatically responded to is also necessary. Therefore, this study tries to find improvements for the current system of threat information collecting and sharing that can actively and practically maintain cyber defense posture, focusing particularly on the structuring of information sharing platforms. To achieve our objective, we use a risk communication theory from the safety field and propose a new platform by combining an action-oriented security process model.