• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2827-2848
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• 2021

Mobile Crowdsourcing (MCS) has become an emerging paradigm evolved from crowdsourcing by employing advanced features of mobile devices such as smartphones to perform more complicated, especially spatial tasks. One of the key procedures in MCS is to collect answers from mobile users (workers), which may face several security issues. First, authentication is required to ensure that answers are from authorized workers. In addition, MCS tasks are usually location-dependent, so the collected answers could disclose workers' location privacy, which may discourage workers to participate in the tasks. Finally, the overhead occurred by authentication and privacy protection should be minimized since mobile devices are resource-constrained. Considering all the above concerns, in this paper, we propose a lightweight and privacy-preserving answer collection scheme for MCS. In the proposed scheme, we achieve anonymous authentication based on traceable ring signature, which provides authentication, anonymity, as well as traceability by enabling malicious workers tracing. In order to balance user location privacy and data availability, we propose a new concept named current location privacy, which means the location of the worker cannot be disclosed to anyone until a specified time. Since the leakage of current location will seriously threaten workers' personal safety, causing such as absence or presence disclosure attacks, it is necessary to pay attention to the current location privacy of workers in MCS. We encrypt the collected answers based on timed-release encryption, ensuring the secure transmission and high availability of data, as well as preserving the current location privacy of workers. Finally, we analyze the security and performance of the proposed scheme. The experimental results show that the computation costs of a worker depend on the number of ring signature members, which indicates the flexibility for a worker to choose an appropriate size of the group under considerations of privacy and efficiency.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.119-124
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• 2021

Today, both sides of modern culture are decisively invaded by digitalization. Authentication is considered to be one of the main components in keeping this process secure. Cyber criminals are working hard in penetrating through the existing network channels to encounter malicious attacks. When it comes to enterprises, the company's information is a major asset. Question here arises is how to protect the vital information. This takes into account various aspects of a society often termed as hyper connected society including online communication, purchases, regulation of access rights and many more. In this research paper, we will discuss about the concepts of MFA and KBA, i.e., Multi-Factor Authentication and Knowledge Based Authentication. The purpose of MFA and KBA its utilization for human.to.everything..interactions, offering easy to be used and secured validation mechanism while having access to the service. In the research, we will also explore the existing yet evolving factor providers (sensors) used for authenticating a user. This is an important tool to protect data from malicious insiders and outsiders. Access Management main goal is to provide authorized users the right to use a service also preventing access to illegal users. Multiple techniques can be implemented to ensure access management. In this paper, we will discuss various techniques to ensure access management suitable for enterprises, primarily focusing/restricting our discussion to multifactor authentication. We will also highlight the role of knowledge-based authentication in multi factor authentication and how it can make enterprises data more secure from Cyber Attack. Lastly, we will also discuss about the future of MFA and KBA.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1539-1552
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• 2018

The necessity of establishing a more secure cyber security system is emerging to protect NPP against cyber attacks as nuclear facilities become increasingly reliant on digital system. Proper security measures should be established through periodic analysis and evaluation of vulnerabilities. However, as Nuclear facilities has safety characteristics as their top priority and it requires a lot of time and cost to construct regarding the activities for vulnerability analysis, it is difficult to apply the existing vulnerability analysis environment and analysis tools. In this study, We propose a analytical vulnerability assessment method to overcome the limitations of existing vulnerability analysis methods through analysis the existing vulnerability analysis methods and the issues to be considered when applying the vulnerability analysis method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.67-74
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• 2011

In this paper, we presented a dynamic cyber attack tree which can describe an attack scenario flexibly for an active cyber attack model could be detected complex and transformed attack method. An attack tree provides a formal and methodical route of describing the security safeguard on varying attacks against network system. The existent attack tree can describe attack scenario as using vertex, edge and composition. But an attack tree has the limitations to express complex and new attack due to the restriction of attack tree's attributes. We solved the limitations of the existent attack tree as adding an threat occurrence probability and 2 components of composition in the attributes. Firstly, we improved the flexibility to describe complex and transformed attack method, and reduced the ambiguity of attack sequence, as reinforcing composition. And we can identify the risk level of attack at each attack phase from child node to parent node as adding an threat occurrence probability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.582-590
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• 2022

As security threats caused by cyber attacks continue, security control is mainly operated in the form of a service business with expertise for rapid detection and response. Accordingly, a number of studies have been conducted on the operation of security control services. However, due to the research on the resulting management, indicators, and measurements, the work process has not been studied in detail, causing confusion in the field, making it difficult to respond to security accidents. This paper presents ISMS-P-based service management methods and proposes an easy outsourcing service management method for client by checklisting each item derived from the mapping of 64 items of ISMS-P protection requirements through business relevance analysis. In addition, it is expected to help implement periodic security compliance and acquire and renew ISMS-P in the mid- to long-term, and to contribute to enhancing security awareness of related personnel.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.135-140
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• 2022

Scientific and technological progress is also fundamental to the evolving merchant shipping industry, both in terms of the size and speed of modern ships and in the level of their technical capabilities. While the freight performance of ships is growing, the number of crew on board is steadily decreasing, as more work processes are being automated through the implementation of information technologies, including ship management systems. Although there have been repeated appeals from international maritime organizations to focus on building effective maritime security defenses against cyber attacks, the problems have remained unresolved. Owners of shipping companies do not disclose information about cyberattack attempts or incidents against them due to fear of commercial losses or consequences, such as loss of image, customer and insurance claims, and investigations by independent international organizations and government agencies. Issues of cybersecurity of control systems in the world today have gained importance, due to the fact that existing threats concern not only the security of technical means and devices, but also issues of environmental safety and safety of life at sea. The article examines the implementation of cyber risk management in the shipping industry, providing recommendations for the safe ship operation and its systems in order to improve vulnerability to external threats related to cyberattacks, and to ensure the safety and security of such a technical object as a seagoing ship.

• Convergence Security Journal
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• v.23 no.5
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• pp.65-72
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• 2023

This paper proposes a method for detecting malicious domains considering human habitual characteristics by building a Deep Learning model based on LSTM (Long Short-Term Memory). DGA (Domain Generation Algorithm) malicious domains exploit human habitual errors, resulting in severe security threats. The objective is to swiftly and accurately respond to changes in malicious domains and their evasion techniques through typosquatting to minimize security threats. The LSTM-based Deep Learning model automatically analyzes and categorizes generated domains as malicious or benign based on malware-specific features. As a result of evaluating the model's performance based on ROC curve and AUC accuracy, it demonstrated 99.21% superior detection accuracy. Not only can this model detect malicious domains in real-time, but it also holds potential applications across various cyber security domains. This paper proposes and explores a novel approach aimed at safeguarding users and fostering a secure cyber environment against cyber attacks.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.618-628
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• 2020

The purpose of this paper is to propose a new security orchestration service model by combining various security solutions that have been introduced and operated individually as a basis for cyber security framework. At present, in order to respond to various and intelligent cyber attacks, various single security devices and SIEM and AI solutions that integrate and manage them have been built. In addition, a cyber security framework and a security control center were opened for systematic prevention and response. However, due to the document-oriented cybersecurity framework and limited security personnel, the reality is that it is difficult to escape from the control form of fragmentary infringement response of important detection events of TMS / IPS. To improve these problems, based on the model of this paper, select the targets to be protected through work characteristics and vulnerable asset identification, and then collect logs with SIEM. Based on asset information, we established proactive methods and three detection strategies through threat information. AI and SIEM are used to quickly determine whether an attack has occurred, and an automatic blocking function is linked to the firewall and IPS. In addition, through the automatic learning of TMS / IPS detection events through machine learning supervised learning, we improved the efficiency of control work and established a threat hunting work system centered on big data analysis through machine learning unsupervised learning results.

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

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.297-301
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• 2013

Key agreement protocols allow multi-parties exchanging public information to create a common secret key that is known only to those entities over an insecure network. Since Joux first published the pairing-based one round tripartite key agreement protocol, many authenticated protocols have been proposed. Unfortunately, many of them have been broken while others have been shown to be deficient in some desirable security attributes. In 2004, Cheng et al. presented two protocols aimed at strengthening Shim's certificate-based and Zhang et al.'s tripartite identity-based protocols. This paper reports that 1) In Cheng et al.'s identity-based protocol, an adversary can extract long-term private keys of all the parties involved; and 2) Cheng et al.'s certification-based protocol is weak against key integrity attacks. This paper suggests possible remedies for the security flaws in both protocols and then presents a modified Cheng et al.'s identity-based, one-round tripartite protocol that is more secure than the original protocol.