• Convergence Security Journal
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• v.14 no.6_2
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• pp.45-52
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• 2014

Up to now, the security system in Korea has been developed from the human security system to more efficient mechanical security system. The mechanical security system has its advantages over the human security system in terms of economy and operation. However, as there are weaknesses in the use of mechanical security equipment such as erroneous alarm sounds, the studies have been done to improve them. This paper tries to suggest how to improve the mechanical security system based on the results of the study on the weakness of the mechanical security obtained through AHP technique.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.399-404
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• 2020

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.

• Convergence Security Journal
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• v.12 no.5
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• pp.71-77
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• 2012

Expenses in the form of personnel expenses in the past, in modern times, machine guards to gradually transition has been. This is because the machine guard is more efficient than personnel expenses. But due to false alarms, despite the high expectations of the effects of electronic security in the operation of the electronic security system due to factors that hinder the development of machine guards growth slows. Defect removal aspects of this paper, using IPA (Importance Performance Analysis) techniques to study the operation of electronic security systems and its importance in the development of machine guards, look at how high the technical aspects of electronic security systems composite type of malfunction to minimize crime sensor are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.305-325
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• 2014

In cloud computing infrastructure, current virtual machine trust measurement methods have many shortcomings in dynamism, security and concurrency. In this paper, we present a new method to measure the trust of virtual machine. Firstly, we propose "behavior trace" to describe the state of virtual machine. Behavior trace is a sequence of behaviors. The measurement of behavior trace is conducted on the basis of anticipated trusted behavior, which not only ensures security of the virtual machine during runtime stage but also reduces complexity of the trust measurement. Based on the behavior trace, we present a Dynamic Tree Style Trust Measurement Model (DTSTM). In this model, the measurement of system domain and user domain is separated, which enhances the extensibility, security and concurrency of the measurement. Finally, based on System Call Interceptor (SCI) and Virtual Machine Introspection (VMI) technology, we implement a DTSTM prototype system for virtual machine trust measurement. Experimental results demonstrate that the system can effectively verify the trust of virtual machine and requires a relatively low performance overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.498-514
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• 2012

Machine to machine (M2M) communications is the hottest issue in the standardization and industry area, it is also defined as machine-type communication (MTC) in release 10 of the 3rd Generation Partnership Project (3GPP). Recently, most research have focused on congestion control, sensing, computing, and controlling technologies and resource management etc., but there are few studies on security aspects. In this paper, we first introduce the threats that exist in M2M system and corresponding solutions according to 3GPP. In addition, we present several new security issues including group access authentication, multiparty authentication and data authentication, and propose corresponding solutions through modifying existing authentication protocols and cryptographic algorithms, such as group authentication and key agreement protocol used to solve group access authentication of M2M, proxy signature for M2M system to tackle authentication issue among multiple entities and aggregate signature used to resolve security of small data transmission in M2M communications.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1396-1405
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• 2020

Cyber threats such as forced personal information collection and distribution of malicious codes using malicious URLs continue to occur. In order to cope with such cyber threats, a security technologies that quickly detects malicious URLs and prevents damage are required. In a web environment, malicious URLs have various forms and are created and deleted from time to time, so there is a limit to the response as a method of detecting or filtering by signature matching. Recently, researches on detecting and predicting malicious URLs using machine learning techniques have been actively conducted. Existing studies have proposed various features and machine learning algorithms for predicting malicious URLs, but most of them are only suggesting specialized algorithms by supplementing features and preprocessing, so it is difficult to sufficiently reflect the strengths of various machine learning algorithms. In this paper, a system for predicting malicious URLs using multiple machine learning algorithms was proposed, and an experiment was performed to combine the prediction results of multiple machine learning models to increase the accuracy of predicting malicious URLs. Through experiments, it was proved that the combination of multiple models is useful in improving the prediction performance compared to a single model.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.83-92
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• 2020

The current technology drain at small and medium-sized enterprises in Korea is very serious. According to the National Intelligence Service's survey data, 69 percent of technology leaks are made through employees of small and medium-sized enterprises. A document security system was introduced to compensate for the problem. However, small and medium-sized enterprises are not doing well due to their poor environment. Therefore, it proposes a document security system suitable for small businesses by developing a location information machine learning system that automatically creates a document security Green Zone through learning, and an ECM-based electronic document leakage prevention system that manages generated Green Zone information by reflecting it into the document authority system. And step by step, propose a universal solution through cloud services..

• Journal of the Korea Convergence Society
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• v.1 no.1
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• pp.49-55
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• 2010

As the developing of the information communication technology, more and more devices are with the capacity of communication and networking. The convergence businesses which communicate with the devices have been developing rapidly. The IT convergence communication is viewed as one of the next frontiers in wireless communications. In this paper, we analyze detailed security threats against M2M(Machine to Machine), intelligent vehicle, smart grid and u-Healthcare in IT convergence architecture. We proposed a direction of the IT convergence security that imbedded system security, forensic security, user authentication and key management scheme.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.707-712
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• 2017

As the amount of data increases exponentially, the recommender system is attracting interest in various industries such as movies, books, and music, and is being studied. The recommendation system aims to propose an appropriate item to the user based on the user's past preference and click stream. Typical examples include Netflix's movie recommendation system and Amazon's book recommendation system. Previous studies can be categorized into three types: collaborative filtering, content-based recommendation, and hybrid recommendation. However, existing recommendation systems have disadvantages such as sparsity, cold start, and scalability problems. To improve these shortcomings and to develop a more accurate recommendation system, we have designed a recommendation system as a factorization machine using actual online product purchase data.