• Geophysics and Geophysical Exploration
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• v.21 no.4
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• pp.244-254
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• 2018

The first geophysical technique applied to the agricultural sector in Korea was electrical resistivity sounding and conducted in purpose of groundwater exploitation in the 1970s. According to the diversity of agricultural activities since the 1990s, various geophysical methods including electrical resistivity, electromagnetic induction, and self-potential method were applied to several agricultural fields such as soil characterization with saline concentration in vast reclaimed area, delineation of seawater intrusion regions in costal aquifer, safety inspection of embankment dikes with leakage problem, detection of ground subsidence from overpumping and tracing of groundwater aquifer contamination by leachate from livestock mortality burial or waste burial site. This paper introduces representative geophysical techniques that have been utilized in various agricultural fields and suggests several ways to develop the geophysical methods required for the precision agriculture field in the near future based on the past achievements.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.131-138
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• 2003

With the Internet winning a huge popularity, there rise urgent problems which are related to Network Security Managements such as Protecting Network and Communication from un-authorized user. Accordingly, Using Security equipments have been common lately such as Intrusion Detection Systems, Firewalls and VPNs. Those systems. however, operate in individual system which are independent to me another. Their usage are so limited according to their vendors that they can not provide a corporate Security Solution. In this paper, we present a Hierarchical Security Management Model which can be applicable to a Network Security Policies consistently. We also propose a Policy Negotiation Mechanism and a Prototype which help us to manage Security Policies and Negotiations easier. The results of this research also can be one of the useful guides to developing a Security Policy Server or Security Techniques which can be useful in different environments. This study also shows that it is also possible to improve a Security Characteristics as a whole network and also to support Policy Associations among hosts using our mechanisms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.27-37
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• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Convergence Security Journal
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• v.20 no.4
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• pp.81-90
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• 2020

In the real world, new types of attacks or variants are constantly emerging, but attack traffic classification models developed through artificial neural networks and supervised learning do not properly detect new types of attacks that have not been trained. Most of the previous studies overlooked this problem and focused only on improving the structure of their artificial neural networks. As a result, a number of new attacks were frequently classified as normal traffic, and attack traffic classification performance was severly degraded. On the other hand, the softmax function, which outputs the probability that each class is correctly classified in the multi-class classification as a result, also has a significant impact on the classification performance because it fails to calculate the softmax score properly for a new type of attack traffic that has not been trained. In this paper, based on this characteristic of softmax function, we propose an efficient method to improve the classification performance against new types of attacks by classifying traffic with a probability below a certain level as attacks, and demonstrate the efficiency of our approach through experiments.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.97-105
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• 2022

This paper explains trends in security technologies for ICS. Since ICS is usually applied to large-scale national main infrastructures and industry fields, minor errors caused by cyberattack could generate enormous economic cost. ICS has different characteristic with commonly used IT systems, so considering security threats of ICS separately with IT is needed for developing modern security technology. This paper introduce framework for ICS that analyzes recent cyberattack tactics & techniques and find out trends in Intrusion Detection System (IDS) which is representative technology for ICS security, and analyzes AI technologies used for IDS. Specifically, this paper explains data collection and analysis for applying AI techniques, AI models, techniques for evaluating AI Model.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• Convergence Security Journal
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• v.22 no.2
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• pp.9-19
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• 2022

As the expansion of digital transformation, we are more exposed to the threat of cyber attacks, and many institution or company is operating a signature-based intrusion prevention system at the forefront of the network to prevent the inflow of attacks. However, in order to provide appropriate services to the related ICT system, strict blocking rules cannot be applied, causing many false events and lowering operational efficiency. Therefore, many research projects using artificial intelligence are being performed to improve attack detection accuracy. Most researches were performed using a specific research data set which cannot be seen in real network, so it was impossible to use in the actual system. In this paper, we propose a technique for classifying major attack keywords in the security event log collected from the actual system, assigning a weight to each key keyword, and then performing a similarity check using TF-IDF to determine whether an actual attack has occurred.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.303-314
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• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• The Journal of Engineering Geology
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• v.7 no.2
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• pp.113-126
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• 1997

Electrical resistivity methods of dipole - dipole array profiling and Schiumberger array sounding were tested on a segment of the Woraksan granitic batholith for the research into the imaging of irregular attitudes of fracture zones in the crystaaline rock in terms of processing and interpretation schemes. By the dipole - dipole array method, inhomogeneities such as small scale of fracture zones were properly delineated down at some depth even within hard rock environment. Fracture zones were interpreted to be at the boundaries between the high amplitude zone and very low amplitude zone in the resistivity plot and they were also successfully outlined in two - dimensional layer and pseudo - three - dimensional volume constructed by the incorporation of vertical sounding data. The surface location of the fracture zones was correlated by the zero - crossing point in the VLF(very low frequency) electromagnetic data. Pseudo - three - dimensional attitudes of fracture zones were efficiently illuminated by optimum projection angle. The mean of bulk resistivity for the Woraksan granite and the near fracture zones is estimated to be approximately of 4,000 ohm - m which is much higher than the value of 700 ohm - m for the Rwachunri limesilicate environment. This difference is due to both the rock type, i.e., biotite granite vs limesilicate, and the occurrence of secondary openings of fold and fault associated with the intrusion of granite. In this study statistical analyses on the resistivity color plot were performed in terms of three representative statistical moments, i.e., standard deviation, skewness, and kurtosis. The fracture zones in the standard deviation plot were characterized by the higher value, compared to the value of homogeneous portion. The upper boundary of the high resistivity zone was also successfully delineated in the skewness and kurtosis plots.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1438-1449
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• 2011

UWSNs(Underwater Wireless Sensor Networks) need effective modeling fitted to the customized type of application and its covering area. In particular it requires an energy efficient data aggregation method for such customized application. In this paper, we envisage the application oriented model for monitoring the pollution or intrusion detection over a given underwater area. The suggested model is based on the honeycomb array of hexagonal prisms. In this model, the purpose of data aggregation is that the head node of each layer(cluster) receives just one event data arrived firstly and transfer this and its position data to the base station effectively in the manner of energy efficiency and simplicity without duplication. Here if we apply the existent data aggregation methods to this kind of application, the result is far from energy efficiency due to the complexity of the data aggregation process based on the shortest path or multicast tree. In this paper we propose three energy efficient and simple data aggregation methods in the domain of cluster and three in the domain of inter-cluster respectively. Based on the comparative performance analysis of the possible combination pairs in the two domains, we derive the best energy efficient data aggregation method for the suggested application.