• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.27-47
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• 1992

Engineers have developed new instruments that aid in diagnosis and therapy Ultrasonic imaging has provided a nondamaging method of imaging internal organs. A complex transducer emits ultrasonic waves at many angles and reconstructs a map of internal anatomy and also velocities of blood in vessels. Fast computed tomography permits reconstruction of the 3-dimensional anatomy and perfusion of the heart at 20-Hz rates. Positron emission tomography uses certain isotopes that produce positrons that react with electrons to simultaneously emit two gamma rays in opposite directions. It locates the region of origin by using a ring of discrete scintillation detectors, each in electronic coincidence with an opposing detector. In magnetic resonance imaging, the patient is placed in a very strong magnetic field. The precessing of the hydrogen atoms is perturbed by an interrogating field to yield two-dimensional images of soft tissue having exceptional clarity. As an alternative to radiology image processing, film archiving, and retrieval, picture archiving and communication systems (PACS) are being implemented. Images from computed radiography, magnetic resonance imaging (MRI), nuclear medicine, and ultrasound are digitized, transmitted, and stored in computers for retrieval at distributed work stations. In electrical impedance tomography, electrodes are placed around the thorax. 50-kHz current is injected between two electrodes and voltages are measured on all other electrodes. A computer processes the data to yield an image of the resistivity of a 2-dimensional slice of the thorax. During fetal monitoring, a corkscrew electrode is screwed into the fetal scalp to measure the fetal electrocardiogram. Correlations with uterine contractions yield information on the status of the fetus during delivery To measure cardiac output by thermodilution, cold saline is injected into the right atrium. A thermistor in the right pulmonary artery yields temperature measurements, from which we can calculate cardiac output. In impedance cardiography, we measure the changes in electrical impedance as the heart ejects blood into the arteries. Motion artifacts are large, so signal averaging is useful during monitoring. An intraarterial blood gas monitoring system permits monitoring in real time. Light is sent down optical fibers inserted into the radial artery, where it is absorbed by dyes, which reemit the light at a different wavelength. The emitted light travels up optical fibers where an external instrument determines O2, CO2, and pH. Therapeutic devices include the electrosurgical unit. A high-frequency electric arc is drawn between the knife and the tissue. The arc cuts and the heat coagulates, thus preventing blood loss. Hyperthermia has demonstrated antitumor effects in patients in whom all conventional modes of therapy have failed. Methods of raising tumor temperature include focused ultrasound, radio-frequency power through needles, or microwaves. When the heart stops pumping, we use the defibrillator to restore normal pumping. A brief, high-current pulse through the heart synchronizes all cardiac fibers to restore normal rhythm. When the cardiac rhythm is too slow, we implant the cardiac pacemaker. An electrode within the heart stimulates the cardiac muscle to contract at the normal rate. When the cardiac valves are narrowed or leak, we implant an artificial valve. Silicone rubber and Teflon are used for biocompatibility. Artificial hearts powered by pneumatic hoses have been implanted in humans. However, the quality of life gradually degrades, and death ensues. When kidney stones develop, lithotripsy is used. A spark creates a pressure wave, which is focused on the stone and fragments it. The pieces pass out normally. When kidneys fail, the blood is cleansed during hemodialysis. Urea passes through a porous membrane to a dialysate bath to lower its concentration in the blood. The blind are able to read by scanning the Optacon with their fingertips. A camera scans letters and converts them to an array of vibrating pins. The deaf are able to hear using a cochlear implant. A microphone detects sound and divides it into frequency bands. 22 electrodes within the cochlea stimulate the acoustic the acoustic nerve to provide sound patterns. For those who have lost muscle function in the limbs, researchers are implanting electrodes to stimulate the muscle. Sensors in the legs and arms feed back signals to a computer that coordinates the stimulators to provide limb motion. For those with high spinal cord injury, a puff and sip switch can control a computer and permit the disabled person operate the computer and communicate with the outside world.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.176-188
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• 2018

Modern urban problems are increasingly becoming a market mix that can not be solved by the power of a single department and the necessity of establishing a cooperation system based on data communication between departments is increasing. Therefore, this study analyzed Busan metropolitan city's IT projects from 2014 to 2018 in order to understand the utilization and sharing status of departmental data from the viewpoint that cooperation between departments can start from the sharing of data with high common utilization. In addition, based on the results of the FGI(Focus Group Interview) conducted for the officials of the department responsible for the informatization project, we verified the results of data status analysis. At the same time, we figured out the necessity of data link between departments through SNA(Social Network Analysis) and presented data that should be shared first in the future. As a result, most of the information systems currently use limited data only within the department that produced the data. Most of the linked data was concentrated in the information department. Therefore, this study suggested the following solutions. First, in order to prevent overlapping investments caused by the operation of individual departments and share information, it is necessary to build a small platform to tie the departments, which have high connectivity with each other, into small blocks. Second, a local level process is needed to develop data standards as an extension of national standards in order to expand the information to be used in various fields. Third, as another solution, we proposed a system that can integrate various types of information based on address and location information through application of cloud-based GIS platform. The results of this study are expected to contribute to build a cooperation system between departments through expansion of information sharing with cost reduction.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.122-130
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• 2013

This work proposes a 12b 100MS/s 45nm CMOS four-step pipeline ADC for high-speed digital communication systems requiring high resolution, low power, and small size. The input SHA employs a gate-bootstrapping circuit to sample wide-band input signals with an accuracy of 12 bits or more. The input SHA and MDACs adopt two-stage op-amps with a gain-boosting technique to achieve the required DC gain and high signal swing range. In addition, cascode and Miller frequency-compensation techniques are selectively used for wide bandwidth and stable signal settling. The cascode current mirror minimizes current mismatch by channel length modulation and supply variation. The finger width of current mirrors and amplifiers is laid out in the same size to reduce device mismatch. The proposed supply- and temperature-insensitive current and voltage references are implemented on chip with optional off-chip reference voltages for various system applications. The prototype ADC in a 45nm CMOS demonstrates the measured DNL and INL within 0.88LSB and 1.46LSB, respectively. The ADC shows a maximum SNDR of 61.0dB and a maximum SFDR of 74.9dB at 100MS/s, respectively. The ADC with an active die area of $0.43mm^2$ consumes 29.8mW at 100MS/s and a 1.1V supply.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.5-16
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• 2009

Against the backdrop of the increasing trend towards economic globalisation, many international firms are indicating that decisions on how to enter foreign markets remains one of the key strategic challenges confronting them. Despite the rich body of literature on the topic, the fact that these challenges have continued to dominate global marketing strategy discourses point to someevident lacunae. Accordingly, this paper considers the variables, categorised in terms of firm contexts (standardisation, market research, competition, structure, competitive advantage) and host country-contexts (economic development, cultural differences, regulation and political risk), which influence the degree of involvement of UK companies in overseas markets. Following hypotheses were drawn from literature review: H1: The greater the level of competition, the higher the degree of involvement in the overseas market. H2: The more centralised the firm's organisation structure, the higher the degree of involvement in the overseas market. H3a: The adoption of a low cost-approach to competitive advantage will lead to a higher degree of involvement. H3b: The adoption of an innovation-approach to competitive advantage will lead to a higher degree of involvement. H3c: The adoption of a market research approach to competitive advantages will lead to a higher degree of involvement. H3d: The adoption of a breadth of strategic target-approach to competitive advantage will lead to a lower degree of involvement. H4: The higher the degree of standardisation of the international marketing mix the higher the degree of involvement. H5: The greater the degree of economic development in the host market, the higher the degree of involvement. H6: The greater the cultural differences between home and host countries, the lower the degree of involvement. H7: The greater the difference in regulations between the home country and the host country, the lower the degree of involvement. H8: The higher the political risk in the host country, the lower the degree of involvement. A questionnaire instrument was constructed using, wherever possible, validated measures of the concepts to serve the aims of this study. Following two sets of mailings, 112 usable completed questionnaires were returned. Correlation analysis and multiple regression analysis were used to analyze data. Statistically, the paper suggests that factors relating to the level of competition, competitive advantages and economic development are strong in influencing foreign market involvements. On the other hand, unexpectedly, cultural factors (especially individualism/collectivism and low and high power distance dimensions) proved to have weak moderating effects. The reason for this, in part, is due to the pervading forces of globalisation and the attendant effect on global marketing. This paper has contributed to the general literature in a way that point to two mainimplications. First, with respect to research on national systems, the study may hold out some important lessons especially for developing nations. Most of these nations are known to be actively seeking to understand what it takes to attract foreign direct investment, expand domestic market and move their economies from the margin to the mainstream global economy. Second, it should be realised that competitive conditions remain in constant flux (even in mature industries and mature economies). This implies that a range of home country factors may be as important as host country factors in explaining firms' strategic moves and the degree of foreign market involvement. Further research can consider the impact of the home country environment on foreign market involvement decisions. Such an investigation will potentially provide further perspectives not only on the influence of national origin but also how home country effects are confounded with industry effects.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.105-119
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• 2017

Smartphone users hit over eighty-five percentage of Korean populations and personal private items and various information are stored in each user's smartphone. There are so many cases to propagate malicious codes or spywares for the purpose of catching illegally these kinds of information and earning pecuniary gains. Thus, need of information security is outstanding for using smartphone but also user's security perception is important. In this paper, we investigate about how information security affects smartphone operating system choices by users. For statistical analysis, the online survey with questionnaires for users of smartphones is conducted and effective 218 subjects are collected. We test hypotheses via communalities analysis using factor analysis, reliability analysis, independent sample t-test, and linear regression analysis by IBM SPSS statistical package. As a result, it is found that hardware environment influences on perceived ease of use. Brand power affects both perceived usefulness and perceived ease of use and degree of personal risk-accepting influences on perception of smartphone spy-ware risk. In addition, it is found that perceived usefulness, perceived ease of use, degree of personal risk-accepting, and spy-ware risk of smartphone influence significantly on intention to purchase smartphone. However, results of independent sample t-test for each operating system users of Android or iOS do not present statistically significant differences among two OS user groups. In addition, each result of OS user group testing for hypotheses is different from the results of total sample testing. These results can give important suggestions to organizations and managers related to smartphone ecology and contribute to the sphere of information systems (IS) study through a new perspective.

• Korean Journal of Environmental Biology
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• v.34 no.4
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• pp.304-313
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• 2016

One of the issues currently facing nuclear power plants is how to store spent nuclear waste materials which are contaminated with radionuclides such as $^{134}Cs$, $^{135}Cs$, and $^{137}Cs$. Bioremediation processes may offer a potent method of cleaning up radioactive cesium. However, there have only been limited reports on $Cs^+$ tolerant bacteria. In this study, we report the isolation and identification of $Cs^+$ tolerant bacteria in environmental soil and sediment. The resistant $Cs^+$ isolates were screened from enrichment cultures in R2A medium supplemented with 100 mM CsCl for 72 h, followed by microbial community analysis based on sequencing analysis from 16S rRNA gene clone libraries(NCBI's BlastN). The dominant Bacillus anthracis Roh-1 and B. cereus Roh-2 were successfully isolated from the cesium enrichment culture. Importantly, B. cereus Roh-2 is resistant to 30% more $Cs^+$ than is B. anthracis Roh-1 when treated with 50 mM CsCl. Growth experiments clearly demonstrated that the isolate had a higher tolerance to $Cs^+$. In addition, we investigated the adsorption of $0.2mg\;L^{-1}$ $Cs^+$ using B. anthracis Roh-1. The maximum $Cs^+$ biosorption capacity of B. anthracis Roh-1 was $2.01mg\;g^{-1}$ at pH 10. Thus, we show that $Cs^+$ tolerant bacterial isolates could be used for bioremediation of contaminated environments.

• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.125-154
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• 2009

This paper describes the possibility of human physiological data, especially brain-wave activity, to detect cognitive overload, a phenomenon that may occur while learner uses an e-learning system. If it is found that cognitive overload to be detectable, providing appropriate feedback to learners may be possible. To illustrate the possibility, while engaging in cognitive activities, cognitive load levels were measured by EEG (electroencephalogram) to seek detection of cognitive overload. The task given to learner was a computerized listening and recall test designed to measure working memory capacity, and the test had four progressively increasing degrees of difficulty. Eight male, right-handed, university students were asked to answer 4 sets of tests and each test took from 61 seconds to 198 seconds. A correction ratio was then calculated and EEG results analyzed. The correction ratio of listening and recall tests were 84.5%, 90.6%, 62.5% and 56.3% respectively, and the degree of difficulty had statistical significance. The data highlighted learner cognitive overload on test level of 3 and 4, the higher level tests. Second, the SEF-95% value was greater on test3 and 4 than on tests 1 and 2 indicating that tests 3 and 4 imposed greater cognitive load on participants. Third, the relative power of EEG gamma wave rapidly increased on the 3rd and $4^{th}$ test, and signals from channel F3, F4, C4, F7, and F8 showed statistically significance. These five channels are surrounding the brain's Broca area, and from a brain mapping analysis it was found that F8, right-half of the brain area, was activated relative to the degree of difficulty. Lastly, cross relation analysis showed greater increasing in synchronization at test3 and $4^{th}$ at test1 and 2. From these findings, it is possible to measure brain cognitive load level and cognitive over load via brain activity, which may provide atimely feedback scheme for e-learning systems.

• Korean Security Journal
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• no.39
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• pp.319-353
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• 2014

Cyber-based technologies are now ubiquitous around the glob and are emerging as an "instrument of power" in societies, and are becoming more available to a country's opponents, who may use it to attack, degrade, and disrupt communications and the flow of information. The globe-spanning range of cyberspace and no national borders will challenge legal systems and complicate a nation's ability to deter threats and respond to contingencies. Through cyberspace, competitive powers will target industry, academia, government, as well as the military in the air, land, maritime, and space domains of our nations. Enemies in cyberspace will include both states and non-states and will range from the unsophisticated amateur to highly trained professional hackers. In much the same way that airpower transformed the battlefield of World War II, cyberspace has fractured the physical barriers that shield a nation from attacks on its commerce and communication. Cyberthreats to the infrastructure and other assets are a growing concern to policymakers. In 2013 Cyberwarfare was, for the first time, considered a larger threat than Al Qaeda or terrorism, by many U.S. intelligence officials. The new United States military strategy makes explicit that a cyberattack is casus belli just as a traditional act of war. The Economist describes cyberspace as "the fifth domain of warfare and writes that China, Russia, Israel and North Korea. Iran are boasting of having the world's second-largest cyber-army. Entities posing a significant threat to the cybersecurity of critical infrastructure assets include cyberterrorists, cyberspies, cyberthieves, cyberwarriors, and cyberhacktivists. These malefactors may access cyber-based technologies in order to deny service, steal or manipulate data, or use a device to launch an attack against itself or another piece of equipment. However because the Internet offers near-total anonymity, it is difficult to discern the identity, the motives, and the location of an intruder. The scope and enormity of the threats are not just focused to private industry but also to the country's heavily networked critical infrastructure. There are many ongoing efforts in government and industry that focus on making computers, the Internet, and related technologies more secure. As the national intelligence institution's effort, cyber counter-intelligence is measures to identify, penetrate, or neutralize foreign operations that use cyber means as the primary tradecraft methodology, as well as foreign intelligence service collection efforts that use traditional methods to gauge cyber capabilities and intentions. However one of the hardest issues in cyber counterintelligence is the problem of "Attribution". Unlike conventional warfare, figuring out who is behind an attack can be very difficult, even though the Defense Secretary Leon Panetta has claimed that the United States has the capability to trace attacks back to their sources and hold the attackers "accountable". Considering all these cyber security problems, this paper examines closely cyber security issues through the lessons from that of U.S experience. For that purpose I review the arising cyber security issues considering changing global security environments in the 21st century and their implications to the reshaping the government system. For that purpose this study mainly deals with and emphasis the cyber security issues as one of the growing national security threats. This article also reviews what our intelligence and security Agencies should do among the transforming cyber space. At any rate, despite of all hot debates about the various legality and human rights issues derived from the cyber space and intelligence service activity, the national security should be secured. Therefore, this paper suggests that one of the most important and immediate step is to understanding the legal ideology of national security and national intelligence.