• Journal of Food Hygiene and Safety
• /
• v.37 no.5
• /
• pp.306-309
• /
• 2022

Probiotics are live microorganisms that confer health benefits onto the host when administered at adequate doses. Most widely used probiotics, such as lactobacilli and bifidobacteria, are known to be elements of healthy gut microflora and hence are not considered a threat to the host. However, probiotics may pose a risk in certain populations with compromised immune systems or defects in gut barrier functions. Herein, we evaluated the safety of Bifidobacterium breve BB077, according to the safety evaluation guidelines for probiotics produced by the National Institute of Food and Drug Safety Evaluation (NIFDS). The results show that B. breve BB077 is both non-hemolytic and non-cytolytic. In contrast, B. breve BB077 exhibited higher streptomycin and tetracycline resistance than the suggested NIFDS standard cut-off values. Hence, a genetic analysis of the streptomycin and tetracycline resistance genes was performed to determine the origin of antimicrobial resistance. Streptomycin and tetracycline resistance was shown have arisen from chromosomal mutations and considered intrinsic to the taxonomic group. In conclusion, the B. breve BB077 strain might be safe for human consumption.

• Journal of Internet Computing and Services
• /
• v.25 no.1
• /
• pp.167-176
• /
• 2024

Chatbot services are used in various fields in connection with AI services. Security research on AI is also in its infancy, but research on practical security in the service implementation stage using it is more insufficient. This paper analyzes the security requirements for chatbot services linked to AI services. First, the paper analyzes the recently published papers and articles on AI security. A general implementation model is established by investigating chatbot services provided in the market. The implementation model includes five components including a chatbot management system and an AI engine Based on the established model, the protection assets and threats specialized in Chatbot services are summarized. Threats are organized around threats specialized in chatbot services through a survey of chatbot service managers in operation. Ten major threats were drawn. It derived the necessary security areas to cope with the organized threats and analyzed the necessary security requirements for each area. This will be used as a security evaluation criterion in the process of reviewing and improving the security level of chatbot service.

• Korean Journal of Environment and Ecology
• /
• v.15 no.3
• /
• pp.247-256
• /
• 2001

The purpose of the present study is to prepare the conservation category to establish the Natural Ecosystem Conservation Area(NECA) in Korea. The authors prepared the conservation category for the NECA based on the previous relevant papers and reports. This draft of conservation category was examined by way of the case study. From this, the possible factors are introduced to prepare the final conservation category that can be applied directly in Korean situation for the conservation of natural areas. The present conservation category was prepared based on the possible data, while some factors of which do not possess the adequate raw data at the moment was removed. According to the reference analyses from the previous conservation categories reported in order to prepare the conservation category in the NECA, a total of 27 factors was assessed; 21 for rarity and 15 fur utility and diversity, 13 far size, for both naturalness and human influence, 13 for typicalness 12 and 10 for fragility. From the literature reviews, the categories which quantitatively assessed was 13: 9 for rarity, 8 far human influence, and 5 for size. From the 27 conservation categories assessed, the factors such as rarity, taxonomic distinctiveness and threat was regarded as applicable to the Korean situation. Furthermore, the criteria such as use could be applied further when this is supported by the augmentative research and field studies.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.5
• /
• pp.919-939
• /
• 2021

As a next-generation communication technology, 5G networks are capable of handling large amounts of traffic based on higher speeds, shorter communication delays, and higher connectivity compared to 4G networks. In this 5G network environment, base stations are installed all over the city at high density due to their characteristics, and are connected to user terminals to provide services. Therefore, if the base station is damaged by a malicious attacker, it is expected to cause great damage to users and society as a whole. So the need for secure communication equipment such as 5G base stations has emerged. Therefore, in this paper, we propose the security functional requirements derived using threat modeling, a systematic methodology for 5G base stations, and the security assurance requirements at the level that can cope with the backdoor issues. The security requirements proposed in this paper can be used for base station design and development to construct a secure network environment as a security evaluation standard for 5G base stations.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.3
• /
• pp.91-98
• /
• 2021

Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.3
• /
• pp.1100-1118
• /
• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Convergence Security Journal
• /
• v.22 no.4
• /
• pp.3-9
• /
• 2022

Recently, as the environment of the 4th industrial revolution has arrived, the opening, sharing and convergence of data are actively being achieved in any organization. However, the opening and sharing of data inevitably leads to security vulnerability and there is ambivalence that is a threat that can affect the existence of an organization operated in the 4th industrial revolution environment. Especially security issues in the organization of the military can be a threat to the state, not the military itself, so it is always necessary to maintain a high level of security discipline. In this paper, 14 variables were selected through structural equation model applying theory of planned behavior, deterrence and protection motivation to find out the security level development measures by extracting factors that can affect security level. As a result, the theory of planned behavior that the security knowledge embodied through the usual security regulation education and evaluation affects the behavior was adopted, and the theory of deterrence and protection motivation showed the significance of the rejection level. In addition, it was confirmed that the variables that have the greatest impact on the military security level through the measured values of the three-year security audit were commanders and mental security. In conclusion, in order to improve the security level, it is suggested that security education, definite reward and punishment, and security system upgrading should be firmly established and mental security posture should be secured.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.5
• /
• pp.827-846
• /
• 2023

Recently, various information technologies such as network communication and sensors have begun to be integrated into weapon systems that were previously operated in stand-alone. This helps the operators of the weapon system to make quick and accurate decisions, thereby allowing for effective operation of the weapon system. However, as the involvement of the cyber domain in weapon systems increases, it is expected that the potential for damage from cyber attacks will also increase. To develop a secure weapon system, it is necessary to implement built-in security, which helps considering security from the requirement stage of the software development process. The U.S. Department of Defense is implementing the Risk Management Framework Assessment and Authorization (RMF A&A) process, along with the introduction of the concept of cybersecurity, for the evaluation and acquisition of weapon systems. Similarly, South Korea is also continuously making efforts to implement the Korea Risk Management Framework (K-RMF). However, so far, there are no cases where K-RMF has been applied from the development stage, and most of the data and documents related to the U.S. RMF A&A are not disclosed for confidentiality reasons. In this study, we propose the method for inferring the composition of the K-RMF based on systematic threat analysis method and the publicly released documents and data related to RMF. Furthermore, we demonstrate the effectiveness of our inferring method by applying it to the naval battleship system.

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

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.4
• /
• pp.41-46
• /
• 2016

Recently, many domestic and foreign corporates are concentrating in investment to wearable devices and users are provided with various service based on wearable devices 26% more than compared to last year. It is widely used in previous healthcare, smart work, smart home environment, and it is now introduced to get connection to fused service environment. However, as products of G company are commercialized, the security issue of personal information is causing dispute in society, and the danger of data management and security regarding telecommunication is increasing. Also, because the password system used in previous wireless environment is still in use, there are possible vulnerability considering the new and mutant security threat. This thesis conducted study about protocols that can exercise safe telecommunication in the basis of wearable devices. In the registration and certification process, the signature value is created based on the code value. The telecommunication method is designed to conduct safe telecommunication based on the signature value. As for the attack method occurring in the wearable device environment, the safety was analyzed and conducted performance evaluation of previous password system and proposal system, and verified about 14% of efficiency.