• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.312-318
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• 2021

Lack of knowledge and digital skills is a threat to the information security of the state and society, so the formation and development of organizational culture of information security is extremely important to manage this threat. The purpose of the article is to assess the state of information security of the state and society. The research methodology is based on a quantitative statistical analysis of the information security culture according to the EU-27 2019. The theoretical basis of the study is the theory of defense motivation (PMT), which involves predicting the individual negative consequences of certain events and the desire to minimize them, which determines the motive for protection. The results show the passive behavior of EU citizens in ensuring information security, which is confirmed by the low level of participation in trainings for the development of digital skills and mastery of basic or above basic overall digital skills 56% of the EU population with a deviation of 16%. High risks to information security in the context of damage to information assets, including software and databases, have been identified. Passive behavior of the population also involves the use of standard identification procedures when using the Internet (login, password, SMS). At the same time, 69% of EU citizens are aware of methods of tracking Internet activity and access control capabilities (denial of permission to use personal data, access to geographical location, profile or content on social networking sites or shared online storage, site security checks). Phishing and illegal acquisition of personal data are the biggest threats to EU citizens. It have been identified problems related to information security: restrictions on the purchase of products, Internet banking, provision of personal information, communication, etc. The practical value of this research is the possibility of applying the results in the development of programs of education, training and public awareness of security issues.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.173-182
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• 2023

The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.497-506
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• 2024

In this study, we proposed security information and event management for ship as a technology to respond to maritime cybersecurity regulations and evolving cyber threats. We analyze the main technologies of network management system and security information and event management, which are representative technologies for responding to ship cyber security, and propose SIEM for ships based on this. Optimized for ships based on the International Maritime Organization's Maritime Cyber Threat Management Guidelines, IACS UR E26, 27, etc. Derive the main functions of the SIEM for ship, linkage and normalization plan for the ship's heterogeneous equipment, ship's cyber threat and ship detection policy to identify ship's cyber security threats, and ship's operating environment and operating personnel.

• IMMUNE NETWORK
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• v.9 no.2
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• pp.46-52
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• 2009

Although tuberculosis poses a significant health threat to the global population, it is a challenge to develop new and effective therapeutic strategies. Nitric oxide (NO) and inducible NO synthase (iNOS) are important in innate immune responses to various intracellular bacterial infections, including mycobacterial infections. It is generally recognized that reactive nitrogen intermediates play an effective role in host defense mechanisms against tuberculosis. In a murine model of tuberculosis, NO plays a crucial role in antimycobacterial activity; however, it is controversial whether NO is critically involved in host defense against Mycobacterium tuberculosis in humans. Here, we review the roles of NO in host defense against murine and human tuberculosis. We also discuss the specific roles of NO in the central nervous system and lung epithelial cells during mycobacterial infection. A greater understanding of these defense mechanisms in human tuberculosis will aid in the development of new strategies for the treatment of disease.

• Journal of Digital Convergence
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• v.9 no.3
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• pp.11-19
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• 2011

The spread of computer and network gets various social and economic activities done quickly and efficiently. As a result, it makes a crime using network easy and increases the vulnerability of a social system. As there is a crime as a social being, we need to give careful consideration to the crime occurring in virtual space. Accordingly, the purpose of this paper is to investigate the regulatory need of the Criminal Procedure concerning the network security issues as the new legal and regulatory space that begins to be realized from the late of 20th century because of the extent of social threat. Above all, we addresses whether the amendment of existing legal regulations is necessary, based on the special characteristics of the virtual space.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.155-162
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• 2022

Over the last 10 years, there has been rapid growth in the use of Machine Learning (ML) techniques to automate the process of intrusion threat detection at a scale never imagined before. This has prompted researchers, software engineers, and network specialists to rethink the applications of machine ML techniques particularly in the area of cybersecurity. As a result there exists numerous research documentations on the use ML techniques to detect and block cyber-attacks. This article is a systematic review involving the identification of published scholarly articles as found on IEEE Explore and Scopus databases. The articles exclusively related to the use of machine learning in Intrusion Detection Systems (IDS). Methods, concepts, results, and conclusions as found in the texts are analyzed. A description on the process taken in the identification of the research articles included: First, an introduction to the topic which is followed by a methodology section. A table is used to list identified research articles in the form of title, authors, methodology, and key findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.89-96
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• 2023

Intrusion detection has been widely studied in both industry and academia, but cybersecurity analysts always want more accuracy and global threat analysis to secure their systems in cyberspace. Big data represent the great challenge of intrusion detection systems, making it hard to monitor and analyze this large volume of data using traditional techniques. Recently, deep learning has been emerged as a new approach which enables the use of Big Data with a low training time and high accuracy rate. In this paper, we propose an approach of an IDS based on cloud computing and the integration of big data and deep learning techniques to detect different attacks as early as possible. To demonstrate the efficacy of this system, we implement the proposed system within Microsoft Azure Cloud, as it provides both processing power and storage capabilities, using a convolutional neural network (CNN-IDS) with the distributed computing environment Apache Spark, integrated with Keras Deep Learning Library. We study the performance of the model in two categories of classification (binary and multiclass) using CSE-CIC-IDS2018 dataset. Our system showed a great performance due to the integration of deep learning technique and Apache Spark engine.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.4
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• pp.278-288
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• 2024

According to International Association of Classification Societies (IACS) Unified Requirement (UR) E26, ships contracted for construction after July 1, 2024 should be designed, constructed, commissioned and operated taking into account of cyber security. In particular, ship network monitoring tools should be installed in accordance with requirement 4.3.1 in IACS UR E26. In this paper, we propose a Security Information and Event Management (SIEM) security policy model for ships as an effective threat detection method by analyzing the cyber security regulations and ship network status in the maritime domain. For this purpose, we derived the items managed in the SIEM from the maritime cyber security regulations such as those of International Maritime Organization (IMO) and IACS, and defined 14 detection policies considering the status of the ship network. We also presents the detection policy for non-expert crews to understand it, and occurrence conditions depending on the ship's network environment to minimize indiscriminate alarms. We expect that the results of this study will help improve the efficiency of ship SIEM to be installed in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.654-666
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• 2019

The tactical network has several different characteristics compared with commercial internet network such as hierarchical topology, dynamic topology changing and wireless link based connectivity. For considering IP mobility management in the tactical network, current mobility management using Mobile IP(MIP) is not suitable with some reasons such as non-optimal routing paths and single point of failure. Proxy Mobile IP(PMIP) which supporting network-based mobility in hierarchical manner can provide optimal routing path in the tactical network environment, but centralized anchor is still remained a threat to the stability of the tactical network which changes its topology dynamically. In this paper, we propose PMIP-based distributed mobility management for the tactical network environment. From our design, routing paths are always configured in optimized way, as well as path is recovered quickly when the mobility anchor of user is failed. From numerical analysis, comparing to other mobility scheme, result shows that the proposed scheme can reduce packet transmission cost and latency in tactical network model.