• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.213-218
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• 2021

This paper proposes a technique for detecting a significant threat that attempts to get sensitive and confidential information such as usernames, passwords, credit card information, and more to target an individual or organization. By definition, a phishing attack happens when malicious people pose as trusted entities to fraudulently obtain user data. Phishing is classified as a type of social engineering attack. For a phishing attack to happen, a victim must be convinced to open an email or a direct message [1]. The email or direct message will contain a link that the victim will be required to click on. The aim of the attack is usually to install malicious software or to freeze a system. In other instances, the attackers will threaten to reveal sensitive information obtained from the victim. Phishing attacks can have devastating effects on the victim. Sensitive and confidential information can find its way into the hands of malicious people. Another devastating effect of phishing attacks is identity theft [1]. Attackers may impersonate the victim to make unauthorized purchases. Victims also complain of loss of funds when attackers access their credit card information. The proposed method has two major subsystems: (1) Data collection: different websites have been collected as a big data corresponding to normal and phishing dataset, and (2) distributed detection system: different artificial algorithms are used: a neural network algorithm and machine learning. The Amazon cloud was used for running the cluster with different cores of machines. The experiment results of the proposed system achieved very good accuracy and detection rate as well.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.577-589
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• 2023

Ministry of National Defense plans to harness AI as a key technology to bolster overall defense capability for cultivation of an advanced strong military based on science and technology based on Defense Innovation 4.0 Plan. However, security threats due to the characteristics of AI can be a real threat to AI-based defense information system. In order to solve them, systematic security activities must be carried out from the development stage. This paper proposes security activities and considerations that must be carried out at each stage of AI-based defense information system. Through this, It is expected to contribute to preventing security threats caused by the application of AI technology to the defense field and securing the safety and reliability of defense information system.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.79-95
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• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• Journal of Internet Technology
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• v.22 no.5
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• pp.1069-1082
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• 2021

The Internet of Things (IoT) is vulnerable to a wide range of security risks, which can be effectively mitigated by applying Cyber Threat Intelligence (CTI) sharing as a proactive mitigation approach. In realizing CTI sharing, it is of paramount importance to guarantee end-to-end protection of the shared information as unauthorized disclosure of CTI is disastrous for organizations using IoT. Furthermore, resource-constrained devices should be supported through lightweight operations. Unfortunately, the aforementioned are not satisfied by the Hypertext Transfer Protocol Secure (HTTPS), which state-of-the-art CTI sharing systems mainly depends on. As a promising alternative to HTTPS, Ephemeral Diffie-Hellman over COSE (EDHOC) can be considered because it meets the above requirements. However, EDHOC in its current version contains several security flaws, most notably due to the unprotected initial message. Consequently, we propose a lightweight end-to-end privacy-preserving security protocol that improves the existing draft EDHOC protocol by utilizing previously shared keys and keying materials while providing ticket-based optimized reauthentication. The proposed protocol is not only formally validated through BAN-logic and AVISPA, but also proved to fulfill essential security properties such as mutual authentication, secure key exchange, perfect forward secrecy, anonymity, confidentiality, and integrity. Also, comparing the protocol's performance to that of the EDHOC protocol reveals a substantial improvement with a single roundtrip to allow frequent CTI sharing.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.228-235
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• 2008

Terror for airplane, airport and passengers of the problems is being threat over the world. and since 9.11 terror of 2001 year, many countries have endeavored to prevent terror and have manipulate airport security part as important field. Especially, The U.S.A made Transportation security Administration in Homeland security adminstration and strongly execute for policies related anti-terror. many countries over the world enforce airport and airplane security facilities with science-technology contents. and with security exploitation for the passengers and freight security inspection level enforcement, many countries also make effort to interupt aviation terror threat. In this process, in the center of developed countries that need science-technology contents adaption, much budget and personals are invested and exploited a security inspection instrument and complimented of many facilities As a result, according to the development of science-technology, prevention of Terror have much developed. The contents using intelligence-communication technology inevitably needed on the goal of terror prevention and safty. From simple monitoring for the people who come in and out airport to boarding process and inspection for the freight, security inspection process for the passengers, bio information input, confirmation, of the level that there is no cases of adaption of contents, The reality have generalized of using contents. The study is going to research contents application situation.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.109-126
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• 2018

With massive and dense production, the livestock industry is rapidly moving into a large-scale, capital-intensive industry especially in swine, poultry, and ducks. However, livestock epidemics can pose a serious threat to the livestock industry and the lives of the people. The government has established and operates the National Animal Protection and Prevention System (KAHIS) since 2013 in order to control the threat, in accordance with the five stages. The digitalized data and information are excellent in ease of management, but it is also pointed out that it is difficult to take countermeasures through linkage with the data in an emergency situation. Recently, the technology of the fourth industrial revolution such as Internet of Things (IoT), Big Data, Artificial intelligence (AI) has been rapidly implemented to the livestock industry, which makes smart livestock disease control system possible. Therefore, this study investigated the domestic and overseas cases which apply 4th Industrial Revolution technology in the industry, and derived 13 possible candidate tasks in the near future. In order to ascertain the priority of policy formulation, we surveyed the expert groups and examined the priority of each of the five stages of the prevention and the priority of each stage. The results of this study are expected to contribute to the establishment of policies for the advancement of smart livestock disease control research and livestock protection.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.102-115
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• 2018

The world's major countries carry forward strategies for enhancing industrial competitiveness, resulting in the fourth industrial revolution while a new growth engine is required to deal with the slow growth of global economy and declining productivity. Artificial intelligence (AI) is regarded as a core technology of the fourth industrial revolution. AI is expected to be implemented rapidly in advertising and media industries. However, it is hard to find an effective way to implement AI in these industries, especially because of how quickly the AI market changes and develops. Therefore, this study seeks the possible industrial influence of AI in advertising and media industries and invigoration plan for AI, by an in-depth interview with 10 professionals who lead the AI market. First, it was analyzed to explore the macroscopic side of the AI market through P (Politics), E (Economy), S (Society), and T (Technology). Also, the applicability of AI in advertising and media industries was explored by analyzing its S (Strength), W (Weakness), O (Opportunity), and T (Threat).The result indicates that it is necessary to build up a nation-wide construction of infrastructure for the fourth industrial revolution to invigorate AI in advertising and media industries. Moreover, a social environment capable of overcoming a hyper-connected society and social risks should be fostered. Lastly, it is urgent for both the industrial and academic world to diagnose the influence of AI in advertising and media industries, to anticipate the future in accordance with technological advance, set a proper direction, to invest actively for technical development of AI, and to formulate innovative policies.