• Journal of Digital Convergence
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• v.12 no.5
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• pp.249-254
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• 2014

Recent advancement of USN technology has lent itself to the evolving communication technology for implantable devices in the field of medical service. The wireless transmission section for communication between implantable medical devices and patients is a cause of concern over invasion of privacy, resulting from external attackers' hacking and thus leakage of private medical information. In addition, any attempt to manipulate patients' medical information could end up in serious medical issues. The present study proposes an authentication protocol safe against intruders' attacks when RFID/USN technology is applied to implantable medical devices. Being safe against spoofing, information exposure and eavesdropping attacks, the proposed protocol is based on hash-function operation and adopts session keys and random numbers to prevent re-encryption. This paper verifies the security of the proposed protocol using the formal verification tool, Casper/FDR.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.297-302
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• 2015

The increase in applying IT to vehicles has given birth to smart cars or connected cars. As smarts cars become connected with external network systems, threats to communication security are on the rise. With simulation test results supporting such threats to Convergence security in vehicular communication, concerns are raised over relevant vulnerabilities, while an increasing number of studies on secure vehicular communication are published. Hacking attacks against vehicles are more dangerous than other types of hacking attempts because such attacks may threaten drivers' lives and cause social instability. This paper designed a Convergence security protocol for inter-vehicle and intra-vehicle communication using a hash function, nonce, public keys, time stamps and passwords. The proposed protocol was tested with a formal verification tool, Casper/FDR, and found secure and safe against external attacks.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.52-60
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• 2002

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users. A computer virus is one of program in computer and has abilities of self reproduction and destruction like a virus of biology. And hacking is to rob a person's data in a intruded computer and to delete data in a Person s computer from the outside. To block hacking that is intrusion of a person's computer and the computer virus that destroys data, a study for intrusion detection of system and virus detection using a biological immune system is in progress. In this paper, we make a model of positive and negative selection for self recognition which have a similar function like T-cytotoxic cell that plays an important role in biological immune system. We embody a self-nonself distinction algorithm in computer, which is an important part when we detect an infected data by computer virus and a modified data by intrusion from the outside. And we showed the validity and effectiveness of the proposed self recognition algorithm by computer simulation about various infected data obtained from the cell change and string change in the self file.

• Journal of Digital Convergence
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• v.13 no.5
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• pp.213-218
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• 2015

In parallel with evolving information communication technology, M2M(Machine-to-Machine) industry has implemented multi-functional and high-performance systems, and made great strides with IoT(Internet of Things) and IoE(Internet of Everything). Authentication, confidentiality, anonymity, non-repudiation, data reliability, connectionless and traceability are prerequisites for communication security. Yet, the wireless transmission section in M2M communication is exposed to intruders' attacks. Any security issues attributable to M2M wireless communication protocols may lead to serious concerns including system faults, information leakage and privacy challenges. Therefore, mutual authentication and security are key components of protocol design. Recently, secure communication protocols have been regarded as highly important and explored as such. The present paper draws on hash function, random numbers, secret keys and session keys to design a secure communication protocol. Also, this paper tests the proposed protocol with a formal verification tool, Casper/FDR, to demonstrate its security against a range of intruders' attacks. In brief, the proposed protocol meets the security requirements, addressing the challenges without any problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.131-138
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• 2016

This study reviewed the status of domestic and foreign Architectural Information Systems and related laws, analyzed the state of the architectural service industry, and proposed the phased introduction of BIM into Architectural Information Systems. The adoption of BIM in Architectural Information Systems both at home and abroad is generally at an unsatisfactory level, with only Singapore assuming a leading role in this area through activities such as the provision of a separate BIM submission service. Since it is desirable for BIM to be applied to additional types of architecture when the architectural licensing procedure is introduced, the different phases of adoption were set after analyzing the scales and types of architecture as defined in related laws. By analyzing the participation rates of architectural design firms in each scale of architecture design, the results demonstrated that, as the number of floors and total floor area in the building increases, the proportion of small scale architectural design firms involved decreases, while that of large-scale architectural design firms increases. The adoption of BIM is occurring mostly within large-scale architectural design firms, which is why it is desirable for its introduction into Architectural Information Systems to be separated into phases from large-scale buildings to increasingly small-scale architecture. In conclusion, this study divided the adoption of BIM in Architectural Information Systems into 6 stages and, following the Architectural administration procedure, established a segmented road map for the gradual activation of BIM.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.58-76
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• 2019

As the number of reported injuries has tended to increase over time, large hospitalization expenditure from excessive medical treatments and hospitalization, and insurance frauds associated with moral hazard in minor collisions have caused a global societal problem. Many occupants of rear-ended vehicles involved in rear-end collisions complain of whiplash injury, which is also known as neck injury, without any anatomical and radiological evidence. With only clinical symptoms, stating that a whiplash injury is a type of injury defined by the Abbreviated Injury Scale would be difficult. Therefore, this study focuses on minor rear-end collisions, where the rear-ender vehicle collides with the rear-ended vehicle at rest. The mathematics dynamic model is employed to simulate a total of 100 rear-end collision scenarios based on various weights and collision speeds and identify how the weights and speeds of both vehicles influence the risk of whiplash injury in occupants involved in minor rear-end collisions. The possibility of an injury is very high when the same-weight vehicles are involved in accidents at collision speeds of 15 km/h or higher. The possibilities are 36% and 84% with collision speeds of 15 km/h and 20 km/h, respectively, if weights are disregarded.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.