• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.495-502
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• 2013

In this paper, we present an anonymous authentication and location assurance protocol for secure location-aware services over vehicular ad hoc networks (VANETs). In other to achieve our goal, we propose the notion of a location-aware signing key so as to strongly bind geographic location information to cryptographic function while providing conditional privacy preservation which is a desirable property for secure vehicular communications. Furthermore, the proposed protocol provides an efficient procedure based on hash chain technique for revocation checking to effectively alleviate communication and computational costs on vehicles in VANETs. Finally, we demonstrate comprehensive analysis to confirm the fulfillment of the security objectives, and the efficiency and effectiveness of the proposed protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.558-579
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• 2021

The cloud storage provides flexible data storage services for data owners to remotely outsource their data, and reduces data storage operations and management costs for data owners. These outsourced data bring data security concerns to the data owner due to malicious deletion or corruption by the cloud service provider. Data integrity verification is an important way to check outsourced data integrity. However, the existing data verification schemes only consider the case that a verifier launches multiple data verification challenges, and neglect the verification overhead of multiple data verification challenges launched by multiple verifiers at a similar time. In this case, the duplicate data in multiple challenges are verified repeatedly so that verification resources are consumed in vain. We propose a duplicate data verification algorithm based on multiple verifiers and multiple challenges to reduce the verification overhead. The algorithm dynamically schedules the multiple verifiers' challenges based on verification time and the frequent itemsets of duplicate verification data in challenge sets by applying FP-Growth algorithm, and computes the batch proofs of frequent itemsets. Then the challenges are split into two parts, i.e., duplicate data and unique data according to the results of data extraction. Finally, the proofs of duplicate data and unique data are computed and combined to generate a complete proof of every original challenge. Theoretical analysis and experiment evaluation show that the algorithm reduces the verification cost and ensures the correctness of the data integrity verification by flexible batch data verification.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.279-294
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• 2024

Agriculture has played a significant role in the national economy, contributing to food security, driving economic growth, and safeguarding the dietary habits of the population. Korean agriculture has been compelled to focus on intensive farming due to its limited cultivation area, excessive input costs, and the limitations of agricultural mechanization. In the Republic of Korea (R.O.K), the concept of environmentally friendly animal agriculture began to be introduced in the early 2000s. This concept ultimately aims to cultivate sustainable animal agriculture (SAA) through environmentally friendly production practices, ensuring the healthy rearing of animals to supply safe animal products. Despite the government's efforts, there are still significant challenges in implementing environmentally friendly agriculture and SAA in the R.O.K. Therefore, the objective of this review is to establish the direction that the animal agriculture sector should take in the era of climate crisis, and to develop effective strategies for SAA tailored to the current situation in the R.O.K by examining the trends in SAA in the U.S. The animal agriculture sector in the U.S. has been working towards creating a SAA system where humans, animals, and the environment can coexist through government initiatives, industry research, technological support, and individual efforts. Efforts have been made to reduce emissions like carbon, and improve factors affecting the environment such as the carbon footprint, odor, and greenhouse gases associated with animal agriculture processes for animals such as cattle and pigs. The transition of the U.S. towards SAA appears to be driven by both external goals related to addressing climate change and the primary objectives of responding to the demand for safe animal products, expanding consumption, and securing competitiveness in overseas export markets. The demand for animal welfare, organic animal products, and processed goods has been increasing in the U.S. consumer market. A major factor in the transformation of the U.S. animal agriculture sector in terms of livestock specifications is attributed to environmentally friendly practices such as high-quality feed, heat stress reduction, improvements in reproductive ability and growth period reduction, and efforts in animal genetic enhancement.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.643-653
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• 2018

Xamarin is a representative cross-platform development framework that allows developers to write mobile apps in C# for multiple mobile platforms, such as Android, iOS, or Windows Phone. Using Xamarin, mobile app developers can reuse existing C# code and share significant code across multiple platforms, reducing development time and maintenance costs. Meanwhile, malware authors can also use Xamarin to spread malicious apps on more platforms, minimizing the time and cost of malicious app creation. In order to cope with this problem, it is necessary to analyze and detect malware written with Xamarin. However, little studies have been conducted on static analysis methods of the apps written in Xamarin. In this paper, we examine the structure of Android apps written with Xamarin and propose a static analysis technique for the apps. We also demonstrate how to statically reverse-engineer apps that have been transformed using code obfuscation. Because the Android apps written with Xamarin consists of Java bytecode, C# based DLL libraries, and C/C++ based native libraries, we have studied static reverse engineering techniques for these different types of code.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.257-270
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• 2022

In this paper, we design a smart factory risk improvement system and risk improvement method using AI edge devices. The smart factory risk improvement system collects, analyzes, prevents, and promptly responds to the worker's work performance process in the smart factory using AI edge devices, and can reduce the risk that may occur during work with improving the defect rate when workers perfom jobs. In particular, based on worker image information, worker biometric information, equipment operation information, and quality information of manufactured products, it is possible to set an abnormal risk condition, and it is possible to improve the risk so that the work is efficient and for the accurate performance. In addition, all data collected from cameras and IoT sensors inside the smart factory are processed by the AI edge device instead of all data being sent to the cloud, and only necessary data can be transmitted to the cloud, so the processing speed is fast and it has the advantage that security problems are low. Additionally, the use of AI edge devices has the advantage of reducing of data communication costs and the costs of data transmission bandwidth acquisition due to decrease of the amount of data transmission to the cloud.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.71-83
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• 2012

The use of technical proposal tendering has been expanding recently with the aim of effecting cost reduction, quality enhancement, technological development and value realization centered on multifunctional administrative cities, innovation cities, and the Yongsan relocation project. In line with the increasing interest towards life cycle cost improvement measures as an important evaluation category concerning technical proposal tendering, efforts in preparing measures that can execute the security of credibility and objective evaluation concerning architectural life cycle cost are being made. However, problems such as lack of applicable cases of design development and detail design, distortion of initial construction costs concerning the original plan, combination of constant price and current price, the ambiguity of the calculation standards between tendering corporations, inaccuracy of terms, and insufficient compositional formats concerning life cycle improvement measures are being cited. Accordingly, this study sought to propose a measure to improve the compositional guidelines, format, and standards so that a systematic life cycle cost evaluation can be executed for the reliable distinction of each participating corporation, enhanced credibility and objective evaluation of the life cycle cost improvement measure for technical proposals.

• Journal of the Korean Society of Safety
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• v.26 no.2
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• pp.89-98
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• 2011

The traffic accidents at a construction site, which happen due to construction vehicles' frequent access to a construction site, its subsequent conflicts with ordinary vehicles and pedestrians, and inappropriate installation & management of traffic security facilities, have not many proportions in all traffic accidents, but obviously, the accident damage is quite serious when comparing the level of the fatal per one accident. This research conducted an analysis of traffic accident injury severity using Ordered Probit Model in relation to 241 traffic accident cases that occurred caused by construction sites among the traffic accidents that took place in Seoul and Gyeoggi-do region for two years from 2006 until 2007. As a result, the significant variables enough to explain traffic accident injury severity were analyzed to be the state of road surface, linear shape of an accident spot & whether the damaging car belongs to the vehicle for construction, and whether vehicles have access to a construction site at the time of an accident. Through this, this research found out some fact as follows: first, there need to be more aggressive management of the vehicles for construction and a year-round placement of the manpower who can control vehicular access to a construction site. Second, it is necessary to get drivers to recognize the fact that there exists a construction site on the construction section which is on the border of curved roads in advance to prevent a traffic accident, helping to reduce socioeconomic loss & costs incurred by a traffic accident.

• The Journal of Society for e-Business Studies
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• v.26 no.2
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• pp.61-81
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• 2021

In the era of untact, the "Chabak" using cars as accommodation spaces is attracting attention as a new form of travel. Due to the advantages, including low costs, convenience, and safety, as well as the characteristics of the vehicle enabling independent travel, the demand for Chabak is continuously increasing. Despite the rapid growth of the market and related industries, little academic has investigated this trend. To establish itself as a new type of travel culture and to sustain the growth of related industries, it is essential to understand the public perception of Chabak. Therefore, based on the marketing mix theory and big data analysis, this study analyzes the public perception of Chabak. The results showed that Chabak has established itself as a consumer-led travel culture, contributing to the aftermarket growth of the automobile industry. Additionally, consumers were found to be increasingly inclined to enjoy travel economically and wisely, and actively share information through social media. This initial study on the new travel trend of Chabak is significant in that it employs big data analysis on a theoretical basis.

• Journal of Platform Technology
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• v.9 no.4
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• pp.32-41
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• 2021

The EU enacted a law strongly regulating the GDPR to protect the privacy of its citizens on 25 May 2018. Compliance with GDPR is an essential prerequisite for companies to enter the European market in the global economic era. In this paper, Step-by-step measures have been defined to conclude DPA agreements for the appropriate level of protection against EU personal data transfer. To explore the benefits and expected effects of determining appropriateness at the government level. As a result, enterprises benefit from simplifying processes, reducing time, and reducing costs when entering the EU. Government-level support in response to personal data breach and communication with the EU Commission will have a positive impact, However, even after the adequacy decision, the entity continues to need activities to secure personal data through compliance with GDPR principles and obligations. Major operations of companies that comply with GDPR are also maintained as important tasks that must be observed in most cases except for the Data Protection Agreement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.