• Title/Summary/Keyword: Grid security

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Survey on Hash-Based Post-Quantum Digital Signature Schemes (해시 기반 양자내성 전자서명 기법 연구 동향)

  • Lee, Jae-Heung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.4
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    • pp.683-688
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    • 2021
  • Digital signature algorithms such as RSA and ECDSA are threatened by the development of quantum computer technology, which is attracting attention as a future technology. Alternatively, various post-quantum algorithms such as grid-based, multivariate-based, code-based, and hash-based are being studied. Among them, the hash-based is a fast and quantitative security level that can be calculated and its safety has been proven. So it is receiving a lot of attention. In this paper, we examine various hash-based digital signature algorithms that have been proposed so far, and analyze their features and their strengths and weaknesses. In addition, we emphasize the importance of reducing the size of the signature in order for the hash-based signature algorithm to be practically used.

Enhanced CNN Model for Brain Tumor Classification

  • Kasukurthi, Aravinda;Paleti, Lakshmikanth;Brahmaiah, Madamanchi;Sree, Ch.Sudha
    • International Journal of Computer Science & Network Security
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    • v.22 no.5
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    • pp.143-148
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    • 2022
  • Brain tumor classification is an important process that allows doctors to plan treatment for patients based on the stages of the tumor. To improve classification performance, various CNN-based architectures are used for brain tumor classification. Existing methods for brain tumor segmentation suffer from overfitting and poor efficiency when dealing with large datasets. The enhanced CNN architecture proposed in this study is based on U-Net for brain tumor segmentation, RefineNet for pattern analysis, and SegNet architecture for brain tumor classification. The brain tumor benchmark dataset was used to evaluate the enhanced CNN model's efficiency. Based on the local and context information of the MRI image, the U-Net provides good segmentation. SegNet selects the most important features for classification while also reducing the trainable parameters. In the classification of brain tumors, the enhanced CNN method outperforms the existing methods. The enhanced CNN model has an accuracy of 96.85 percent, while the existing CNN with transfer learning has an accuracy of 94.82 percent.

A Maximum A Posterior Probability based Multiuser Detection Method in Space based Constellation Network

  • Kenan, Zhang;Xingqian, Li;Kai, Ding;Li, Li
    • International Journal of Computer Science & Network Security
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    • v.22 no.12
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    • pp.51-56
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    • 2022
  • In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB Eb/N0 gains respectively when activity detection error rate and symbol error rate reach 10-3, comparing with reference methods.

System implementation for Qshing attack detection (큐싱(Qshing) 공격 탐지를 위한 시스템 구현)

  • Hyun Chang Shin;Ju Hyung Lee;Jong Min Kim
    • Convergence Security Journal
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    • v.23 no.1
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    • pp.55-61
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    • 2023
  • QR Code is a two-dimensional code in the form of a matrix that contains data in a square-shaped black-and-white grid pattern, and has recently been used in various fields. In particular, in order to prevent the spread of COVID-19, the usage increased rapidly by identifying the movement path in the form of a QR code that anyone can easily and conveniently use. As such, Qshing attacks and damages using QR codes are increasing in proportion to the usage of QR codes. Therefore, in this paper, a system was implemented to block movement to harmful sites and installation of malicious codes when scanning QR codes.

The Development of an Intelligent Home Energy Management System Integrated with a Vehicle-to-Home Unit using a Reinforcement Learning Approach

  • Ohoud Almughram;Sami Ben Slama;Bassam Zafar
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.87-106
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    • 2024
  • Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

Design and Implementation of Fully Automated Solar Powered Irrigation System

  • Mohammad Fawzi Al Ajlouni;Essam Ali Al-Nuaimy;Salman Abdul-Rassak Sultan;Ali Hammod AbdulHussein Twaij;Al Smadi Takialddin
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.197-205
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    • 2024
  • This paper presents a fully automated stand-alone irrigation system with GSM (Global System for Mobile Communication) module. Solar energy is utilized to power the system and it is aimed to conserve water by reducing water losses. The system is based on a DC water pump that draws energy from solar panels along with automated water flow control using a moisture sensor. It is also fitted with alert and protection system that consists of an ultrasonic sensor and GSM messages sender that transmits signals showing the levels of the water in the reservoir and the battery charge. The control system is designed to stop the water pump from pumping water either when the battery level drops to equal or less than 10% of its full charge, or when the water level becomes less than 10 cm high in the reservoir. The experimental results revealed that the system is appropriate to use in remote areas with water scarcity and away from the national grid.

Securing the IoT Frontier: Exploring the Limitation and Future Directions in Cybersecurity

  • Moustafa Abdelrahman Mahmoud Ahmed;Nur Arzilawati Md Yunus
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.1-9
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    • 2024
  • As the Internet of Things (IoT) continues to permeate every facet of modern life, the imperative to secure this vast and dynamic frontier becomes increasingly paramount. This presents a comprehensive exploration of the challenges and opportunities inherent in safeguarding the interconnected web of IoT devices. The research critically examines the limitations of current cybersecurity measures through an extensive review of diverse topics, including IoT network performance, smart grid security, and the escalating cyber threats against critical infrastructures. A meticulous analysis of research findings underscores the need for enhanced infrastructure and ongoing research to fortify the cybersecurity mechanisms surrounding IoT objects. We underline the imperative of relentless research efforts to parry the advancing threats and leverage the promise of nascent technologies. Our findings affirm the pivotal influence of robust cybersecurity measures in crafting a resiliently connected ecosystem. The paper underscores the importance of ongoing research to address evolving threats and harness the potential of emerging technologies, reaffirming the central role of cybersecurity in shaping a secure interconnected world. In conclusion, the study emphasizes the dynamic and ever-evolving nature of cybersecurity on the IoT frontier. It unveils a complex landscape of challenges, ranging from network performance intricacies to the security concerns of critical infrastructures.

Research Trend Analysis Using Bibliographic Information and Citations of Cloud Computing Articles: Application of Social Network Analysis (클라우드 컴퓨팅 관련 논문의 서지정보 및 인용정보를 활용한 연구 동향 분석: 사회 네트워크 분석의 활용)

  • Kim, Dongsung;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.195-211
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    • 2014
  • Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

Design of Idle-time Measurement System for Data Spoofing Detection (데이터 스푸핑 탐지를 위한 유휴 시간 측정 시스템 설계)

  • Jung, Sung-Mo;Song, Jae-Gu;Kim, Tai-Hoon;So, Yo-Hwan;Kim, Seok-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.1
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    • pp.151-158
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    • 2010
  • The industrial foundation of the inside and outside of a country has brought significant damages due to attacks from hackers. Especially, if the national primary core infrastructures(like electric power, dam, railroad, atomic energy, etc.) has been significantly damaged, it can be directly linked not only to economic problems but also to people's lives. These national primary core infrastructures usually constitute SCADA system using Modbus RS486 communication. Because of this characteristic, SCADA system has RTU master and slave linked to RJ11 cables to directly pass commands. RJ11 is possible in data spoofing using physical connection because the transmission range of RJ11 has a wide bandwidth(almost 1km). Hence, this paper designed an idle-time measurement system for SCADA system for emerging security improvement in the national primary core infrastructures.

Study on the Application of V2G for Electric Vehicles in Korea Using Total Cost of Ownership Analysis (총소유비용 분석을 이용한 전기차의 V2G 도입에 대한 연구)

  • Kim, Younghwan;Lee, Jae-Seung
    • Journal of Energy Engineering
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    • v.24 no.2
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    • pp.129-143
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    • 2015
  • Increasing concerns on climate change and energy security accelerated policies to reduce green-house gas emission, especially from the transportation sector. Electric vehicle (EV) has been on the spotlight to deal with such environmental issue and V2G (Vehicle-to-Grid) technology began to draw attentions as an alternative to reduce ownership costs while contributing to an efficient and decentralized power grid. This study conducts a scenario analysis on total cost of ownership of EV under V2G scheme and compare with non-V2G EV and Internal Combustion Engine (ICE) vehicle. As result, V2G service is expected to provide an annual average profit of $210 to EV users willing to reverse flow its residual power in the battery. The profit from V2G service leaves a margin of $4,530 over operational lifetime, compared with $2,420 cost of charge for non-V2G EV. In summary, total cost of ownership of V2G-capable EV was 6.2% less than non-V2G EV and 10.2% higher than ICE vehicle. The results confirm a comparative economic advantage of operating EV under V2G scheme. Increased number of EVs with V2G service has shown to provide positive effects to power industry for valley filling in load distribution, thus, favorably increasing the overall economic feasibility.