• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.305-325
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• 2014

In cloud computing infrastructure, current virtual machine trust measurement methods have many shortcomings in dynamism, security and concurrency. In this paper, we present a new method to measure the trust of virtual machine. Firstly, we propose "behavior trace" to describe the state of virtual machine. Behavior trace is a sequence of behaviors. The measurement of behavior trace is conducted on the basis of anticipated trusted behavior, which not only ensures security of the virtual machine during runtime stage but also reduces complexity of the trust measurement. Based on the behavior trace, we present a Dynamic Tree Style Trust Measurement Model (DTSTM). In this model, the measurement of system domain and user domain is separated, which enhances the extensibility, security and concurrency of the measurement. Finally, based on System Call Interceptor (SCI) and Virtual Machine Introspection (VMI) technology, we implement a DTSTM prototype system for virtual machine trust measurement. Experimental results demonstrate that the system can effectively verify the trust of virtual machine and requires a relatively low performance overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6098-6122
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• 2018

Cache-based side-channel attacks have achieved more attention along with the development of cloud computing technologies. However, current host-based mitigation methods either provide bad compatibility with current cloud infrastructure, or turn out too application-specific. Besides, they are defending blindly without any knowledge of on-going attacks. In this work, we present CacheSCDefender, a framework that provides a (Virtual Machine Monitor) VMM-based comprehensive defense framework against all levels of cache attacks. In designing CacheSCDefender, we make three key contributions: (1) an attack-aware framework combining our novel dynamic remapping and traditional cache cleansing, which provides a comprehensive defense against all three cases of cache attacks that we identify in this paper; (2) a new defense method called dynamic remapping which is a developed version of random permutation and is able to deal with two cases of cache attacks; (3) formalization and quantification of security improvement and performance overhead of our defense, which can be applicable to other defense methods. We show that CacheSCDefender is practical for deployment in normal virtualized environment, while providing favorable security guarantee for virtual machines.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.216-217
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• 2024

최근 클라우드 컴퓨팅 인프라 및 소프트웨어의 지속적인 발전으로 인한 복잡성 증가로 인해 신속한 확장성과 유연성에 대한 요구가 증가하고 있다. 이에 클라우드 네이티브 환경과의 호환성뿐만 아니라 개발과 운영의 효율성을 높이고자 코드로 인프라를 정의하여 자동화된 환경을 구축해 주는 코드형 인프라(Infrastructure as Code, IaC) 기술이 주목받고 있으며, AWS CloudFormation 은 대표적인 솔루션 중 하나이다. 그러나 IaC 형태로 배포되는 템플릿에 취약성이 존재할 경우, 인스턴스가 실행되기 전까지 보안 취약점을 미리 발견하기 어려워 DevOps 사이클에서의 보안 이슈를 야기할 수 있다. 이에 본 논문은 CloudFormation 템플릿의 보안 취약성 스캔이 가능하다고 알려진 오픈 소스 도구의 효율성을 평가하기 위한 사례 연구를 수행한다. 분석 결과를 바탕으로, DevSecOps 달성을 위한 IaC 기반 환경에서 취약성 사전 탐지의 필요성과 세분화된 접근 방식을 제시하고자 한다.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.205-213
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• 2024

As the Restaurant industry is growing rapidly. The demand for an effortless POS (Point Of Sale) system which can make management easy is increasing. So, the purpose of this study is to digitalise the growing industry of restaurants and its consumers by utilizing cross-platform development. Crossplatform development frameworks provide great opportunities to solve the issues of handling ubiquitous devices with minimum efforts to reduce the cost and increase the stability, accessibility of the end consumers. By availing those opportunities, an Integrated POS system with cross platform is proposed. This integrated cross-platform POS system is originally designed for a single restaurant managed by its own private cloud server. This research solves the 2 major problems. One of them is the accessibility of the system on modern devices without even writing platform-specific code with the help of cross-platform development. This included web, mobile, desktops & tablets at the same time with the same codebase. Second one is handling data consistency with ubiquitous devices with the help of cloud infrastructure to make data safe and consistent more than ever. In the Development of this system Dart will be used as the primary programming language for cross-platform development. On the Cloud server system apache will be used as the web server and PHP as server side language. System will be using MySQL as the database server.

• Information and Communications Magazine
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• v.32 no.7
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• pp.3-8
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• 2015

인터넷의 폭발적인 팽창에 따른 부작용들을 근본적으로 해소하고자 2000년대 후반부터 시작된 미래인터넷(Future Internet)에 관한 연구들이 최근까지 지속적으로 진행 중이다. 또한 새롭게 대두된 융합형(convergent) ICT 자원구성에 맞춘 지속적인 사용자 주도의 인프라 혁신 전략에 기반하여, SDN/NFV/Cloud 통합으로 형성하는 소프트웨어-정의 인프라(Software-Defined Infrastructure: SDI)를 개방형으로 구축하는 흐름이 있다. 즉 구축/운용의 중심이 하드웨어에서 소프트웨어 중심으로 최근 급속하게 전환되는 큰 변화가 ICT 인프라차원에서 본격화하고 있다. 즉 지금까지 논의되었던 여러 미래 인터넷 이슈들을 스마트한 초연결과 사용자 중심 서비스의 관점에서 바라보면서 미래형 ICT 인프라의 바람직한 구축을 서서히 가시화하고 있다. 따라서 본 논문에서는 초연결에 기반하여 값싸고 신속하게 서비스를 실증하기 위해 DevOps(Developers & Operators: 개발/운영 병행체제) 방법론으로 소프트웨어-정의 인프라로 체질을 바꿔가는 개방형 혁신을 살펴본다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1146-1165
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• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.584-586
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• 2011

네트워크 가상화(Network virtualization)란 물리적인 네트워크 자원들의 사용 효율을 높이기 위한 방법으로 자원들을 논리적으로 분리하는 기술이다. 네트워크 가상화는 클라우드 컴퓨팅(Cloud computing) 구현을 위한 네트워크 인프라(Infrastructure) 제공 기술로 각광받고 있다. 또한 MPLS(Multiprotocol Label Switching)기술은 빠른 고속 전송을 위한 라우팅 기술로서 가상 사설망을 구성하는 기술로 많이 사용되고 있다. 본 논문에서는 MPLS 라우팅 기술을 활용하여 클라우드 컴퓨팅 서버 간의 패킷 전송에 다양한 장점을 활용할 수 있는 방법을 제시한다. 제안하는 시스템은 독립성, 유연성, 성능과 비용의 요구사항을 만족하며, 논리적인 망분리를 통해 다양한 클라우드 컴퓨팅에 맞는 인프라를 서비스할 수 있다.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.25-31
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• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.150-155
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• 2024

Genomic data plays a transformative role in medicine, biology, and forensic science, offering insights that drive advancements in clinical diagnosis, personalized medicine, and crime scene investigation. Despite its potential, the integration and analysis of diverse genomic datasets remain challenging due to compatibility issues and the specialized nature of existing tools. This paper presents the GenomeSync system, designed to overcome these limitations by utilizing the Hadoop framework for large-scale data handling and integration. GenomeSync enhances data accessibility and analysis through SQL-based search capabilities and machine learning techniques, facilitating the identification of genetic traits and the resolution of forensic cases. By pre-processing DNA profiles from crime scenes, the system calculates similarity scores to identify and aggregate related genomic data, enabling accurate prediction models and personalized treatment recommendations. GenomeSync offers greater flexibility and scalability, supporting complex analytical needs across industries. Its robust cloud-based infrastructure ensures data integrity and high performance, positioning GenomeSync as a crucial tool for reliable, data-driven decision-making in the genomic era.