• 제목/요약/키워드: Security Metrics

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보안관제 업무에 대한 평가지표 개발 연구 (A Study on development of evaluation indicators on the Managed Security Service(MSS))

  • 이현도;이상진
    • 정보보호학회논문지
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    • 제22권5호
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    • pp.1133-1143
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    • 2012
  • 현재 많은 중앙행정기관, 지방자차단체 및 공공기관, 포탈 및 일반기업, 금융권 등은 사이버안전센터를 구축하여 운영하고 있다. 기관 입장에서 보안관제 업무는 이제 구축 보다는 효과적인 운영이 중요시되고 있다. 하지만 보안관제 업무를 평가할 수 있는 지표 및 제도가 없는 상황에서 사이버안전센터의 전체적 업무수행 수준을 파악할 수 없고 사이버안전센터별 강점과 약점을 도출하기도 어렵다. 이에 따라 본 논문은 보안관제 업무평가를 위한 지표를 개발함으로서 사이버안전센터의 업무수행 수준파악 및 향후 발전 방향 모색에 기여함을 목적으로 한다. 또한 기관의 정보보안 관리실태 평가를 수행함에 있어 보안관제 업무평가를 반영한다면 기관의 보안수준을 정확히 측정하여 체계적인 보안대책을 수립할 수 있다.

오픈소스 취약점 점검 도구 및 종합 보안 메트릭 설계를 통한 DevSecOps 구축방안 연구 (A Study on the Development of DevSecOps through the Combination of Open Source Vulnerability Scanning Tools and the Design of Security Metrics)

  • 최영해;노형준;조성윤;강한승;김동완;박수현;조민재;이주형
    • 정보보호학회논문지
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    • 제33권4호
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    • pp.699-707
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    • 2023
  • DevSecOps는 DevOps의 짧은 개발과 운용주기에 대응하기 위해 DevOps의 운용절차에 보안절차를 추가한 개념이다. DevSecOps 구축 시 빠른 개발 및 배포 주기를 지원하면서 안정적으로 보안성을 제공하기 위해 여러 단계의 취약점 점검 절차가 고려되어야 한다. 각 점검 단계별 활용 가능한 여러 오픈소스 취약점 점검 도구들이 존재하고 있으나 도구들이 지원하는 기능이 다양하고 점검결과들이 상이해 통합 운용 시 보안성 수준 평가 및 정보의 중요도 파악에 어려움이 있다. 본 논문은 오픈소스를 활용한 DevSecOps 구축 시에 보안점검 단계별 활용 가능한 오픈소스 취약점 점검 도구의 조합과 점검결과에 대한 통합적인 보안메트릭 설계방안을 제안한다.

IPv6 기반의 사물인터넷 환경에서 악성 노드의 패킷 유실 공격 탐지 및 우회 기법 분석 (An Analysis of Detection of Malicious Packet Dropping and Detour Scheme in IoT based on IPv6)

  • 최재우;권태경
    • 정보보호학회논문지
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    • 제26권3호
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    • pp.655-659
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    • 2016
  • 본 논문에서는 IPv6를 적용한 표준인 IEEE 802.15.4e와 RPL을 기반으로 하는 사물인터넷 환경에서 가용성을 확보하기 위하여 패킷 유실 공격 탐지 기법과 우회 기법을 제안한다. RPL의 순위값과 패킷 유실 연속성을 고려하여 패킷 유실 탐지 메트릭을 개선하였고 RPL을 통해 생성된 라우팅 경로에서 형제노드 및 자식노드를 활용한 우회기법을 구성하였다. 시뮬레이션을 통해 제안한 탐지 기법의 탐지 속도가 향상되었음을 확인하였고 제안한 우회 기법의 우회 성공률이 향상되었음을 확인하였다.

Enhanced Network Intrusion Detection using Deep Convolutional Neural Networks

  • Naseer, Sheraz;Saleem, Yasir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권10호
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    • pp.5159-5178
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    • 2018
  • Network Intrusion detection is a rapidly growing field of information security due to its importance for modern IT infrastructure. Many supervised and unsupervised learning techniques have been devised by researchers from discipline of machine learning and data mining to achieve reliable detection of anomalies. In this paper, a deep convolutional neural network (DCNN) based intrusion detection system (IDS) is proposed, implemented and analyzed. Deep CNN core of proposed IDS is fine-tuned using Randomized search over configuration space. Proposed system is trained and tested on NSLKDD training and testing datasets using GPU. Performance comparisons of proposed DCNN model are provided with other classifiers using well-known metrics including Receiver operating characteristics (RoC) curve, Area under RoC curve (AuC), accuracy, precision-recall curve and mean average precision (mAP). The experimental results of proposed DCNN based IDS shows promising results for real world application in anomaly detection systems.

모바일 RFID 미들웨어 품질 평가 모델 (Quality Testing Model of Mobile RFID Middleware)

  • 정혜정
    • 정보학연구
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    • 제10권4호
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    • pp.85-93
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    • 2007
  • RFID applied in many area. I think that RFID enlarge for our life more and more. The application technology of RFID change the Mobile RFID using mobile phone and PDF etc. I think, Mobile RFID enlarge application technology gradually. In this paper, we propose the quality measurement metrics for mobile RFID middleware. I propose the quality testing model for interoperability and security of mobile RFID middleware. We examine the international standard for mobile RFID and software testing. In this paper, I proposed the evaluation model of mobile RFID middleware on the basis of international standard ISO/IEC 9126-2 and ISO/IEC 25000 series.

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Fuzzy Based Multi-Hop Broadcasting in High-Mobility VANETs

  • Basha, S. Karimulla;Shankar, T.N.
    • International Journal of Computer Science & Network Security
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    • 제21권3호
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    • pp.165-171
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    • 2021
  • Vehicular Ad hoc Network (VANET) is an extension paradigm of moving vehicles to communicate with wireless transmission devices within a certain geographical limit without any fixed infrastructure. The vehicles have most important participation in this model is usually positioned quite dimly within the certain radio range. Fuzzy based multi-hop broadcast protocol is better than conventional message dissemination techniques in high-mobility VANETs, is proposed in this research work. Generally, in a transmission range the existing number of nodes is obstacle for rebroadcasting that can be improved by reducing number of intermediate forwarding points. The proposed protocol stresses on transmission of emergency message projection by utilization subset of surrounding nodes with consideration of three metrics: inter-vehicle distance, node density and signal strength. The proposed protocol is fuzzy MHB. The method assessment is accomplished in OMNeT++, SUMO and MATLAB environment to prove the efficiency of it.

A Comparative Analysis on Performance of Wireless Sensor Networks Routing Protocols

  • KRISHNA, KONDA. HARI;NAGPAL, TAPSI;BABU, Y. SURESH
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.240-244
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    • 2022
  • The common goals of designing a routing algorithm are not only to reduce control packet overhead, maximize throughput and minimize the end-to-end delay, but also take into consideration the energy consumption. Scalability is an important factor in designing an efficient routing protocol for wireless sensor networks (WSN's). Three metrics (power consumption, time of transmission and packet loss rate) are used in order to compare three routing protocols which are AODV, DSDV and LEACH.

A Comparison of Scene Change Localization Methods over the Open Video Scene Detection Dataset

  • Panchenko, Taras;Bieda, Igor
    • International Journal of Computer Science & Network Security
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    • 제22권6호
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    • pp.1-6
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    • 2022
  • Scene change detection is an important topic because of the wide and growing range of its applications. Streaming services from many providers are increasing their capacity which causes the industry growth. The method for the scene change detection is described here and compared with the State-of-the-Art methods over the Open Video Scene Detection (OVSD) - an open dataset of Creative Commons licensed videos freely available for download and use to evaluate video scene detection algorithms. The proposed method is based on scene analysis using threshold values and smooth scene changes. A comparison of the presented method was conducted in this research. The obtained results demonstrated the high efficiency of the scene cut localization method proposed by authors, because its efficiency measured in terms of precision, recall, accuracy, and F-metrics score exceeds the best previously known results.

Enhancement OLSR Routing Protocol using Particle Swarm Optimization (PSO) and Genrtic Algorithm (GA) in MANETS

  • Addanki, Udaya Kumar;Kumar, B. Hemantha
    • International Journal of Computer Science & Network Security
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    • 제22권4호
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    • pp.131-138
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    • 2022
  • A Mobile Ad-hoc Network (MANET) is a collection of moving nodes that communicate and collaborate without relying on a pre-existing infrastructure. In this type of network, nodes can freely move in any direction. Routing in this sort of network has always been problematic because of the mobility of nodes. Most existing protocols use simple routing algorithms and criteria, while another important criterion is path selection. The existing protocols should be optimized to resolve these deficiencies. 'Particle Swarm Optimization (PSO)' is an influenced method as it resembles the social behavior of a flock of birds. Genetic algorithms (GA) are search algorithms that use natural selection and genetic principles. This paper applies these optimization models to the OLSR routing protocol and compares their performances across different metrics and varying node sizes. The experimental analysis shows that the Genetic Algorithm is better compared to PSO. The comparison was carried out with the help of the simulation tool NS2, NAM (Network Animator), and xgraph, which was used to create the graphs from the trace files.

A Novel Thresholding for Prediction Analytics with Machine Learning Techniques

  • Shakir, Khan;Reemiah Muneer, Alotaibi
    • International Journal of Computer Science & Network Security
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    • 제23권1호
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    • pp.33-40
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    • 2023
  • Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.