• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.119-132
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• 2006

The network based security techniques well-known until now have week points to be passive in attacks and susceptible to roundabout attacks so that the misuse detection based intrusion prevention system which enables positive correspondence to the attacks of inline mode are used widely. But because the Misuse detection based Intrusion prevention system is proportional to the detection rules, it causes excessive false alarm and is linked to wrong correspondence which prevents the regular network flow and is insufficient to detect transformed attacks, This study suggests an Intrusion prevention system which uses Support Vector machines(hereinafter referred to as SVM) as one of rule based Intrusion prevention system and Anomaly System in order to supplement these problems, When this compared with existing intrusion prevention system, show performance result that improve about 20% and could through intrusion prevention system that propose false positive minimize and know that can detect effectively about new variant attack.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1449-1457
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• 2010

The intrusion prevention system solution is receiving the spotlight as the next generation security system. It is anticipated that the system will form a very active security market both domestically and overseas. Moreover, quality evaluation proving successful inspection of merchandises is required of domestic businesses seeking to operate in the international market, and general users also prefer those that have successfully passed inspection. This study has constructed a security quality evaluation model for intrusion prevention system by deriving and analyzing security quality evaluation items required by an intrusion prevention system solution and by classifying them in detail. The derived quality evaluation model will play an important role of assessing and improving the quality of intrusion prevention system.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.42-49
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• 2021

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1070-1080
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• 2015

In this paper, we introduce an SDN-based intrusion prevention system for more secure Science DMZ with no performance limits. The proposed system is structured with intrusion-prevention, intrusion-detection, and prevention-decision subsystems which are physically distributed but informationally connected by an SDN interface. The functional distribution and the application of SDN technology increase the flexibility and extensibility of the proposed system and prevent performance degradation possibly caused by network security equipments on Science DMZ. We verified the feasibility and performance of the proposed system over a testbed set up at KREONET.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.76-81
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• 2011

Intrusion prevention systems (IPS) are important solution about solved problems for inside system security or outsider attacks. When introduce this system, first consideration item is secured rather than multiple function. Colored Petri Nets (CPNs) used that in order to secured verification for user authentication function of intrusion prevention system security model. CPNs is a graphical modeling language suitable for modeling distributed, concurrent, deterministic or non-deterministic systems with synchronous. Like these CPNs was expressed every possible state and occurrence graph. Secured of IPS security model was verified because expression every state using CPN tool and as a result of analyzing the occurrence graph was without a loop or interruption.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.1
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• pp.55-63
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• 2006

Recently, there is much abnormal traffic driven by several worms, such as Nimda, Code Red, SQL Stammer, and so on, making badly severe damage to networks. Meanwhile, diverse prevention schemes for defeating abnormal traffic have been studied in the academic and commercial worlds. In this paper, we present the structure of a stepwise intrusion prevention system that is designed with the feature of putting limitation on the network bandwidth of each network traffic and dropping abnormal traffic, and then compare the proposed scheme with a pre-existing scheme, which is a True/False based an anomaly prevention scheme for several worm-patterns. There are two criteria for comparison of the schemes, which are Normal Traffic Rate (NTR) and False Positive Rate (FPR). Assuming that the abnormal traffic rate of a specific network is $\beta$ during a predefined time window, it is known that the average NTR of our stepwise intrusion prevention scheme increases by the factor of (1+$\beta$)/2 than that of True/False based anomaly prevention scheme and the average FPR of our scheme decrease by the factor of (1+$\beta$)/2.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.242-250
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• 2013

Many information systems that provide useful services to people are connected to the Internet for convenience and efficiency. However, improper accessibility might make the systems susceptible to a variety of attacks. Although existing security solutions such as an intrusion detection system, intrusion prevention system, and firewalls have been designed to protect against such attacks, it is impossible to block all kinds of attacks. Furthermore, most of the proposed solutions require information about attacks for efficient prevention. Research on intrusion-tolerant systems (ITSs) have been conducted in order to continue providing proper services in threatening environments. The purpose of an ITS is to survive against every intrusion, rather than to prevent them. In this paper, previous studies on ITS are introduced and classified according to the centric scheme as middleware-based ITS, hardware-based ITS, and recovery-based ITS. Recent research focusing on adaptive transformation schemes is also introduced.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.1-12
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• 2022

Besides unexpected growth perceived by IoT's, the variety and volume of threats have increased tremendously, making it a necessity to introduce intrusion detections systems for prevention and detection of such threats. But Intrusion Detection and Prevention System (IDPS) inside the IoT network yet introduces some unique challenges due to their unique characteristics, such as privacy inference, performance, and detection rate and their frequency in the dynamic networks. Our research is focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing unified a solution to implement the open-source IDPS in the IoT architecture for assessing the performance of IDS by calculating; usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2895-2921
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• 2018

Security has become one of the major concerns in mobile adhoc networks (MANETs). Data and voice communication amongst roaming battlefield entities (such as platoon of soldiers, inter-battlefield tanks and military aircrafts) served by MANETs throw several challenges. It requires complex securing strategy to address threats such as unauthorized network access, man in the middle attacks, denial of service etc., to provide highly reliable communication amongst the nodes. Intrusion Detection and Prevention System (IDPS) undoubtedly is a crucial ingredient to address these threats. IDPS in MANET is managed by Command Control Communication and Intelligence (C3I) system. It consists of networked computers in the tactical battle area that facilitates comprehensive situation awareness by the commanders for timely and optimum decision-making. Key issue in such IDPS mechanism is lack of Smart Learning Engine. We propose a novel behavioral based "Smart Multi-Instance Multi-Label Intrusion Detection and Prevention System (MIML-IDPS)" that follows a distributed and centralized architecture to support a Robust C3I System. This protocol is deployed in a virtually clustered non-uniform network topology with dynamic election of several virtual head nodes acting as a client Intrusion Detection agent connected to a centralized server IDPS located at Command and Control Center. Distributed virtual client nodes serve as the intelligent decision processing unit and centralized IDPS server act as a Smart MIML decision making unit. Simulation and experimental analysis shows the proposed protocol exhibits computational intelligence with counter attacks, efficient memory utilization, classification accuracy and decision convergence in securing C3I System in a Tactical Battlefield environment.