• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1920-1937
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• 2015

Network environment has been under constant threat from both malicious attackers and inherent vulnerabilities of network infrastructure. Existence of such threats calls for exhaustive vulnerability analyzing to guarantee a secure system. However, due to the diversity of security hazards, analysts have to select from massive alternative hardening strategies, which is laborious and time-consuming. In this paper, we develop an approach to seek for possible hardening strategies and prioritize them to help security analysts to handle the optimal ones. In particular, we apply a Risk Flow Attack Graph (RFAG) to represent network situation and attack scenarios, and analyze them to measure network risk. We also employ a multi-objective genetic algorithm to infer the priority of hardening strategies automatically. Finally, we present some numerical results to show the performance of prioritizing strategies by network risk and hardening cost and illustrate the application of optimal hardening strategy set in typical cases. Our novel approach provides a promising new direction for network and vulnerability analysis to take proper precautions to reduce network risk.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.145-154
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• 2007

Analyzed about a matter and requirements to intimidate security of ubiquitous and home network threatening various security for personal information protection in ubiquitous home networks at this paper, and studied. Got authentication procedures and verification procedures acid user approach to be reasonable through designs to the home security gateway which strengthened a security function in the outsides, and strengthened protection of a home network. Also, execute a DoS. DDoS, IP Spoofing attack protective at home network security gateways proved, and security regarding against the Hacker's attack was performed, and confirmed. Strengthen appliances and security regarding a user, and confirm a defense regarding an external attack and present a home network security model of this paper to the plans that can strengthen personal information protection in ubiquitous home networks in ubiquitous home networks through experiment.

• Smart Media Journal
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• v.4 no.4
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• pp.24-32
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• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.45-54
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• 2007

As one of the most threatening attacks, DDoS attack makes distributed multiple agents consume some critical resources at the target within the short time, thus the extent and scope of damage is serious. Against the problems, the existing defenses focus on detection, traceback (identification), and filtering. Especially, in the hierarchical networks, the traffic congestion of a specific node could incur the normal traffic congestion of overall lower nodes, and also block the control traffic for notifying the attack detection and identifying the attack agents. In this paper, we introduce a DDoS attack tolerant network structure using a hierarchical overlay for hierarchical networks, which can convey the control traffic for defense such as the notification for attack detection and identification, and detour the normal traffic before getting rid of attack agents. Lastly, we analyze the overhead of overlay construction, the possibility of speedy detection notification, and the extent of normal traffic transmission in the attack case through simulation.

• Journal of IKEEE
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• v.26 no.4
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• pp.614-621
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• 2022

This paper proposes RIDS (Random Forest-Based Intrusion Detection), which is an intrusion detection system to detect hacking attack based on random forest. RIDS detects three typical attacks i.e. DoS (Denial of service) attack, fuzzing attack, and spoofing attack. It detects hacking attack based on four parameters, i.e. time interval between data frames, its deviation, Hamming distance between payloads, and its diviation. RIDS was designed in memory-centric architecture and node information is stored in memories. It was designed in scalable architecture where DoS attack, fuzzing attack, and spoofing attack can be all detected by adjusting number and depth of trees. Simulation results show that RIDS has 0.9835 accuracy and 0.9545 F1 score and it can detect three attack types effectively.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2112-2115
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• 2003

In this paper, we describe a SSAS (stepping stones attack simulator) that is automatic tool for testing and evaluation in TCP connection traceback system. The SSAS can pass multiple hosts that are included with hacker, middle-path hosts and victim’s system. And SSAS can also attack through commands to exploit the victim’s system. Usually, hackers do not expose their real attack positions through compromising the middle-path hosts like stepping-stones. Namely, hackers perform the stepping stones attacks in Internet. The SSAS can be utilized by developments and tests of the various countermeasure techniques of hacking. Specially, in this paper, it is used to test the performance of TCP connection traceback system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.660-663
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• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(DoS) attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1602-1605
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• 2005

An audit tracer is one of the last ways to defend an attack for network equipments. Firewall and IDS which block off an attack in advance are active way and audit tracing is passive way which analogizes a type and a situation of an attack from log after an attack. This paper explains importance of audit trace function in network equipment for security and defines events which we must leave by security audit log. We design and implement security audit system for secure router. This paper explains the reason why we separate general audit log and security audit log.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.449-456
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• 2018

Many organizations divide the network to manage the network in order to prevent the leakage of internal data between separate organizations / departments by sending and receiving unnecessary traffic. The most fundamental network separation method is based on physically separate equipment. However, there is a case where a network is divided and operated logically by utilizing a virtual LAN (VLAN) network access control function that can be constructed at a lower cost. In this study, we first examined the possibility of bypassing the logical network separation through VLAN ID scanning and double encapsulation VLAN hopping attack. Then, we showed and implemented a data leak scenario by utilizing the acquired VLAN ID. Furthermore, we proposed a simple and effective technique to detect and prevent the double encapsulation VLAN hopping attack, which is also implemented for validation. We hope that this study improves security of organizations that use the VLAN-based logical network separation by preventing internal data leakage or external cyber attack exploiting double encapsulation VLAN vulnerability.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.