• Convergence Security Journal
• /
• v.5 no.2
• /
• pp.9-17
• /
• 2005

Recently It's difficult to deal with about variety of attack. And Simple Security management have a problem. It is that they don't develop system measuring their system envoirment and have efficient attack detector, countermeasure organization about large network. Therefore, need model about enterprise management of various security system and intrusion detection of each systems and response. In this paper, improve PBNM structure that manage wide network resources and presented suitable model in intrusion detection and response of security system. Also, designed policy-based enterprise security management system for effective intrusion detection and response by applying presented model to enterprise security management system.

• Journal of Computing Science and Engineering
• /
• v.5 no.4
• /
• pp.305-313
• /
• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.4B
• /
• pp.566-575
• /
• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.6
• /
• pp.205-212
• /
• 2015

SSH provides a secure, encrypted communication channel between two end point systems using public key encryption. But SSH brute force attack is one of the most significant attacks. This kind of attack aims to login to the SSH server by continually guessing a large number of user account and password combinations. In this paper, we analyze logs of SSH brute force attacks in 2014 and propose a failed-log based detection mechanism in high performance computing service environment.

• Journal of information and communication convergence engineering
• /
• v.7 no.1
• /
• pp.7-12
• /
• 2009

The advanced computer network and Internet technology enables connectivity of computers through an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We proposed a network based hybrid Probe Intrusion Detection model using Fuzzy cognitive maps (PIDuF) that detects intrusion by DoS (DDoS and PDoS) attack detection using packet analysis. A DoS attack typically appears as a probe and SYN flooding attack. SYN flooding using FCM model captures and analyzes packet information to detect SYN flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance evaluation, the "IDS Evaluation Data Set" created by MIT was used. From the simulation we obtained the max-average true positive rate of 97.064% and the max-average false negative rate of 2.936%. The true positive error rate of the PIDuF is similar to that of Bernhard's true positive error rate.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.2
• /
• pp.259-266
• /
• 2017

In modern society, IT technology based systems are introduced and operated in various fields such as home, industry, and finance. To ensure the safety of society, IT systems introduced throughout society should be protected from cyber attacks. Understanding and checking the current security status of the system is one of the important tasks to response effectively against cyber attacks. In this paper, we analyze limitations of Game Theory and Attack Tree methodologies used to inspect for security vulnerabilities. Based on this, we propose a security vulnerability quantification method that complements the limitations of both methodologies. This provides a more objective and systematic way to inspect for security weaknesses.

• Convergence Security Journal
• /
• v.13 no.4
• /
• pp.41-46
• /
• 2013

Routing protocol using in the existing wire network cannot be used as it is for efficient data transmission in MANET. Because it consists of only mobile nodes, network topology is changing dynamically. Therefore, each mobile node must perform router functions. Variety of routing attack like DoS in MANET is present owing to these characteristic. In this paper, we proposed cooperative-based detection method to improve detection performance of flooding attack which paralyzes network by consuming resource. Accurate attack detection is done as per calculated adaptively threshold value considered the amount of all network traffic and the number of nodes. All the mobile nodes used a table called NHT to perform collaborative detection and apply cluster structure to the center surveillance of traffic.

• Proceedings of the National Institute of Ecology of the Republic of Korea
• /
• v.3 no.1
• /
• pp.47-53
• /
• 2022

The escape behavior of prey fish to predator attack is directly linked to the survival of the fish. In this study, I explored the escape behavior of Medaka fish to bird attacks. To simulate the attack, I designed a model triangular-shaped bird to slide along a fishing line connected between rods at both ends of the tank. The triangular shape was set to 10×15 (S=1), 15×20 (S=2), and 20×25 cm (S=3) with base×height. The slope (θ) of the fishing line, which determines the attack speed of the model bird, was set to values of 15° (θ=1), 30° (θ=2), and 45° (θ=3). The escape behavior was characterized using five variables: escape speed (ν), escape acceleration (α), responsiveness (γ), branch length similarity entropy (ε), and alignment (ϕ). The experimental results showed when (S, θ)=(fixed, varied), the change in values of the five variables were not significant. Thus, the fish respond more sensitively to S than to θ In contrast, when (S, θ)=(varied, fixed), ν, α, and γ showed increasing trends but ε and ϕ did not change much. This indicates the nature of fish escape behavior irrespective of the threat is inherent in ε and ϕ. I found that fish escape behavior can be divided into two types for the five physical quantities. In particular, the analysis showed that the type was mainly determined by the size of the model bird.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.9
• /
• pp.1374-1381
• /
• 2022

Existing research on security technology related to network attack response has focused on research using hardware network security technology, network attacks that wiretap and wiretap network packets, denial of service attack that consumes server resources to bring down the system, and network by identifying vulnerabilities before attack. It is classified as a scanning attack. In addition, methods for increasing network security, antivirus vaccines and antivirus systems have been mainly proposed and designed. In particular, many users do not fully utilize the security function of the router. In order to overcome this problem, it is classified according to the network security level to block external attacks through layered security management through layer-by-layer experiments. The scope of the study was presented by examining the security technology trends of edge routers, and suggested methods and implementation examples to protect from threats related to edge router-based network attacks.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.3
• /
• pp.479-490
• /
• 2013

Recently, the number of attacks by malicious application has significantly increased, targeting Android-platform mobile terminal such as Samsung Galaxy Note and Galaxy Tab 10.1. The malicious application can be distributed to currently used mobile devices through open market masquerading as an normal application. An attacker inserts malicious code into an application, which might threaten privacy by rooting attack. Once the rooting attack is successful, malicious code can collect and steal private data stored in mobile terminal, for example, SMS messages, contacts list, and public key certificate for banking. To protect the private information from the malicious attack, malicious code detection, rooting attack detection and countermeasure method are required. To meet this end, this paper investigates rooting attack mechanism for Android-platform mobile terminal. Based on that, this paper proposes countermeasure system that enables to extract and collect events related to attacks occurring from mobile terminal, which contributes to active protection from malicious attacks.