• Journal of IKEEE
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• v.26 no.4
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• pp.622-627
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• 2022

This paper proposes an intrusion detection system for in-vehicle network to improve detection performance considering attack counts and attack types. In intrusion detection system, both FNR (False Negative Rate), where intrusion frame is misjudged as normal frame, and FPR (False Positive Rate), where normal frame is misjudged as intrusion frame, seriously affect vechicle safety. This paper proposes a novel intrusion detection algorithm to improve both FNR and FPR, where data frame previously detected as intrusion above certain attack counts is automatically detected as intrusion and the automatic intrusion detection method is adaptively applied according to attack types. From the simulation results, the propsoed method effectively improve both FNR and FPR in DoS(Denial of Service) attack and spoofing attack.

• ETRI Journal
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• v.38 no.2
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• pp.387-396
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• 2016

This paper introduces a new type of collision attack on first-order masked Advanced Encryption Standards. This attack is a known-plaintext attack, while the existing collision attacks are chosen-plaintext attacks. In addition, our method requires significantly fewer power measurements than any second-order differential power analysis or existing collision attacks.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.185-188
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• 2002

This paper proposes a efficient way to use Database that is constructed about attack-pattern. For IDS that activate confrontation, we reconstruct by Layered Attack Tree after constructing attack pattern by Attack Tree. And then this paper has designed IDS that Layered Attack Tree is applied, verified them.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1685-1689
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• 2018

In this research, 51% attack or majority attack is becoming an important security issue for proof of work based blockchains. Due to decentralized nature of blockchains, any attacks that shutdowns the network or which take control over the network is hard to prevent and assess. In this paper, different types of majority attack are summarized and the motivations behind the attacks are explained. To show the feasibility of the majority attack, we build an example mining machines that can take control over two of the public blockchains, Vertcoin and Monero.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1802-1819
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• 2017

Correlation-enhanced collision attack has been proposed by Moradi et al. for several years. However, in practical operations, this method costs lots of time on trace acquisition, storage and averaging due to its bytewise collision detection. In this paper, we propose a bitwise collision attack based on second-order distance model. In this method, only 9 average traces are enough to finish a collision attack. Furthermore, two candidate models are given in this study to distinguish collisions, and the corresponding practical experiments are also performed. The experimental results indicate that the operation time of our attack is only 8% of that of correlation-enhanced collision attack, when the two success rates are both above 0.9.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.4
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• pp.252-259
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• 2008

The purpose of this study is to estimate the movement of microbial contaminant caused by bio-attack using bio-agent such as bacillus anthracis for preventing contaminant diffusion. multizone simulation was carried out in the case of three types of bio-attack scenario in the government building. Simulation results show that severe contaminant diffusion is brought about in all cases of bio-attack scenario in one hour, though pollution boundaries have different mode according to bio-attack scenarios. Simulation results also show that immune building technology such as filter and UVGI technology gives us powerful alternatives to meet the emergent situation caused by unexpected bio-attack.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.139-149
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• 2010

Internet was designed for network scalability and best-effort service which makes all hosts connected to Internet to be vulnerable against attack. Many papers have been proposed about attack detection algorithms against the attack using IP spoofing and DoS/DDoS attack. Purpose of DoS/DDoS attack is achieved in short period after the attack begins. Therefore, DoS/DDoS attack should be detected as soon as possible. Attack detection algorithms using false alarm rates consist of the false negative rate and the false positive rate. Moreover, they are important metrics to evaluate the attack detections. In this paper, we analyze the performance of the attack detection algorithms using the impact of false negative rate and false positive rate variation to the normal traffic and the attack traffic by simulations. As the result of this, we find that the number of passed attack packets is in the proportion to the false negative rate and the number of passed normal packets is in the inverse proportion to the false positive rate. We also analyze the limits of attack detection due to the relation between the false negative rate and the false positive rate. Finally, we propose a solution to minimize the limits of attack detection algorithms by defining the network state using the ratio between the number of packets classified as attack packets and the number of packets classified as normal packets. We find the performance of attack detection algorithm is improved by passing the packets classified as attacks.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.65-72
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• 2020

With the development of information technology and the growth of the scale of system and network, cyber threats and crimes continue to increase. To cope with these threats, cybersecurity training based on actual attacks and defenses is required. However, cybersecurity training requires expert analysis and attack performance, which is inefficient in terms of cost and time. In this paper, we propose a cyber attack simulator that automatically executes attack techniques. This simulator generates attack scenarios by combining attack techniques modeled to be implemented and executes the attack by sequentially executing the derived scenarios. In order to verify the effectiveness of the proposed attack simulator, we experimented by setting an example attack goal and scenarios in a real environment. The attack simulator successfully performed five attack techniques to gain administrator privileges.

• The KIPS Transactions:PartC
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• v.11C no.2
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• pp.183-192
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• 2004

As the use of the Internet has explosively increased, it is likely for the Internet to be exposed to various attacks. Modeling the Internet attacks is essential to simulate the attacks. However, the existing studies on attack modeling have mainly focused on classifying and categorizing the attacks and consequently they are not suitable to representing attack scenarios in the Internet security simulation. In this paper, we introduce the existing methods of attack modeling, and propose an adapted attack modeling to properly express the properties for the Internet security simulator. The adapted attack modeling suggests a solution to the problems of the existing attack tree modelings, such as difficulty of composing complex scenarios ambiguity of attack sequence, lack of system state information. And it can represent simultaneous, precise time-dependent attack, and attack period, which are nearly impossible to be represented in many other existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1462-1470
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• 2013

This paper proposes an SWAD-KNH(Sybil & Wormhole Attack Detection using Key, Neighbor list and Hop count) technique which consists of an SWAD(Sybil & Wormhole Attack Detection) module detecting an Worm attack and a KGDC(Key Generation and Distribution based on Cluster) module generating and an sense node key and a Group key by the cluster and distributing them. The KGDC module generates a group key and an sense node key by using an ECDH algorithm, a hash function, and a key-chain technique and distributes them safely. An SWAD module strengthens the detection of an Sybil attack by accomplishing 2-step key acknowledgement procedure and detects a Wormhole attack by using the number of the common neighbor nodes and hop counts of an source and destination node. As the result of the SWAD-KNH technique shows an Sybil attack detection rate is 91.2% and its average FPR 3.82%, a Wormhole attack detection rate is 90%, and its average FPR 4.64%, Sybil and wormhole attack detection rate and its reliability are improved.