• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.311-316
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• 2016

Network intrusion detection system based on machine learning method such as artificial neural network is quite dependent on the selected features in terms of accuracy and efficiency. Nevertheless, choosing the optimal combination of features, which guarantees accuracy and efficienty, from generally used many features to detect network intrusion requires extensive computing resources. In this paper, we deal with a optimal feature selection problem to determine 6 denial service attacks and normal usage provided by NSL-KDD data. We propose a optimal feature selection algorithm. Proposed algorithm is based on the multi-start local search algorithm, one of representative meta-heuristic algorithm for solving optimization problem. In order to evaluate the performance of our proposed algorithm, comparison with a case of all 41 features used against NSL-KDD data is conducted. In addtion, comparisons between 3 well-known machine learning methods (multi-layer perceptron., Bayes classifier, and Support vector machine) are performed to find a machine learning method which shows the best performance combined with the proposed feature selection method.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.23-34
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• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• Knowledge Management Research
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• v.24 no.3
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• pp.149-172
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• 2023

With the development of information technology, new technologies to be introduced in each industry are continuously increasing. This study aims to verify the influence of ambivalent emotions experienced when encountering new technologies, the coping strategies they induce, and their impact on the decision-making process of technology adoption Specifically, this research investigates the emotions and responses to new technologies in the situational context where service providers must deliver services based on new technology in environments where no such services have been developed previously. Furthermore, it seeks to verify the influence of coping responses on the intention to use services based on new technologies. To this end, this study investigated the ambivalent emotions and coping responses of financial sector workers to new financial services based on metaverse technology. As a result of the analysis ambivalance had a significant effect on all four coping responses (disengagement-oriented coping, denial, indecision and compromise). Among them, denial, which is an inflexible response, and compromise, which is a flexible response, had a significant positive effect on the intention to use, and disengagement-oriented coping and indecision had a significant negative effect on the intention to use. The results of this study confirm the user's metaverse acceptance factor and user-centered influence, and are expected to provide guidelines for the introduction of services to practical workers with academic significance.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.157-165
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• 2024

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7B
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• pp.489-498
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• 2005

A Denial of Sewice (DoS) attack attempts to prevent legitimate users of a sewice from being adequately served by monopolizing networks resources and, eventually, resulting in network or system congestion. This paper proposes a Minority First (MF) gateway, which is capable of guaranteeing the Quality of Service (QoS) of legitimate service traffic under DoS situations. A MF gateway can rapidly determine whether an aggregated flow is a congestion-inducer and can protect the QoS of legitimate traffic by providing high priority service to the legitimate as aggregate flows, and localize network congestion only upon attack traffic by providing low priority to aggregate flows regarded as congestion-inducer. We verify through simulation that the suggested mechanism possesses excellence in that it guarantees the QoS of legitimate traffic not only under a regular DoS occurrence, but also under a Distributed DoS (DDoS) attack which brings about multiple concurrent occurrences of network congestion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.237-240
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• 2011

Voice over Internet Protocol calls using administrative agency to build a national information and communication service, 'C' group, providers, the KT, SK Broadband, LG U+, Samsung SDS, as there are four operators. To prepare for an attack on Voice over Internet Protocol for administrative agency, security is a need for research to support the model. In this paper, the Internet telephone business of Administrative Agency to investigate and analyze the specific security measures to respond. Should set priorities around confidentiality about five security threats from NIS to Study of Voice over Internet Protocol Security Response Model for Administrative Agency. (1) Illegal wiretapping, (2) call interception, (3) service misuse, (4) denial of service attacks, (5) spam attacks, write about and analyze attack scenarios. In this paper, an analysis of protection by security threats and security breaches through a step-by-step system to address the research study is a step-by-step development of the corresponding model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1471-1492
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• 2015

The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain.

• ETRI Journal
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• v.36 no.1
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• pp.51-61
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• 2014

In the Mobile IPv6 (MIPv6) protocol, a mobile node (MN) is a mobile device with a permanent home address (HoA) on its home link. The MN will acquire a care-of address (CoA) when it roams into a foreign link. It then sends a binding update (BU) message to the home agent (HA) and the correspondent node (CN) to inform them of its current CoA so that future data packets destined for its HoA will be forwarded to the CoA. The BU message, however, is vulnerable to different types of security attacks, such as the man-in-the-middle attack, the session hijacking attack, and the denial-of-service attack. The current security protocols in MIPv6 are not able to effectively protect the BU message against these attacks. The private-key-based BU (PKBU) protocol is proposed in this research to overcome the shortcomings of some existing MIPv6 protocols. PKBU incorporates a method to assert the address ownership of the MN, thus allowing the CN to validate that the MN is not a malicious node. The results obtained show that it addresses the security requirements while being able to check the address ownership of the MN. PKBU also incorporates a method to verify the reachability of the MN.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.35-41
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• 2016

Internet of Things (IoT) services are widely used in appliances of daily life and industries. IoT services also provide various conveniences to users and are expected to affect value added of all industries and national competitiveness. However, a variety of security threats are increased in IoT environments and lowers reliability of IoT devices and services that make some obstacles for commercialization. The attacks arising in IoT environments are making industrial and normal life accidents unlike existing information leak and monetary damages, and can expand damage scale of leakage of personal information and privacy more than existing them. To solve these problems, we design a session key based access control scheme for secure communications in IoT environments. The proposed scheme reinforces message security by generating session key between device and access control network system. We analyzed the stability of the proposed access scheme in terms of data forgery and corruption, unauthorized access, information disclosure, privacy violations, and denial of service attacks. And we also evaluated the proposed scheme in terms of permission settings, privacy indemnity, data confidentiality and integrity, authentication, and access control.

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