• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.1-10
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• 2021

The purpose of the study is to contribute to the positive development of blockchain technology by providing data to examine security vulnerabilities and threats to blockchain-based services and review countermeasures. The findings of this study are as follows. Threats to the security of blockchain-based services can be classified into application security threats, smart contract security threats, and network (P2P) security threats. First, application security threats include wallet theft (e-wallet stealing), double spending (double payment attack), and cryptojacking (mining malware infection). Second, smart contract security threats are divided into reentrancy attacks, replay attacks, and balance increasing attacks. Third, network (P2P) security threats are divided into the 51% control attack, Sybil attack, balance attack, eclipse attack (spread false information attack), selfish mining (selfish mining monopoly), block withholding attack, DDoS attack (distributed service denial attack) and DNS/BGP hijacks. Through this study, it is possible to discuss the future plans of the blockchain technology-based ecosystem through understanding the functional characteristics of transparency or some privacy that can be obtained within the blockchain. It also supports effective coping with various security threats.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.23-33
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• 2004

In this paper, we propose a novel traffic measurement based detection of network attack symptoms on high speed Internet backbone links. In order to do so, we characterize the traffic patterns from the normal and the network attacks appeared on Internet backbone links, and we derive two efficient measures for representing the network attack symptoms at aggregate traffic level. The two measures are the power spectrum and the ratio of packet counts to traffic volume of the aggregate traffic. And, we propose a new methodology to detect networks attack symptoms by measuring those traffic measures. Experimental results show that the proposed scheme can detect the network attack symptoms very exactly and quickly. Unlike existing methods based on Individual packets or flows, since the proposed method is operated on the aggregate traffic level. the computational complexity can be significantly reduced and applicable to high speed Internet backbone links.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.111-119
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• 2023

Mobile Ad-hoc Network (MANET) is an infrastructure-less network that can configure itself without any centralized management. The topology of MANET changes dynamically which makes it open for new nodes to join it easily. The openness area of MANET makes it very vulnerable to different types of attacks. One of the most dangerous attacks is the Resource Consumption Attack (RCA). In this type of attack, the attacker consumes the normal node energy by flooding it with bogus packets. Routing in MANET is susceptible to RCA and this is a crucial issue that deserves to be studied and solved. Therefore, the main objective of this paper is to study the impact of RCA on two routing protocols namely, Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR); as a try to find the most resistant routing protocol to such attack. The contribution of this paper is a new RCA model (RCAM) which applies RCA on the two chosen routing protocols using the NS-2 simulator.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.112-118
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• 2023

As technology advances, the need for enhanced preparedness against cyber-attacks becomes an increasingly critical problem. Therefore, it is imperative to consider various circumstances and to prepare for cyber-attack strategic technology. This paper proposes a method to solve network security problems by applying reinforcement learning to cyber-security. In general, traditional static cyber-security methods have difficulty effectively responding to modern dynamic attack patterns. To address this, we implement cyber-attack scenarios such as 'Tiny Alpha' and 'Small Alpha' and evaluate the performance of various reinforcement learning methods using Network Attack Simulator, which is a cyber-attack simulation environment based on the gymnasium (formerly Open AI gym) interface. In addition, we experimented with different RL algorithms such as value-based methods (Q-Learning, Deep-Q-Network, and Double Deep-Q-Network) and policy-based methods (Actor-Critic). As a result, we observed that value-based methods with discrete action spaces consistently outperformed policy-based methods with continuous action spaces, demonstrating a performance difference ranging from a minimum of 20.9% to a maximum of 53.2%. This result shows that the scheme not only suggests opportunities for enhancing cybersecurity strategies, but also indicates potential applications in cyber-security education and system validation across a large number of domains such as military, government, and corporate sectors.

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

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.540-543
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• 2004

Address Resolution Protocol (ARP) cache poisoning is a MAC layer attack that can only be carried out when an attacker is connected to the same local network as the target machines. ARP is not a new problem, but wireless network introduces a new attack point and more vulnerable to the attack. The attack on wireless network cannot be detected by current detection tool installed on wired network. In order to detect the ARP poisoning attack, there must be a ARP poisoning detection tool for wireless LAN environment. This paper proposes linux-based ARP poisoning detection system equipped with wireless LAN card and Host AP device driver

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3671-3689
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• 2019

Software defined networking brings unique security risks such as control plane saturation attack while enhancing the performance of wireless sensor networks. The attack is a new type of distributed denial of service (DDoS) attack, which is easy to launch. However, it is difficult to detect and hard to defend. In response to this, the attack threat model is discussed firstly, and then a DDoS attack prevention extension, called FuzzyGuard, is proposed. In FuzzyGuard, a control network with both the protection of data flow and the convergence of attack flow is constructed in the data plane by using the idea of independent routing control flow. Then, the attack detection is implemented by fuzzy inference method to output the current security state of the network. Different probabilistic suppression modes are adopted subsequently to deal with the attack flow to cost-effectively reduce the impact of the attack on the network. The prototype is implemented on SDN-WISE and the simulation experiment is carried out. The evaluation results show that FuzzyGuard could effectively protect the normal forwarding of data flow in the attacked state and has a good defensive effect on the control plane saturation attack with lower resource requirements.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.24-30
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• 2020

As the number of internet-connected appliances and the variety of IoT services are rapidly increasing, it is hard to protect IT assets with traditional network security techniques. Most traditional network log analysis systems use rule based mechanisms to reduce the raw logs. But using predefined rules can't detect new attack patterns. So, there is a need for a mechanism to reduce congested raw logs and detect new attack patterns. This paper suggests enterprise security management for IoT services using graph and network measures. We model an event network based on a graph of interconnected logs between network devices and IoT gateways. And we suggest a network clustering algorithm that estimates the attack probability of log clusters and detects new attack patterns.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.48-59
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• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.10
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• pp.67-78
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• 2003

As optical network technology advances and high bandwidth Internet is demanded for the exponential growth of internet traffic volumes, the Dense-Wavelength Division Multiplexing (DWDM) networks have been widely accepted as a promising approach to the Next Generation Optical Internet (NGOI) backbone networks for nation wide or global coverage. Important issues in the NGOI based on DWDM networks are the Routing and Wavelength Assignment(RWA) problem and survivability. Especially, fault/attack detection, localization and recovery schemes in All Optical Transport Network(AOTN) is one of the most important issues because a short service disruption in DWDM networks carrying extremely high data rates causes loss of vast traffic volumes. In this paper, we suggest a fault/attack management model for NGOI through analyzing fault/attack vulnerability of various optical backbone network devices and propose fault/attack recovery procedure considering Extended-LMP(Link Management Protocol) and RSVP-TE+(Resource Reservation Protocol-Traffic Engineering) as control protocols in IP/GMPLS over DWDM.