• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.252-255
• /
• 2002

As more critical services are provided in the internet, the risk to these services from malicious users increases. Several networks have experienced problems like Denial of Service(DoS) attacks recently. We analyse a network-based denial of service attack, which is called SYM flooding, to TCP-based networks. It occurs by an attacker who sends TCP connection requests with spoofed source address to a target system. Each request causes the targeted system to send instantly data packets out of a limited pool of resources. Then the target system's resources are exhausted and incoming TCP port connections can not be established. The paper is concerned with a detailed analysis of TCP SYN flooding denial of service attack. In this paper, we propose a Real Time Scan Detector(RTSD) mechanism and evaluate it\`s Performance.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.12
• /
• pp.1849-1856
• /
• 2013

DOS attack, the short of Denial of Service attack is an internet intrusion technique which harasses service availability of legitimate users. To respond the DDoS attack, a lot of methods focusing attack source, target and intermediate network, have been proposed, but there have not been a clear solution. In this paper, we purpose the prevention of malicious activity and early detection of DDoS attack by detecting and removing the activity of botnets, or other malicious codes. For the purpose, the proposed method monitors the network traffic, especially DSN traffic, which is originated from botnets or malicious codes.

• Journal of Korea Multimedia Society
• /
• v.18 no.1
• /
• pp.35-41
• /
• 2015

SDN(Software Defined Networking) has been considered as a new future computer network architecture and DDoS(Distributed Denial of Service) is the biggest threat in the network security. In SDN architecture, we present the technique to defend the DDoS SYN Flooding attack that is one of the DDoS attack method. First, we monitor the Backlog queue in order to reduce the unnecessary monitoring resources. If the Backlog queue of the certain server is occupied over 70%, the sFlow performs packet sampling with the server address as the destination address. To distinguish between the attacker and the normal user, we use the source address. We decide the SYN packet threshold using the remaining Backlog queue that possible to allow the number of connections. If certain sources address send the SYN packet over the threshold, we judge that this address is attacker. The controller will modify the flow table entry to block attack traffics. By using this method, we reduce the resource consumption about the unnecessary monitoring and the protection range is expanded to all switches. The result achieved from our experiment show that we can prevent the SYN Flooding attack before the Backlog queue is fully occupied.

• Journal of Convergence for Information Technology
• /
• v.9 no.9
• /
• pp.52-57
• /
• 2019

DNS stands for 'Domain Name System' and uses IP addresses to identify devices connected to the network on the network. IP is a protocol that registers and manages aliases such as IPs because it is difficult for general users to remember. In recent years, the abuse of such DNS is increasing abroad, and behind the scenes, called 'DNS pionage,' are developing and evolving new rules and malware. DNSpionage attack is abusing DNS system such as Increasing hacking success rate, leading to fake sites, changing or forged data. As a result it is increasing the damage cases. As the global DNS system is expanding to the extent that it is out of control. Therefore, in this research, the countermeasures of DNSpionage attack is proposed to contribute to build a secure and efficient DNS system.

• Convergence Security Journal
• /
• v.18 no.5_1
• /
• pp.33-43
• /
• 2018

In this paper, we want to solve the problems that users want to search the progress of attack, continuity of attack, association between attackers and victims, blocking priority and countermeasures by using visualization interface with multi-rotational axis and radial axis structure. It is possible to effectively monitor and track security events by arranging a time series event based on a multi-rotational axis structured by an event generation order, a subject of an event, an event type, and an emission axis, which is an objective time indicating progress of individual events. The proposed interface is a practical visualization interface that can apply attack blocking and defense measures by providing the progress and progress of the whole attack, the details and continuity of individual attacks, and the relationship between attacker and victim in one screen.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.12
• /
• pp.4909-4926
• /
• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.6
• /
• pp.1657-1673
• /
• 2023

With the advancement of information technology, criminals employ multiple cyberspaces to promote cybercrime. To combat cybercrime and cyber dangers, banks and financial institutions use artificial intelligence (AI). AI technologies assist the banking sector to develop and grow in many ways. Transparency and explanation of AI's ability are required to preserve trust. Deep learning protects client behavior and interest data. Deep learning techniques may anticipate cyber-attack behavior, allowing for secure banking transactions. This proposed approach is based on a user-centric design that safeguards people's private data over banking. Here, initially, the attack data can be generated over banking transactions. Routing is done for the configuration of the nodes. Then, the obtained data can be preprocessed for removing the errors. Followed by hierarchical network feature extraction can be used to identify the abnormal features related to the attack. Finally, the user data can be protected and the malicious attack in the transmission route can be identified by using the Wrapper stepwise ResNet classifier. The proposed work outperforms other techniques in terms of attack detection and accuracy, and the findings are depicted in the graphical format by employing the Python tool.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.2
• /
• pp.193-200
• /
• 2023

Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.4
• /
• pp.747-754
• /
• 2016

DHCP(Dynamic Host Configuration Protocol) is a protocol for efficiency and convenience of the IP address management. DHCP automatically assigns an IP address and configuration information needed to run the TCP/IP communication to individual host in the network. However, existing DHCP is vulnerable for network attack such as DHCP spoofing, release attack because there is no mutual authentication systems between server and client. To solve this problem, we have designed a new DHCP protocol supporting the following features: First, ECDH(Elliptic Curve Diffie-Hellman) is used to create session key and ECDSA(Elliptic Curve Digital Signature Algorithm) is used for mutual authentication between server and client. Also this protocol ensures integrity of message by adding a HMAC(Hash-based Message Authentication Code) on the message. And replay attacks can be prevented by using a Nonce. As a result, The receiver can prevent the network attack by discarding the received message from unauthorized host.