• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.971-984
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• 2004

In the coming age of information warfare, information security patterns need to be changed such as to the active approach using offensive security mechanisms rather than traditional passive approach just protecting the intrusions. In an active security environment, it is essential that, when detecting an intrusion, the immediate confrontation such as analysing the intrusion situation in realtime, protecting information from the attacks, and even tracing the intruder. This paper presents an active intrusion-confronting system using a fake session and a honeypot. Through the fake session, the attacks like Dos(Denial of Service) and port scan can be intercepted. By monitoring honeypot system, in which the intruders are migrated from the protected system and an intrusion rule manager is being activated, new intrusion rules are created and activated for confronting the next intrusions.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.135-142
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• 2017

DDoS (Distributed Denial of Service) exhausts the target server's resources using the large number of zombie pc, As a result normal users don't access to server. DDoS Attacks steadly increase by many attacker, and almost target of the attack is critical system such as IT Service Provider, Government Agency, Financial Institution. In this paper, We will introduce the CNN (Convolutional Neural Network) of deep learning based real-time detection system for DNS amplification Attack (DNS DDoS Attack). We use the dataset which is mixed with collected data in the real environment in order to overcome existing research limits that use only the data collected in the experiment environment. Also, we build a deep learning model based on Convolutional Neural Network (CNN) that is used in pattern recognition.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.33-40
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• 2007

In this paper, low-rate TCP attack as one of shrew attacks is considered and the scaling based dynamic time warping (S-DTW) algorithm is introduced. The low-rate TCP attack can not be detected by the detection method for the previous flooding DoS/DDoS (Denial of Service/Distirbuted Denial of Service) attacks due to its low average traffic rate. It, however, is a periodic short burst that exploits the homogeneity of the minimum retransmission timeout (RTO) of TCP flows and then some pattern matching mechanisms have been proposed to detect it among legitimate input flows. A DTW mechanism as one of detection approaches has proposed to detect attack input stream consisting of many legitimate or attack flows, and shown a depending method as well. This approach, however, has a problem that legitimate input stream may be caught as an attack one. In addition, it is difficult to decide a threshold for separation between the legitimate and the malicious. Thus, the causes of this problem are analyzed through simulation and the scaling by maximum auto-correlation value is executed before computing the DTW. We also discuss the results on applying various scaling approaches and using standard deviation of input streams monitored.

• Smart Media Journal
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• v.12 no.2
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• pp.66-75
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• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.895-909
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• 2013

Distributed Denial-of-Service (DDoS) attacks towards name servers of the Domain Name System (DNS) have threaten to disrupt this critical service. This paper studies the vulnerability of the cache server to the flooding DNS query traffic. As the resolution service provided by cache server, the incoming DNS requests, even the massive attacking traffic, are maintained in the waiting queue. The sojourn of requests lasts until the corresponding responses are returned from the authoritative server or time out. The victim cache server is thus overloaded by the pounding traffic and thereafter goes down. The impact of such attacks is analyzed via the model of queuing process in both cache server and authoritative server. Some specific limits hold for this practical dual queuing process, such as the limited sojourn time in the queue of cache server and the independence of the two queuing processes. The analytical results are presented to evaluate the impact of DDoS attacks on cache server. Finally, numerical results are provided for further analysis.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.106-106
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• 2004

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.59.1-59
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• 2001

The attackers on Internet-connected systems we are seeing today are more serious and more technically complex than those in the past. Computer security incidents are different from many other types of crimes because detection is unusually difficult. So, network security managers need a IDS and Firewall. IDS (Intrusion Detection System) monitors system activities to identify unauthorized use, misuse or abuse of computer and network system. It accomplishes these by collecting information from a variety of systems and network resources and then analyzing the information for symptoms of security problems. A Firewall is a way to restrict access between the Internet and internal network. Usually, the input ...

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.225-226
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• 2011

IP traceback is an solution for Defending against distributed denial-of-service attacks, the Fragment Marking Scheme is the famous method for IP traceback problem. In this paper, we are interested in understanding the reconstruction process at the victim of Fragment Marking Scheme deeply and make us more clearly about its limitation based on some papers mentioning it.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9B
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• pp.931-938
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• 2009

Recently, Holbl et al. proposed an improvement to Peyravian-Jeffries's password-based authentication protocol to overcome some security flaws. However, Munilla et al. showed that Holbl et al.'s improvement is still vulnerable to off-line password guessing attack. In this paper, we provide a secure password-based authentication protocol which gets rid of the security flaws of Holbl et al.'s protocol.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.89-92
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• 1999

This paper describes on the threats such as IP spoofing, denial of service, and ILMI based attack etc. for IP over ATM network. Especially we discuss on the threats due to ATM characteristics that are VC stealing, multiparty and multi-connection call. Also we investigate on the threats of ATM based MPLS network. Finally we discuss and suggest the various solutions of ATM security.