• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.846-864
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• 2017

Software Defined Network (SDN) realizes management and control over the underlying forwarding device, along with acquisition and analysis of network topology and flow characters through south bridge protocol. Data path Identification (DPID) is the unique identity for managing the underlying device, so forged DPID can be used to attack the link of underlying forwarding devices, as well as carry out DoS over the upper-level controller. This paper proposes a dynamic defense method based on Client-Puzzle model, in which the controller achieves dynamic management over requests from forwarding devices through generating questions with multi-level difficulty. This method can rapidly reduce network load, and at the same time separate attack flow from legal flow, enabling the controller to provide continuous service for legal visit. We conduct experiments on open-source SDN controllers like Fluid and Ryu, the result of which verifies feasibility of this defense method. The experimental result also shows that when cost of controller and forwarding device increases by about 2%-5%, the cost of attacker's CPU increases by near 90%, which greatly raises the attack difficulty for attackers.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.1
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• pp.44-53
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• 2023

Adversarial attacks have received great attentions for their capacity to distract state-of-the-art neural networks by modifying objects in physical domain. Patch-based attack especially have got much attention for its optimization effectiveness and feasible adaptation to any objects to attack neural network-based object detectors. However, despite their strong attack performance, generated patches are strongly perceptible for humans, violating the fundamental assumption of adversarial examples. In this paper, we propose a camouflaged adversarial patch optimization method using military camouflage assessment metrics for naturalistic patch attacks. We also investigate camouflaged attack loss functions, applications of various camouflaged patches on army tank images, and validate the proposed approach with extensive experiments attacking Yolov5 detection model. Our methods produce more natural and realistic looking camouflaged patches while achieving competitive performance.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.127-132
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• 2024

With the rapid evolution of the Internet, the application of artificial intelligence fields is more and more extensive, and the era of AI has come. At the same time, adversarial attacks in the AI field are also frequent. Therefore, the research into adversarial attack security is extremely urgent. An increasing number of researchers are working in this field. We provide a comprehensive review of the theories and methods that enable researchers to enter the field of adversarial attack. This article is according to the "Why? → What? → How?" research line for elaboration. Firstly, we explain the significance of adversarial attack. Then, we introduce the concepts, types, and hazards of adversarial attack. Finally, we review the typical attack algorithms and defense techniques in each application area. Facing the increasingly complex neural network model, this paper focuses on the fields of image, text, and malicious code and focuses on the adversarial attack classifications and methods of these three data types, so that researchers can quickly find their own type of study. At the end of this review, we also raised some discussions and open issues and compared them with other similar reviews.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.679-689
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• 2012

There were clear differences between the DDoS attack on 7th July 2009 and the rest of them prior to the attack. Despite It had emitted relatively small sized packets per infected PC, the attack was very successful making use of HTTP Flooding attack by aggregating small sized packets from the well sized zombie network. As the objective of the attack is not causing permanent damage to the target system but temporal service disruption, one should ensure the availability of the target server by deploying effective defense strategy. In this paper, a novel HTTP based DDoS defense mechanism is introduced with capacity based defense-in-depth strategy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.441-447
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• 2004

Information security simulator is required for the study on the cyber intrusion and defense as information security has been increasingly popular Until now, the main purposes of information security simulation are security estimation of small network as well as performance analysis of information protection systems. However, network simulators that can simulate attacks in a huge network are in needs since large scale internet attacks are very common in these days. In this paper we proposed a simulator design and its implementation details. Our simulator is implemented by expanding the SSFNet program to the client-sewer architecture. A cyber attack scenario used in our simulator is composed by the advanced attack tree model. We analyzed the simulation results to show the correctness of our network defense simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.484-510
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• 2017

Network security is rapidly developing, but so are attack methods. Network worms are one of the most widely used attack methods and have are able to propagate quickly. As an active defense approach to network worms, the honeynet technique has long been limited by the closed architecture of traditional network devices. In this paper, we propose a closed loop defense system of worms based on a Software-Defined Networking (SDN) technology, called Worm-Hunter. The flexibility of SDN in network building is introduced to structure the network infrastructures of Worm-Hunter. By using well-designed flow tables, Worm-Hunter is able to easily deploy different honeynet systems with different network structures and dynamically. When anomalous traffic is detected by the analyzer in Worm-Hunter, it can be redirected into the honeynet and then safely analyzed. Throughout the process, attackers will not be aware that they are caught, and all of the attack behavior is recorded in the system for further analysis. Finally, we verify the system via experiments. The experiments show that Worm-Hunter is able to build multiple honeynet systems on one physical platform. Meanwhile, all of the honeynet systems with the same topology operate without interference.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.75-82
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• 2014

MANET has various types of attacks. In particular, routing attacks using characteristics of movement of nodes and wireless communication is the most threatening because all nodes which configure network perform a function of router which forwards packets. Therefore, mechanisms that detect routing attacks and defense must be applied. In this paper, we proposed hierarchical structure attack detection techniques in order to improve the detection ability against routing attacks. Black hole detection is performed using PIT for monitoring about control packets within cluster and packet information management on the cluster head. Flooding attack prevention is performed using cooperation-based distributed detection technique by member nodes. For this, member node uses NTT for information management of neighbor nodes and threshold whether attack or not receives from cluster head. The performance of attack detection could be further improved by calculating at regular intervals threshold considering the total traffic within cluster in the cluster head.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.64-72
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• 2024

In recent times cyber attackers can use Artificial Intelligence (AI) to boost the sophistication and scope of attacks. On the defense side, AI is used to enhance defense plans, to boost the robustness, flexibility, and efficiency of defense systems, which means adapting to environmental changes to reduce impacts. With increased developments in the field of information and communication technologies, various exploits occur as a danger sign to cyber security and these exploitations are changing rapidly. Cyber criminals use new, sophisticated tactics to boost their attack speed and size. Consequently, there is a need for more flexible, adaptable and strong cyber defense systems that can identify a wide range of threats in real-time. In recent years, the adoption of AI approaches has increased and maintained a vital role in the detection and prevention of cyber threats. In this paper, an Ensemble Deep Restricted Boltzmann Machine (EDRBM) is developed for the classification of cybersecurity threats in case of a large-scale network environment. The EDRBM acts as a classification model that enables the classification of malicious flowsets from the largescale network. The simulation is conducted to test the efficacy of the proposed EDRBM under various malware attacks. The simulation results show that the proposed method achieves higher classification rate in classifying the malware in the flowsets i.e., malicious flowsets than other methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1041-1051
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• 2012

Attack on Cloud Computing, an intensive service solution using network infrastructure recently released, generates service breakdown or intrusive incidents incapacitating developmental platforms, web-based software, or resource services. Therefore, it is needed to conduct research on security for the operational information of three kinds of services (3S': laaS, PaaS, SaaS) supported by the Cloud Computing system and also generated data from the illegal attack on service blocking. This paper aims to build a system providing optimal services as a 4-stage defensive method through the test on the attack and defense of Cloud Computing services. It is a defense policy that conducts 4-stage, orderly and phased access control as follows: controlling the initial access to the network, controlling virtualization services, classifying services for support, and selecting multiple routes. By dispersing the attacks and also monitoring and analyzing to control the access by stage, this study performs defense policy realization and analysis and tests defenses by the types of attack. The research findings will be provided as practical foundational data to realize Cloud Computing service-based defense policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6845-6848
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• 2014

This paper proposes a system design of IDS for detecting and defending against DDoS attacks on a network. The proposed system has three parts; the Alert, Attack Analyzer and Defense agent. When the server resource was reduced too much by incoming traffic, the Alert Agent sends message and traffic information to the Attack Analyzer. The message and traffic to the Attack analyzer include only the sender & receiver address and packet numbers for minimizing the overload of Attack Analyzer. Message Received Attack Analyzer investigates the Message. If the pattern of traffic is the same as the DDoS Style, the Analyzer sends a message to the Defense Agent to block that traffic. In this system, at the serious state of the server-down, the Attack analyzer uncovers the DDoS Attacker and send a message to the Defense Agent to block that traffic. This works for server reactivation as soon as possible.