• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1187-1190
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• 2005

인터넷 토폴로지 생성 기법에 대하여 많은 연구가 진행되고 있다. 이는 인터넷 토폴로지가 라우팅, 멀티캐스트, 프로토콜 등의 성능과 사이버 테러 공격에 대한 분석 및 방어체계와 밀접한 관계가 있기 때문이다. 토폴로지를 생성하는 GT-ITM[5], INET-3.0[6] 등은 Autonomous System (AS) 노드들로 이루어진 네트워크 토폴로지를 생성한다. 즉, 이들 도구들은 AS 가 노드인 토폴로지를 생성하며, AS 내의 네트워크에 대해서는 표현하지 않는다. 이에, 본 논문에서는 대규모 네트워크의 시뮬레이션을 위한 토폴로지를 구성하는 데 필요한 PoP (Presence of Point), ISP(Internet Service Provider) 등 하위 레벨의 토폴로지를 자동 생성함으로써 네트워크 토폴로지를 표현하는 방법을 제안한다. 본 연구에서 제안하는 방법은 서로 다른 특성을 가진 하부 서브넷을 가지고 있으며 hierarchy 를 반영한 토폴로지를 생성할 수 있다는 장점을 가지고 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4701-4719
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• 2015

A Mobile Ad hoc Network (MANET) consists of mobile nodes which co-operate to forward each other's packets without the presence of any centralized authority. Due to this lack of centralized monitoring authority, MANETs have become vulnerable to various kinds of routing misbehaviour. Sometimes, nodes exhibit non-cooperating behaviour for conserving their own resources and exploiting others' by relaying their traffic. A node may even drop packets of other nodes in the guise of forwarding them. This paper proposes an efficient Reputation and Collaboration technique through route-request for handling such misbehaving nodes. It lays emphasis not only on direct observation but also considers the opinion of other nodes about misbehaving nodes in the network. Unlike existing schemes which generate separate messages for spreading second-hand information in the network, nodes purvey their opinion through route-request packet. Simulation studies reveal that the proposed scheme significantly improves the network performance by efficiently handling the misbehaving nodes in the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3414-3434
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• 2016

Classical key generation is complicated to update and key distribution generally requires fixed infrastructures. In order to eliminate these restrictions researchers have focused much attention on physical-layer (PHY-layer) based key generation methods. In this paper, we present a PHY-layer fingerprints based fuzzy key generation scheme, which works to prevent primary user emulation (PUE) attacks and spectrum sensing data falsification (SSDF) attacks, with multi-node collaborative defense strategies. We also propose two algorithms, the EA algorithm and the TA algorithm, to defend against eavesdropping attacks and tampering attacks in mobile cognitive radio networks (CRNs). We give security analyses of these algorithms in both the spatial and temporal domains, and prove the upper bound of the entropy loss in theory. We present a simulation result based on a MIMO-OFDM communication system which shows that the channel response characteristics received by legitimates tend to be consistent and phase characteristics are much more robust for key generation in mobile CRNs. In addition, NIST statistical tests show that the generated key in our proposed approach is secure and reliable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2370-2387
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• 2012

A new security management model based on Rough set and Bayesian learner is proposed in the paper. The model focuses on finding out malicious nodes and getting them under control. The degree of dissatisfaction (DoD) is defined as the probability that a node belongs to the malicious node set. Based on transaction history records local DoD (LDoD) is calculated. And recommended DoD (RDoD) is calculated based on feedbacks on recommendations (FBRs). According to the DoD, nodes are classified and controlled. In order to improve computation accuracy and efficiency of the probability, we employ Rough set combined with Bayesian learner. For the reason that in some cases, the corresponding probability result can be determined according to only one or two attribute values, the Rough set module is used; And in other cases, the probability is computed by Bayesian learner. Compared with the existing trust model, the simulation results demonstrate that the model can obtain higher examination rate of malicious nodes and achieve the higher transaction success rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1571-1589
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• 2016

Nodes in MANETs are battery powered which makes energy an invaluable resource. In OLSR, MPRs are special nodes that are selected by other nodes to relay their data/control traffic which may lead to high energy consumption of MPR nodes. Therefore, employing energy efficient MPR selection mechanism is imperative to ensure prolonged network lifetime. However, misbehaving MPR nodes tend to preserve their energy by dropping packets of other nodes instead of forwarding them. This leads to huge energy loss and performance degradation of existing energy efficient MPR selection schemes. This paper proposes an energy efficient secure MPR selection (ES-MPR) technique that takes into account both energy and security metrics for MPR selection. It introduces the concept of 'Composite Eligibility Index' (CEI) to examine the eligibility of a node for being selected as an MPR. CEI is used in conjunction with willingness to provide distinct selection parameters for Flooding and Routing MPRs. Simulation studies reveal the efficiency of ES-MPR in selection of energy efficient secure and stable MPRs, in turn, prolonging the network operational lifetime.

• 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.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5260-5275
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• 2019

In the process of constructing the traditional offensive and defensive game theory model, these are some shortages for considering the dynamic change of security risk problem. By analysing the critical indicators of the incomplete information game theory model, incomplete information attack and defense game theory model and the mathematical engineering method for solving Bayes-Nash equilibrium, the risk-averse income function for information assets is summarized as the problem of maximising the return of the equilibrium point. To obtain the functional relationship between the optimal strategy combination of the offense and defense and the information asset security probability and risk probability. At the same time, the offensive and defensive examples are used to visually analyse and demonstrate the incomplete information game and the Harsanyi conversion method. First, the incomplete information game and the Harsanyi conversion problem is discussed through the attack and defense examples and using the game tree. Then the strategy expression of incomplete information static game and the engineering mathematics method of Bayes-Nash equilibrium are given. After that, it focuses on the offensive and defensive game problem of unsafe information network based on risk aversion. The problem of attack and defense is obtained by the issue of maximizing utility, and then the Bayes-Nash equilibrium of offense and defense game is carried out around the security risk of assets. Finally, the application model in network security penetration and defense is analyzed by designing a simulation example of attack and defense penetration. The analysis results show that the constructed income function model is feasible and practical.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.101-115
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• 2011

A botnet is a huge network of hacked zombie PCs. Recognizing the fact that the majority of email spam is sent out by botnets, a system that is capable of detecting botnets and zombie PCS will be designed in this study by analyzing email spam. In this study, spam data collected in "an email spam trail system", Korea's national spam collection system, were used for analysis. In this study, we classified the spam groups by the URLs or attached files, and we measured how much the group has the characteristics of botnet and how much the IPs have the characteristics of zombie PC. Through the simulation result in this study, we could extract 16,030 zombie suspected PCs for one hours and it was verified that email spam can provide considerably useful information in tracing zombie PCs.

• Journal of Internet Computing and Services
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• v.6 no.1
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• pp.27-38
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• 2005

Recently, the rapidly development of computing environments and the spread of Internet make possible to obtain and use of information easily. Immediately, by opposition function the Hacker's unlawful intrusion and threats rise for network environments as time goes on. Specially, the internet consists of Unix and TCP/IP had many vulnerability. the security techniques of authentication and access controls cannot adequate to solve security problem, thus IDS developed with 2nd defence line. In this paper, intrusion detection method using Bayesian Networks estimated probability values of behavior contexts based on Bayes theory. The contexts of behaviors or events represents Bayesian Networks of graphic types. We profiled concisely normal behaviors using behavior context. And this method be able to detect new intrusions or modificated intrusions. We had simulation using DARPA 2000 Intrusion Data.