• Convergence Security Journal
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• v.15 no.2
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• pp.43-55
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• 2015

Security infrastructure of Educational Network responds to threats by collecting and analyzing security events from various information protection system based on the integrated management system. Even if this system provides useful and detailed information to the administrator, there are some problems that this system does not provide effective response process and management systems for various threatening situations and the simultaneous threat processes. To solve this problem, we propose and develop security agents that enable the administrator to effectively manage integrated security for Educational Network. The proposed solution provides the administrator with efficient management techniques and process scheduling for various security events so that the administrator can response promptly to problems with the initial threat to Educational Network.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.83-90
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• 2008

We introduce the coordination among the intrusion detection agents by BBA(BlackBoard Architecture) that belongs to the field of distributed artificial intelligence. The system which uses BBA for the coordination can be easily expanded by adding new agents and increasing the number of BB(BlackBoard) levels. Several simulation tests performed on the targer network will illustrate our techniques. And this paper applies PBN(Policy-Based Network) to reduce the false positives that is one of the main problems of IDS. The performance obtained from the coordination of intrusion detection agent with PBN is compared against the corresponding non PBN type intrusion detection agent. The application of the research results lies in the experimentation of the various security policies according to the network types in selecting the best security policy that is most suitable for a given network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1228-1237
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• 1992

Network management represents those activities which control and moitor the use of resources. Remote delegation model supports flexible and effective distribution of management functions among managers and agents, and it may cause an reliable network management in a relatively complex and high-speed networks. in this model, managers delegate to agents execution of management programs as prescribed in a management scripting language. In addition, primitives included in the management programs enable agents to monitor and control localmanaged objects effectively. We suggest management algorithms in which management scripts are delegated from managers to agents and partiality implement OSI fault management. This mans gement algorithm can effectively support delegation and control concurrent accesses to management information. Moreover, it can be easily translated into object-based concurrent programming language: ABCL. In this paper, we will scrutinize some essential aspects of this management.

• Journal of Information Technology Services
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• v.18 no.3
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• pp.17-35
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• 2019

Call centers do not simply play a role of responding to customers' calls, but they have developed into a core unit for maintaining competitiveness through services, marketing, or sales. Since the service quality of call centers heavily affects customer satisfaction, organizations have focused on enhancing it by reducing waiting time and increasing service level. One of the techniques, which improve the service quality of call centers, is to employ multi-skilled agents that can handle more than one type of calls. This study deals with three issues relevant to multi-skilled agents. First, we analyze how the way of allocating a specific group of agents to a set of skills affects the performance of call centers. Secondly, we investigate the relationship between the number of multi-skilled agents and the performance of call centers. Finally, we examine the impact of agent selection rules on the performance of call centers. Two selection rules are compared : the first rule is to assign a call to any available agent at random while the other rule is to assign a call preferably to single-skilled agents over multi-skilled agents when applicable. Based on simulation experiments, we suggest three implications. First, as the length of cycles in the agent-skill configuration network becomes longer, call centers achieve higher service level and shorter waiting time. Secondly, simulation results show that as the portion of multi-skilled agents increases, the performance of call centers improves. However, most of the improvement is attained when the portion of multi-skilled agents is relatively low. Finally, the agent selection rules do not significantly affect the call centers' performance, but the rule of preferring single-skilled agents tends to distribute the workload among agents more equally.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1332-1341
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• 1999

Rapid expansion of network and increment of computer system access cause computer security to be an important issue. Hence, the researches in intrusion detection system(IDS)are active to reduce the risk from hackers. Considering IDS, we propose a new IDS model(DABIDS : Distributed Agent Based Intelligent intrusion Detection System) based on distributed intrusion detecting agents. The DABIDS dynamically collects intrusion behavior knowledge from each agents when some doubtable behaviors of users are detected and make new agents codes using intrusion scenario data base, and broadcast the detector codes to the distributed intrusion detecting agent of all node. This DABIDS can efficiently solve the problem to reduce the overhead for training detecting agent for intrusion behavior patterns.

• Educational Technology International
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• v.6 no.1
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• pp.65-79
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• 2005

In a widely distributed environment, many occasions arise when people need to filter informationwith email clients. The existing information agents such as Maxims and Message Assistant have capabilities of filtering email messages either by an autonomous agent or by user-defined rules. FlexMA, a variation of FAMES (Flexible Asynchronous Messaging System) is proposed as an information filtering agent. Agents in our system can be scaled up to adapt user's various demands by controlling messages delivered among heterogeneous email clients. Several functionalities are split into each agent in terms of component configuration with the addition of multiple agents'cooperation and negotiation. User-defined rules are collected and executed by these agents in a semi-autonomous manner. This paper demonstrates how this design is feasible in a flexible message system.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.45-54
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• 2007

As one of the most threatening attacks, DDoS attack makes distributed multiple agents consume some critical resources at the target within the short time, thus the extent and scope of damage is serious. Against the problems, the existing defenses focus on detection, traceback (identification), and filtering. Especially, in the hierarchical networks, the traffic congestion of a specific node could incur the normal traffic congestion of overall lower nodes, and also block the control traffic for notifying the attack detection and identifying the attack agents. In this paper, we introduce a DDoS attack tolerant network structure using a hierarchical overlay for hierarchical networks, which can convey the control traffic for defense such as the notification for attack detection and identification, and detour the normal traffic before getting rid of attack agents. Lastly, we analyze the overhead of overlay construction, the possibility of speedy detection notification, and the extent of normal traffic transmission in the attack case through simulation.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.89-96
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• 2001

Agent-mediated electronic markets have been a grow-ing area of agent research and developmen tin recent year. There exist a lot of e-commerce sites on the In-ternet(e.g. Priceline, com, Amazon, com etc). These e-commerce site have proposed new business models for effective and efficient commerce activity. Intelli-gent agents have been studied very widely in the field of artificial intelligence, For purpose of this paper, an agent can act autonomously and collaboratively in a network environment on behalf of its users. It is hard for people to effectively and efficiently monitor, buy, and sell at multiple e-commerce sites. If we intro-duce agent technologies into e-commerce systems, we can expect to further enhance the intelligence of their support. In this paper, we propose a new coopera-tion mechanism among seller agents based on exchang-ing their goods in our agent-mediated electronic market system. G-Commerce. On G-Commerce, seller agents and buyer agents negotiate with each other. In our model, seller agents cooperatively negotiate in order to effectively sell goods in stock. Buyer agents coopera-tively form coalitions in order to buy goods based an discount proices. Seller agent's negotiation goods. Our current experiments show that exchanging mechanism enables seller agents to effectively sell goods in stock. Also, we present the Pareto optimality of our exchang-ing mechanism.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.133-136
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• 2000

In this paper, a new service architecture for IP Telephony, based on the ITU-T standard H.323［1］, is proposed. This architecture uses mobile Agents and existing architectural concepts taken from Intelligent Network［IN］. This IP service architecture enables telecom services deployed through mobile service agents on a per user basis, which results in several advantages when compared to centralized service architecture. The paper demonstrates that the flexible and extensible architecture can accommodate a wide variety of future services.