• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.73-82
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• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.975-983
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• 1998

In these days, information communication systems are based on both open distributed computing technologies and object-oriented techniques like inheritance, encapsulation and object reuse to support various system configuration and application. As information systems are interconnected through unsecure networks, the need for the secure information exchange is more critical than before. In this paper, we have designed and implemented a transparent CORBA-basce Security infrastructure with authentication, security context association, access control and security information management to support a secure applications in distributed object environment. SESAME Ver. 4 was adopted as an external security service to manage user privilege attributes and to distribute keys for data encryption, decryption and integrity. Using filter and transformer with an interface to Object Request Broker, it provides a transparent security service to applications. The filter objects are special classes that allow additional parameters to be inserted into messages before they are sent and removed just after they are received. The transformer objects are special classes that allow direct access to the byte stream of every messages for encryption and decryption before it is sent and just after it is received. This study is to implement the access control interceptor(ACI) and the secure invocation interceptor(SII) of secure ORB defined in CORBA using filter and transformer.

• Management & Information Systems Review
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• v.29 no.4
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• pp.123-142
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• 2010

This study suggest that firms can use online brand communities as an IMC tool to achieve high brand loyalty through marketer-controlled or loyal customer-controlled brand contacts. In this perspective, the online brand community as a marketing communication tool can help the firm in eliciting favorable responses from customers. This study finds that an online brand community, as a critical marketing promotion tool, helps a firm elicit favorable relationship with customers and build strong brand loyalty. In particular, this study suggests several important theoretical and managerial implications. First, this study confirm that "advertising usefulness" is the most powerful and important factor that affects cgerial 's positive emotionomehile "sales promotion usefulness" impacmehin "interactivity" but dies not impacmhin "cgerial iexperience"ltyevent usefulness" impacmehin "cgerial iexperience"but dies not impacmhin "interactivity." In addition, "cgerial iexperience" signifn "itly impacmehin "cgerial -to-cgerial iinteractivity." This indicates that online environment provides participapacmwith a fun and exciting environment. In that sense, enhancing the online brand community experiencemwould be a critical factor for building strong brand. Thi", mword of mouth can play a riclly important role in making many cgerial s to trust brand and to enhance online brand community loyalty. Web users are becoming web authoore owning and creating content limited only by their imaginations.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.2
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• pp.33-40
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• 2018

In an environment with a large network bandwidth, maximizing bandwidth utilization is an important issue to increase transmission efficiency. End-to-end transfer efficiency is significantly influenced by factors such as network, data transfer nodes, and intranet network security policies. Science DMZ is an innovative network architecture that maximizes transfer performance through optimal solution of these complex components. Among these, the data transfer node is a key factor that greatly affects the transfer performance depending on storage, network interface, operating system, and transfer application tool. However, tuning parameters constituting a data transfer node must be performed to provide high transfer efficiency. In this paper, we propose a method to enhance performance through tuning parameters of 100Gbps data transfer node. With experiment result, we confirmed that the transmission efficiency can be improved greatly in 100Gbps network environment through the tuning of Jumbo frame and CPU governor. The network performance test through Iperf showed improvement of 300% compared to the default state and NVMe SSD showed 140% performance improvement compared to hard disk.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.473-480
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• 2005

We can obtain useful information by deploying large scale sensor networks in various situations. Security is also a major concern in sensor networks, and we need to establish pairwise keys between sensor nodes for secure communication. In this paper, we propose new pairwise key establishment mechanism based on clustering and polynomial sharing. In the mechanism, we divide the network field into clusters, and based on the polynomial-based key distribution mechanism we create bivariate Polynomials and assign unique polynomial to each cluster. Each pair of sensor nodes located in the same cluster can compute their own pairwise keys through assigned polynomial shares from the same polynomial. Also, in our proposed scheme, sensors, which are in each other's transmission range and located in different clusters, can establish path key through their clusterheads. However, path key establishment can increase the network overhead. The number of the path keys and tine for path key establishment of our scheme depend on the number of sensors, cluster size, sensor density and sensor transmission range. The simulation result indicates that these schemes can achieve better performance if suitable conditions are met.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.9
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• pp.369-380
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• 2013

Recently, role-based distributed system models have been proposed to support adaptive interactions in ubiquitous application environment. A Role-based distributed model regards an application as an organization composed of roles, and separate players running role processes from the roles. When an application is running, it binds a role with a player, and the player runs dynamically assigned role processes provided by an application for supporting adaptability. However, there has not been much attention on researches about development and runtime environment for role-based distributed systems. In this paper we suggest an application framework as an environment for developing and executing role-base distributed systems. The application framework is divided into two parts: an organization framework to manage and construct an organization composed of roles necessary in the application, and a player framework to provide running environment for players. In this paper, we focus on the organization framework which supports the creation and management of organizations, directory service for players and allocation of players to roles, and message brokering between roles and players. The proposed framework makes developers to be able to develop highly adaptive distributed systems in the ubiquitous environment.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.377-384
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• 2017

The performance improvement of a single core processor has reached its limit since the circuit density cannot be increased any longer due to overheating. Therefore, the multicore and manycore architectures have emerged as viable approaches and parallel programming becomes more important. Haskell, a purely functional language, is getting popular in this situation since it naturally supports parallel programming owing to its beneficial features including the implicit parallelism in evaluating expressions and the monadic tools supporting parallel constructs. However, the performance of Haskell parallel programs is strongly influenced by the performance of the run-time system including the garbage collector. Though a memory profiling tool namely GC-tune has been suggested, we need a more systematic way to use this tool. Since GC-tune finds the optimal memory size by executing the target program with all the different possible GC options, the GC-tuning time takes too long. This paper suggests a basic divide-and-conquer method to reduce the number of GC-tune executions by reducing the search area by one-quarter for every searching step. Applying this method to two parallel programs, a maximally independent set and a K-means programs, the memory tuning time is reduced by 7.78 times with accuracy 98% on average.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.281-288
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• 2017

In Smart-cities, various types of integrated services must be linked to provide services to applications. Therefore, flexibility must be ensured between services so that various services can be efficiently provided. In order to secure the flexibility among services, it is very important to have a function to dynamically discover and invoke a desired service by searching for a semantic service by reflecting a recognized context through real-time context-aware in smart-cities. To date, quite a number of semantic service discovery techniques have been developed. However, they have not been verified as suitable for use in the smart-city domain. In this study, we tried to verify the existing ones to use a suitable one. We tested most of existing semantic service discovery techniques, but we found that none of them is suitable to our research. Therefore, we developed our own semantic service discovery technique. This paper introduces our work and presents the performance evaluation results that demonstrate that our developed works well and show good performance. For the performance evaluation, the experimental system was actually constructed and the real performance was measured. In the experiment, we implemented the semantic service discovery scenario that dynamically searches and calls the services needed to provide fire accident management services in smart cities.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.57-64
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• 2017

Short message service (SMS) is one of the most important communication methods for people who use mobile phones. However, illegal advertising spam messages exploit people because they can be used without the need for friend registration. Recently, spam message filtering systems that use machine learning have been developed, but they have some disadvantages such as requiring many calculations. In this paper, we implemented a spam message filtering system using the set-based POI search algorithm and sentence similarity without servers. This algorithm can judge whether the input query is a spam message or not using only letter composition without any server computing. Therefore, we can filter the spam message although the input text message has been intentionally modified. We added a specific preprocessing option which aims to enable spam filtering. Based on the experimental results, we observe that our spam message filtering system shows better performance than the original set-based POI search algorithm. We evaluate the proposed system through extensive simulation. According to the simulation results, the proposed system can filter the text message and show high accuracy performance against the text message which cannot be filtered by the 3 major telecom companies.