• KIPS Transactions on Computer and Communication Systems
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• v.7 no.10
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• pp.251-258
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• 2018

Ransomware, a malicious software that requires a ransom by encrypting a file, is becoming more threatening with its rapid propagation and intelligence. Rapid detection and risk analysis are required, but real-time analysis and reporting are lacking. In this paper, we propose a ransomware infection detection system using social big data mining technology to enable real-time analysis. The system analyzes the twitter stream in real time and crawls tweets with keywords related to ransomware. It also extracts keywords related to ransomware by crawling the news server through the news feed parser and extracts news or statistical data on the servers of the security company or search engine. The collected data is analyzed by data mining algorithms. By comparing the number of related tweets, google trends (statistical information), and articles related wannacry and locky ransomware infection spreading in 2017, we show that our system has the possibility of ransomware infection detection using tweets. Moreover, the performance of proposed system is shown through entropy and chi-square analysis.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.1-9
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• 2002

Video server which stores video streams should serve more users with the requested streams rapidly, satisfying their time constraints. In this paper, we propose the storage system that does not only maintain fast responses but also increase the number of users supported, with satisfying the time constraints characteristics of the video streams. When the video streams are retrieved in storage system under multiple disks environments, it can not only maintain the rapid responses but also can save the disk bandwidth owing to the retrieval based on priority. Also, it utilizes the given buffer capacity efficiently owing to determining the stream segment size heuristically, which is adapted to the buffer capacity Consequentially, these policies can increase the number of users supported. The correctness of the proposed policies is not only analyzed theoretically but also evaluated through simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.571-573
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• 2014

In today's technology streaming service's QoS technologiey is an issue. On quality video streaming service there are some technical issues exist, such as buffering. This submission is "Adaptive dual-streaming system design" which is for the integrity of the data streaming that is sent to TCP and UDP for faster transmission of data to the stream. This system provides real-time incoming video encoding in bitrate of h.264-based H through a process based on the video footage of several server and client-to-TCP and UDP via Adaptive providing streaming services in a network environment. This is an unspecified number of buffers in a network environment and continued through the minimization of various streaming for playback of videos and multimedia will be utilized in the field.

• Database Research
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• v.34 no.3
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• pp.58-68
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• 2018

Distributed computing helps to efficiently store and process large data on a cluster of multiple machines. The performance of distributed computing is greatly influenced depending on the state of the servers constituting the distributed system. In this paper, we propose a self-diagnosis system that collects log data in a distributed system, detects anomalies and visualizes the results in real time. First, we divide the self-diagnosis process into five stages: collecting, delivering, analyzing, storing, and visualizing stages. Next, we design a real-time self-diagnosis system that meets the goals of real-time, scalability, and high availability. The proposed system is based on Apache Flume, Apache Kafka, and Apache Storm, which are representative real-time distributed techniques. In addition, we use simple but effective moving average and 3-sigma based anomaly detection technique to minimize the delay of log data processing during the self-diagnosis process. Through the results of this paper, we can construct a distributed real-time self-diagnosis solution that can diagnose server status in real time in a complicated distributed system.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.139-148
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• 2005

The desired level for multimedia services in the mobile web environment, the next generation web environment, is expected to be of PC level quality. And great efforts have been made in the development of hadware technology, communication technology, various kinds of services and standardization to support these services, In the mobile web environment, multimedia contents adaptation services should be available through supporting various kinds of devices, network abilities and users' preferences. It means that due to the variety of both desired devices' hardware specifications, called destinations, and desired QoSes, the QoSes in the destinations are not fixed or defined. If a new user wants to stream multimedia contents in a server through a new kind of terminal device, it should be considered whether the existing transcoders are able to adapt the multimedia contents. However, the existing libraries for multimedia adaptation have heavy transcoder figures which include all adaptive functions in one library, The challenge of universal access is too complex to be solved with these all in one solutions. Therefore, in this paper we propose an application independent multimedia adaptation framework which meets the QoS of new and varied mobile devices. This framework is composed of a group of unit transcoders having only one transcoding function respectively, Instead of heavy transcoders. Also, It includes the transcoder manager supporting the dynamic connections of the unit transcoders in order to satisfy end to end QoS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.603-612
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• 2010

Recently, with the advance of computing and networking technique, the high speed internet becomes widespread, however, it is still hard job to do streaming the media which requires high network bandwidth over the internet. Previous VoD system researches for streaming over the internet mainly proposed techniques that controls the QoS(Quality of Service) of the media in proportion to the network status. Though, this could be the solution for the service provider while the service user who wants constant QoS may not satisfy with variable QoS. In the paper, we propose greedy precedent frame transmission technique, GPFT, for guarantee of constant QoS. In GPFT, Streaming VoD server prefetches precedent frames and transmits the frame greedily by increasing the frame transmission rate while the available network bandwidth is high. The GPFT uses the prefetched precedent frames to guarantee the QoS while the available network bandwidth is low. The experiment result shows that the proposed GPFT could guarantee the constant QoS by prefetching the frames adaptively to the network bandwidth with the characteristic of video stream.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.8
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• pp.297-306
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• 2018

In this paper, we address how to apply Apache Storm, a distributed stream processing framework, to InfiniBand, a high performance communication device. An easy way to run Storm on InfiniBand is to simply use IPoIP (IP over InfiniBand). However, this method causes a serious CPU load on the node, which is caused by frequent context switches and buffer copies. To solve this problem, we propose a new communication method using InfiniBand's Remote Direct Memory Access (RDMA) function in Storm. First, we design and implement RJ-Netty (RDMA/JXIO Netty), a new framework that replaces Netty, the legacy framework, to exploit RDMA functionality. Second, we reimplement the related classes so that Storm can use both existing Netty and new RJ-Netty. Third, we extend the JXIO server functionality so as to support multi-threading to maximize the performance of RJ-Netty. Experimental results show that the proposed RJ-Netty significantly reduces CPU load while improving message throughput compared to IPoIB as well as Ethernet. This paper is the first attempt to run Apache Storm on InfiniBand, and we believe that it is an excellent research result that improves the performance of Storm by using InfiniBand RDMA.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.660-673
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• 2001

In Video-on-Demand (VoD) servers, disk throughput is an important system design parameter because it is directly related to the number of user requests that can be served simultaneously. In this paper, we propose an efficient periodic request grouping scheme for disk array-based VoD servers that reduces the disk seek time, thus improving the disk throughput of VoD disk arrays. To reduce the disk seek time, the proposed scheme groups the periodic requests that access data blocks stored in adjacent regions into one, and arranges these groups in a pre-determined order (e.g., in left-symmetric or right-symmetric fashion). Our simulation result shows that the proposed scheme reduces the average disk bandwidth required by a single video stream and can serve more user requests than existing schemes. For a data block size of 192KB, the number of simultaneously served user requests is increased by 8% while the average waiting time for a user request is decreased by 20%. We also propose an adaptation technique that conforms the proposed scheme to the user preference changes for video streams.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7B
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• pp.608-618
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• 2006

The increasing popularity of multimedia streaming services introduces new challenges in content distribution. Especially, it is important to provide the QoS guarantees as they are increasingly expected to support the multimedia applications. The service providers can improve the performance of multimedia streaming by caching the initial segment (prefix) of the popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while requesting the remainder of the stream from the server. In this paper, in order to apply the prefix caching service based on IETF's RTSP environment to the wireless networks, we propose the effective RTSP handling scheme that can adapt to the radio situation in wireless network and reduce the cutting phenomenon. Also, we propose the traffic based caching algorithm (TSLRU) to improve the performance of caching proxy. TSLRU classifies the traffic into three types, and improve the performance of caching proxy by reflecting the several elements such as traffic types, recency, frequency, object size when performing the replacement decision. In simulation, TSLRU and RTSP handling scheme performs better than the existing schemes in terms of byte hit rate, hit rate, startup latency, and throughput.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.1059-1066
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• 2003

In this paper, the magnetic sensing system is designed and implemented for the safe security in internet commerce system. When the payment is required inthe internet commerce system, the magnetic sensing system will get the information from a credit card without keyboard input and then encrypt and transmit the information to server. The credit card sensing system, which is proposed in this paper, is safe from keyboard hacking because it encrypts card information immediately in its internal chip and sends the information to host system. For the protection of information, the magnetic sensing system is basically based on a synchronous stream cipher cryptosystem which is related to a group of matrices. The size of matrices and the bits of keys for the best performances are determined for various cases. It is shown that for credit card payments. matrices of size 2 have good performance even at most 128bits keys with the consideration of inverse matrices. For authentication of general-purpose data, the magnetic sensing system needs more than 1.5KB data and in this case, the optimum size of matrices is 2 or 3 at more 256bits keys with consideration of inverse matrices.