• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.193-197
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• 2021

Customers are increasingly attracted towards different e-commerce websites and applications for the purchase of products significantly. This is the reason the sellers are moving to different internet based services to sell their products online. The growth of customers in this sector has resulted in the use of big data analytics to understand customers' behavior in predicting the demand of items. It uses a complex process of examining large amount of data to uncover hidden patterns in the information. It is established on the basis of finding correlation between various parameters that are recorded, understanding purchase patterns and applying statistical measures on collected data. This paper is a document of the bottom-up strategy used to manage the selling price of a first-time product for maximizing profit while selling it online. It summarizes how existing customers' expectations can be used to increase the sale of product and attract the attention of the new customer for buying the new product.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.329-339
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• 2022

Small cells, particularly femtocells, are regarded a promising solution for limited resources required to handle the increasing data demand. They usually boost wireless network capacity. While widespread usage of femtocells increases network gain, it also raises several challenges. Interference is one of such concerns. Interference management is also seen as a main obstacle in the adoption of two-tier networks. For example, placing femtocells in a traditional macrocell's geographic area. Interference comes in two forms: cross-tier and co-tier. There have been previous studies conducted on the topic of interference management. This study investigates the principle of categorization of interference management systems. Many methods exist in the literature to reduce or eliminate the impacts of co-tier, cross-tier, or a combination of the two forms of interference. Following are some of the ways provided to manage interference: FFR, Cognitive Femtocell and Cooperative Resource Scheduling, Beamforming Strategy, Transmission Power Control, and Clustering/Graph-Based. Approaches, which were proposed to solve the interference problem, had been presented for each category in this work.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.131-136
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• 2022

This study was initially conducted to explore Saudi students' use of reading strategies and their relationship to their reading comprehension level. The study employed quantitative methods to obtain information about Saudi students' perceived use of reading strategies and their comprehension levels. The results showed that EFL learners in Saudi Arabia use planning strategies more than attending strategies and evaluating strategies. Saudi students also perceived the environment as the most critical factor affecting their reading comprehension. There was no significant relationship between Saudi EFL learners' comprehension level and their use of reading strategies. Finally, gender differences favoring female learners were evident in almost all analyses conducted in the current study. Significant differences were found favoring female students in overall strategy use, comprehension level, and the use of evaluating strategies.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.81-93
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• 2023

The popularity of short-form video platforms like TikTok has increased recently. Short-form videos are significantly shorter than traditional videos, and viewers regularly switch between different types of content to watch. Therefore, a successful prefetching strategy is essential for this novel type of video. This study provides a resource-effective prefetching technique for streaming short-form videos. The suggested solution dynamically adjusts the quantity of prefetched video data based on user viewing habits and network traffic conditions. The results of the experiments demonstrate that, in comparison to baseline approaches, our method may reduce data waste by 21% to 83%, start-up latency by 50% to 99%, and the total time of Re-buffering by 90% to 99%.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.210-218
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• 2023

The author presents a simple data-driven intraday technical indicator trading approach based on Genetic Programming (GP) for return forecasting in the Bitcoin market. We use five trend-following technical indicators as input to GP for developing trading rules. Using data on daily Bitcoin historical prices from January 2017 to February 2020, our principal results show that the combination of technical analysis indicators and Artificial Intelligence (AI) techniques, primarily GP, is a potential forecasting tool for Bitcoin prices, even outperforming the buy-and-hold strategy. Sensitivity analysis is employed to adjust the number and values of variables, activation functions, and fitness functions of the GP-based system to verify our approach's robustness.

• Journal of Communications and Networks
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• 제7권1호
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• pp.87-92
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• 2005

This paper presents basic queueing analysis contributing to teletraffc theory, with commonly accessible mathematical tools. This paper studies queueing systems with bulk arrivals. It is assumed that the number of arrivals and the expected number of arrivals in each bulk are bounded by some constraints B and (equation omitted), respectively. Subject to these constraints, convexity argument is used to show that the bulk-size probability distribution that results in the worst mean queue performance is an extremal distribution with support {1, B} and mean equal to A. Furthermore, from the viewpoint of security against denial-of-service attacks, this distribution remains the worst even if an adversary were allowed to choose the bulk-size distribution at each arrival instant as a function of past queue lengths; that is, the adversary can produce as bad queueing performance with an open-loop strategy as with any closed-loop strategy. These results are proven for an arbitrary arrival process with bulk arrivals and a general service model.

• 정보보호학회논문지
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• 제26권2호
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• pp.327-334
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• 2016

일반적으로 알려진 믿음과는 달리 다양한 컴퓨팅 장치의 메인 메모리로 사용되는 DRAM은 전원이 차단되더라도 저장하고 있던 데이터가 곧바로 사라지지 않고, 대신 어느 정도의 시간 동안 데이터를 유지하게 된다. 특히 DRAM을 냉각시키면 그 데이터 유지 시간이 더 길어진다는 사실 역시 알려져 있다. Cold Boot Attack이란 이러한 DRAM의 데이터 유지 성질을 이용하여, 전원이 차단된 DRAM으로부터 암호 알고리즘의 키와 같은 민감한 정보를 복구해내는 부채널 공격 방법의 일종이다. 본 논문에서는 대칭붕괴모델을 가정한 Cold Boot Attack 방법을 이용하여 전원이 차단된 DRAM으로부터 추출된 AES 키 비트열로부터 원래의 AES 키를 복구하는 알고리즘을 제안한다. 제안된 알고리즘은 추출된 AES 키 비트열의 랜덤성을 테스트하는 방법을 사용하여 후보 키 공간의 크기를 줄이는 방법을 사용한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3375-3400
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• 2018

With the advent of database-as-a-service (DAAS) and cloud computing, more and more data owners are motivated to outsource their data to cloud database in consideration of convenience and cost. However, it has become a challenging work to provide security to database as service model in cloud computing, because adversaries may try to gain access to sensitive data, and curious or malicious administrators may capture and leak data. In order to realize privacy preservation, sensitive data should be encrypted before outsourcing. In this paper, we present a secure and practical system over encrypted cloud data, called QSDB (queryable and secure database), which simultaneously supports SQL query operations. The proposed system can store and process the floating point numbers without compromising the security of data. To balance tradeoff between data privacy protection and query processing efficiency, QSDB utilizes three different encryption models to encrypt data. Our strategy is to process as much queries as possible at the cloud server. Encryption of queries and decryption of encrypted queries results are performed at client. Experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed system.

• Management Science and Financial Engineering
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• 제17권1호
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• pp.45-63
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• 2011

The aim of this paper is to consider the process of supplying trained workers with knowledge and skills for upcoming business opportunities and the process of training apprentices to be prepared to meet future demands in an IT service firm. As the demand for new workers fluctuates, a firm should employ a buffer workforce such as apprentices or interns. However, as a result of rapid business development, the capacity of the buffer may be exceeded, thus requiring the company to recruit skilled workers from outside the firm. Therefore, it is important for a firm to map out a strategy for manpower planning so as to fulfill the demands of new business and minimize the operation costs related to training apprentices and recruiting experienced workers. First, this paper analyzes the supply and demand of workers for the IT service in a knowledge-intensive field. It then presents optimal human resource planning strategies via the familiar method of stochastic process. Also, we illustrate that our model is applied to the human resource planning of an information security service firm in South Korea.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.321-322
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• 2018

본 연구에서는 학습자의 프로그래밍 학습능력을 향상시키기 위하여, 학습효과에 영향을 미치는 교수 전략을 규명하는 것을 목표로 하였다. 프로그래밍 학습효과에 영향을 미치는 교수전략으로는 진도 적절성, 난이도 적절성, 교수자의 개입수준, 유머 사용으로 측정하였으며 학습효과는 성취도와 만족도를 측정하였다. A 전문대학의 컴퓨터공학과 110명의 학생을 대상의 설문을 실시한 후 학습효과에 대한 교수전략의 영향을 분석한 결과, 난이도 적절성이 성취도에 영향을 끼치며, 난이도 적절성과 교수자의 개입수준이 수업만족도에 영향을 미치는 것으로 규명되었다. 이에 따라 프로그래밍의 학습효과를 향상시킬 수 있는 시사점을 제안하였다.