• Title/Summary/Keyword: Computer-based Solution

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An Integer Programming-based Local Search for the Set Partitioning Problem

  • Hwang, Junha
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.9
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    • pp.21-29
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    • 2015
  • The set partitioning problem is a well-known NP-hard combinatorial optimization problem, and it is formulated as an integer programming model. This paper proposes an Integer Programming-based Local Search for solving the set partitioning problem. The key point is to solve the set partitioning problem as the set covering problem. First, an initial solution is generated by a simple heuristic for the set covering problem, and then the solution is set as the current solution. Next, the following process is repeated. The original set covering problem is reduced based on the current solution, and the reduced problem is solved by Integer Programming which includes a specific element in the objective function to derive the solution for the set partitioning problem. Experimental results on a set of OR-Library instances show that the proposed algorithm outperforms pure integer programming as well as the existing heuristic algorithms both in solution quality and time.

The Development of Collection Solution of the Three-Phase Power Data based on the Personal Computer for Supporting the Smart Grid (스마트 그리드 지원을 위한 컴퓨터 기반 3상 전력 데이터 수집 솔루션 개발)

  • Ko, Yun-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.4
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    • pp.553-558
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    • 2011
  • The smart grid is an intelligent electric power network in which a digital communication network is integrated into the existing electric power system. This enhances the efficiency of the electric use by supplying and controlling the electric power through the two-way communication between the utility and the electric customer. In this paper, to support the smart grid, a computer-based solution which collects the three-phase electric power data based on the LPT Communication is designed, and then its prototype is made.

Design of GBSB Neural Network Using Solution Space Parameterization and Optimization Approach

  • Cho, Hy-uk;Im, Young-hee;Park, Joo-young;Moon, Jong-sup;Park, Dai-hee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.1 no.1
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    • pp.35-43
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    • 2001
  • In this paper, we propose a design method for GBSB (generalized brain-state-in-a-box) based associative memories. Based on the theoretical investigation about the properties of GBSB, we parameterize the solution space utilizing the limited number of parameters sufficient to represent the solution space and appropriate to be searched. Next we formulate the problem of finding a GBSB that can store the given pattern as stable states in the form of constrained optimization problems. Finally, we transform the constrained optimization problem into a SDP(semidefinite program), which can be solved by recently developed interior point methods. The applicability of the proposed method is illustrated via design examples.

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Palliates the Attack by Hacker of Android Application through UID and Antimalware Cloud Computing

  • Zamani, Abu Sarwar;Ahmad, Sultan;Uddin, Mohammed Yousuf;Ansari, Asrar Ahmad;Akhtar, Shagufta
    • International Journal of Computer Science & Network Security
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    • v.21 no.8
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    • pp.182-186
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    • 2021
  • The market for smart phones has been booming in the past few years. There are now over 400,000 applications on the Android market. Over 10 billion Android applications have been downloaded from the Android market. Due to the Android popularity, there are now a large number of malicious vendors targeting the platform. Many honest end users are being successfully hacked on a regular basis. In this work, a cloud based reputation security model has been proposed as a solution which greatly mitigates the malicious attacks targeting the Android market. Our security solution takes advantage of the fact that each application in the android platform is assigned a unique user id (UID). Our solution stores the reputation of Android applications in an anti-malware providers' cloud (AM Cloud). The experimental results witness that the proposed model could well identify the reputation index of a given application and hence its potential of being risky or not.

Robust Face Recognition under Limited Training Sample Scenario using Linear Representation

  • Iqbal, Omer;Jadoon, Waqas;ur Rehman, Zia;Khan, Fiaz Gul;Nazir, Babar;Khan, Iftikhar Ahmed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3172-3193
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    • 2018
  • Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.

A Solution towards Eliminating Transaction Malleability in Bitcoin

  • Rajput, Ubaidullah;Abbas, Fizza;Oh, Heekuck
    • Journal of Information Processing Systems
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    • v.14 no.4
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    • pp.837-850
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    • 2018
  • Bitcoin is a decentralized crypto-currency, which is based on the peer-to-peer network, and was introduced by Satoshi Nakamoto in 2008. Bitcoin transactions are written by using a scripting language. The hash value of a transaction's script is used to identify the transaction over the network. In February 2014, a Bitcoin exchange company, Mt. Gox, claimed that they had lost hundreds of millions US dollars worth of Bitcoins in an attack known as transaction malleability. Although known about since 2011, this was the first known attack that resulted in a company loosing multi-millions of US dollars in Bitcoins. Our reason for writing this paper is to understand Bitcoin transaction malleability and to propose an efficient solution. Our solution is a softfork (i.e., it can be gradually implemented). Towards the end of the paper we present a detailed analysis of our scheme with respect to various transaction malleability-based attack scenarios to show that our simple solution can prevent future incidents involving transaction malleability from occurring. We compare our scheme with existing approaches and present an analysis regarding the computational cost and storage requirements of our proposed solution, which shows the feasibility of our proposed scheme.

FI-Based Local Group Key Generation/Distribution for Mobile Multicast in a Hierarchical Mobile IPv6Network

  • Baek, Jin-Suk;Fisher, Paul S.;Kwak, Ming-Yung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.2 no.1
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    • pp.5-21
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    • 2008
  • In order to securely transmit multicast data packets in a mobile environment where frequent join/leave events are a characteristic of the environment, there is a need for a new secure and efficient group key management solution. We propose a secure group key generation/distribution solution providing scalability and reliability. Using this solution, when a mobile node, which is in a multicast session, enters a new domain, the agent of the domain joins the multicast session and coordinates its data packets with the mobile node. The agent encrypts and transmits subsequent data packets to the mobile node, using a local one-time pad key. This key is generated with FI sequences, enabling the mobile node to regenerate the same data packet, based on the information sent by the agent. Our performance analysis demonstrates that the proposed solution can significantly reduce the number of key generations and distributions, when it is applied to the hierarchical mobile IPv6 network.

An Analysis of Security Threats and Security Requirements on the Designated PC Solution

  • Lee, Kyungroul;Lee, Sun-Young;Yim, Kangbin
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.5
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    • pp.29-39
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    • 2017
  • In this paper, we analyse security threats and security requirements about the designated PC solution which restricts usable PCs that are only an user own PCs or a registered PC for online banking or very important services. Accordingly, causable threats of the designated PC solution are classified a process, a network layer, a software module, and an environment of platform, and we draw security requirements based on analysed security threats. Results of this research are considered utilization of criteria for improving security of the designated PC solution and standards for giving hint of imposition of the designated PC solution.

Comparative Analysis of Centralized Vs. Distributed Locality-based Repository over IoT-Enabled Big Data in Smart Grid Environment

  • Siddiqui, Isma Farah;Abbas, Asad;Lee, Scott Uk-Jin
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.01a
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    • pp.75-78
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    • 2017
  • This paper compares operational and network analysis of centralized and distributed repository for big data solutions in the IoT enabled Smart Grid environment. The comparative analysis clearly depicts that centralize repository consumes less memory consumption while distributed locality-based repository reduce network complexity issues than centralize repository in state-of-the-art Big Data Solution.

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Assessment and Access Control for Ubiquitous Environments

  • Diep, Nguyen Ngoc;Lee, Sung-Young;Lee, Young-Koo;Lee, Hee-Jo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.05a
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    • pp.1107-1109
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    • 2007
  • Context-based access control is an emerging approach for modeling adaptive solution, making access control management more flexible and powerful. However, these strategies are inadequate for the increased flexibility and performance that ubiquitous computing environment requires because such systems can not utilize effectively all benefit from this environment. In this paper, we propose a solution based on risk to make use of many context parameters in order to provide good decisions for a safety environment. We design a new model for risk assessment in ubiquitous computing environment and use risk as a key component in decision-making process in our access control model.

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