Vol. 45, No. 10, Oct. 2018
Digital Library


An Efficient and Adaptable Hybrid Multi-channel Multi-hop MAC Protocol in VANETs

VanDung Nguyen, Eui-Nam Huh, Choong Seon Hong

http://doi.org/10.5626/JOK.2018.45.10.981

Vehicular Ad-hoc NETworks (VANETs) are designed to improve transportation efficiency such as to increase safety and reduce traffic accidents. In addition, VANET is created to connect and exchange information between vehicles or between vehicle and infrastructure. For VANET, Medium Access Control (MAC) protocols, which provide an efficient broadcast service, are designed to efficiently and fairly share the wireless medium between vehicles and providers. Recently, the hybrid MAC protocol was designed to combine TDMA- and CSMA-based mechanisms into a single mechanism to improve the Quality of Service (QoS) and decrease the collision rate. In this paper, we propose an Efficient and Adaptable Hybrid Multi-channel Multi-hop MAC protocol in VANETs, called the EAHMAC protocol, which allows vehicles to not only occupy time slots but also to broadcast packets in a flexible way based on the two-hop neighbor"s information. The simulation results show that our proposal outperforms the existing protocols in terms of access collision rate, packet delivery ratio, and throughput on the service channel.

An Offloading Scheme for Reliable Data Processing of Swarm-drones

Hong Min, Bongjae Kim, Junyoung Heo, Jinman Jung

http://doi.org/10.5626/JOK.2018.45.10.990

With the developing drone-related technologies, autonomous drones have many applications. The offloading technique is used to execute high computational tasks that are stored in the cloud to preserve the limited resources of a drone. In this paper, we determine the effect of offloading by using cost analysis for swarm-drones considering task completion time and energy consumption. If the drones take more time and spend more energy while offloading their tasks to the cloud, drones divide a large task into small tasks. These tasks are run by using the drone’s own resources to process data reliably and efficiently. Our simulation results also show how the task completion time and the energy consumption infuence the offloading decision.

Crack Map Synthesis Using Primitives and a Guidance Vector Field

Hyojin Jung, Yuna Jeong, Sungkil Lee

http://doi.org/10.5626/JOK.2018.45.10.996

Cracks effectively show surface changes caused by weather or impacts. In general, crack rendering uses physically-based simulations. However, these approaches require huge computational cost, and it is hard to intuitively obtain non-physical effects. This paper presents a crack-map synthesis technique based on crack-map primitives and a guidance vector field. Diverse crack patterns are pre-defined as height maps. Their placements are determined by the Perlin noise-based guidance vector field. The output crack map is defined as a composite of primitives. When multiple primitives exist in the same area, the lowest of their heights is selected. Unlike other physically-based rendering approaches that have previously been used, our primitive-based approach allows us to easily obtain intuitive crack effects as desired.

Integrated Explanation System for a Scalable Data based on SPARQL Results

MyungJoong Jeon, HyunKyu Park, YoungTack Park

http://doi.org/10.5626/JOK.2018.45.10.1004

Recently, there has been an increasing demand for an explanation of query results in a variety of QA systems and expert systems. However, the systems being studied today only focus on the scalable query processing. Therefore, this paper proposes an integrated system that explains the causal relationship to the query results based on large volumes of retrievable data. The system uses a distributed rule-based SWRL engine for reasoning about large amounts of knowledge. And in this case uses evidence of reasoning as input for a distributed ATMS to express the structure of the causal relationship. Finally, after obtaining the answers using SPARQLGX, and a scalable SPARQL query processor, this system explains the evidence of answers using a reference to the previously established dependency structure. The evaluation of the proposed explanation system used the benchmark data(Lehigh University Benchmark) and used 14 test queries provided by the LUBM for evaluating the response time and explanation time in this case.

Social Engineering based Security Requirements Recommendation Framework to Prevent an Advanced Persistent Threat

Seung-Jun Kim, Seok-Won Lee

http://doi.org/10.5626/JOK.2018.45.10.1015

Advanced Persistent Threat (APT) is a major threat to Socio-Technical System, which constitutes our society. This threat is an attack process rather than a hacking technique, unlike traditional methods of cyberbullying, so it is difficult to detect or defend a wide range of targets for a long period of time using a wide range of exploits. In particular, traditional advanced threats involve technical approaches, such as firewalls, log checks, and packet analysis, in which the first stage of the intelligent, sustained threat analysis involves the ease with which human vulnerabilities are pursued during the early stages of the process. This paper proposes a framework that analyzes the vulnerable social perspective based on the various human factors to prevent advanced persistent threats by using three-layered approach and recommends a security requirement to complement them by using ontology-based approach.

Analysis of the Cost-effectiveness of Regression Testing Techniques in Continuous Integration Environments based on Failure to Pay Attention

Jung-Hyun Kwon, In-Young Ko

http://doi.org/10.5626/JOK.2018.45.10.1029

In continuous integration (CI) environments, it is possible to provide fast feedback on test failures by applying cost-effective regression-testing techniques. In this study, we analyze the cost-effectiveness of two test-case prioritization techniques based on the test history of three industrial projects. In addition, because test failures may have different degrees of attention paid to them by different developers in CI environments, we consider this characteristic in the experiment. As a result, we discovered that the cost-effectiveness of applying the TCP techniques can be similar to that of not applying any of the TCP techniques when failure of the developers to pay attention is considered. The experiment shows that it is necessary to improve the state-of-the-art test-case prioritization techniques for CI environments by considering such characteristics.

Automated Capturing and Replaying Unit Inputs of C Programs from System Executions through Static and Dynamic Analysis

Hyunsu Lim, Yunho Kim, Moonzoo Kim

http://doi.org/10.5626/JOK.2018.45.10.1035

Despite the high testing power of unit testing, it has an infeasible input problem, which is an impossible input for a unit in a real system. There is a technique known as Carving and Replay (CR) that serializes the state of the program when a target function is called in system execution and uses it as unit test case by deserializing it, to solve this infeasible input problem. However, unlike programming languages like Java, the C programming language does not provide a serialization method. Also, because of the C programming language’s features such as structure, union, and pointer, it has its own challenges for applying the CR technique. In this paper, we examine the challenges and suggest a CR tool for C programs by solving such problems with tracking the memory usage of the program, using run-time information from dynamic analysis, and inserting a probe code by static analysis.

A Twitter News-Classification Scheme Using Semantic Enrichment of Word Features

Seonmi Ji, Jihoon Moon, Hyeonwoo Kim, Eenjun Hwang

http://doi.org/10.5626/JOK.2018.45.10.1045

Recently, with the popularity of Twitter as a news platform, many news articles are generated, and various kinds of information and opinions about them spread out very fast. But since an enormous amount of Twitter news is posted simultaneously, users have difficulty in selectively browsing for news related to their interests. So far, many works have been conducted on how to classify Twitter news using machine learning and deep learning. In general, conventional machine learning schemes show data sparsity and semantic gap problems, and deep learning schemes require a large amount of data. To solve these problems, in this paper, we propose a Twitter news-classification scheme using semantic enrichment of word features. Specifically, we first extract the features of Twitter news data using the Vector Space Model. Second, we enhance those features using DBpedia Spotlight. Finally, we construct a topic-classification model based on various machine learning techniques and demonstrate by experiments that our proposed model is more effective than other traditional methods.

Analysis of Case Scenario to Develop a System of Systems Meta-model for Ontology Representation

Young-Min Baek, Sumin Park, Yong-Jun Shin, Doo-Hwan Bae

http://doi.org/10.5626/JOK.2018.45.10.1056

Ontology is a formal and explicit specification technique that defines concepts and relationships of a system. It is utilized to establish a common knowledge base and to reduce mismatches or inconsistencies during communication. Since a System-of-Systems (SoS) is a large-scale complex system that achieves higher-level common goals by the collaboration of constituent systems, ontologies need to be established for overall SoS development and operations. In other words, refined development and communications among various stakeholders of an SoS can be achieved based on the conceptualization power of an ontology. However, in order to build an ontology effectively, SoS engineers require a systematic means to provide a guideline for domain analysis and ontology establishment. To fulfill these requirements, this study proposes a meta-model, called the Meta-model for System-of- Systems (M2SoS), which enables systematic specifications of ontologies for SoS development. M2SoS is developed based on existing studies on meta-modeling approaches in the multi-agent system domain, but M2SoS is improved to meet SoS-specific requirements by SoS case analysis.

Improving Applicability and Usability of a Concolic Testing Tool CROWN

Hyunwoo Kim, Yunho Kim, Moonzoo Kim

http://doi.org/10.5626/JOK.2018.45.10.1071

The paper presents an extension of the Concolic testing tool CROWN(Concolic testing for Real-wOrld softWare aNalysis) for improving the applicability and usability of Concolic testing. The existing CROWN tool is limited to Linux platforms and the Concolic testing results generated from CROWN are hard for users to understand. We extend CROWN to run on Windows OS to increase the running platforms and improve user interface with CROWN and its applicability to help users analyze Concolic testing results in an easier way.

Systematic Analysis of Optimal Feature Extraction Methods for Developing a Near-Infrared Spectroscopy-Based Brain-Computer Interface System

Jaeyoung Shin, Han-Jeong Hwang

http://doi.org/10.5626/JOK.2018.45.10.1080

In this study, we systematically investigated optimal feature extraction methods for developing a near-infrared spectroscopy (NIRS)-based brain-computer interface (BCI) by considering various analysis time periods and feature combinations. While twelve subjects performed mental arithmetic and resting tasks for 10 s 30 times each, NIRS signals were measured. Seven types of different features were extracted from the NIRS signals, and classification accuracies were calculated using individual feature types extracted from 0-10 and 0-15 s single analysis periods and feature combinations extracted from 0-15 s analysis period that was divided into three time periods (0-5, 5-10, 10-15 s), respectively. As a result, the highest classification accuracy was obtained when the combination of different feature types extracted from a 0-15 s analysis period divided into the three periods was used, and it was confirmed that the combinations of mean and slope features were considered the most suitable for developing a NIRS-based BCI system.

Correct Linear Skyline Algorithm in High-Dimensional Space

Heesoo Park, Jongwuk Lee

http://doi.org/10.5626/JOK.2018.45.10.1089

Skyline query is a preference query that finds a candidate set for user preferences, employing the dominance property. It can be effectively used for decision problems that have multiple data attributes. However, a problem arises whereby the skyline becomes too large as the number of attributes in the data increases. To solve this problem, in this paper, we propose a new algorithm for a linear skyline query that restricts a user’s preference function by a linear function. In the previous work, a method was proposed to obtain a linear skyline by adding the same number of virtual points to the data as the number of attributes. However, it has been observed that this previous method does not guarantee the correctness of the linear skyline. We revised this method by adding virtual points in order to find the correct linear skyline. We prove that the proposed algorithm finds the correct linear skyline, and we empirically evaluate the correctness of the proposed algorithm.

Collecting Network Field Information using Machine Learning

Kyu Seok Han, Taekyu Kim, Shinwoo Shim, Sung Goo Jun, Jiwon Yoon

http://doi.org/10.5626/JOK.2018.45.10.1096

Recently, various systems based on Internet of Things (IOT) and Information and Communications Technologies(ICT) have been developed. Today, assorted devices are connected to a network, and various operating systems according to devices having different resources and functions have appeared. With the increased need for in hacking security, researches on the vulnerability analysis of the operating system installed on each device and the actual attack technique have been carried out. Accordingly, the type and detailed version of the operating system of the device, Function (API) is emerging as important information in security. Since the control of this information gathering in the cyber warfare is the first stage of the cyber threat, many studies have been conducted on mehods for controlling the network traffic while scanning. In order to bypass this control of the network, information collectors prepare countermeasures to secretly collect port information. In this paper, we deal with a scanning method that can acquire information about opponents through network basic commands which are not important in the network control system.

Web-based Integrated Management System Using oneM2M Platform in IoT Environment

Manseong Lee, Geonwoo Kim, Jiwoo Park, Kwangsue Chung

http://doi.org/10.5626/JOK.2018.45.10.1104

Today, the Internet of Things (IoT) is increasingly utilized to connect between devices as Machine to Machine (M2M) technology develops. A standardized communication protocol is required for device-to-device connections. The oneM2M standard is being used in IoT devices as a standardization method for stable communication between two devices. oneM2M controls resources by requesting resources through Create, Retrieve, Update, Delete, Notify (CRUDN) operations. Since the existing system checks the status information of the device through the application, a problem arises whereby the user has no accessibility and the real-time information cannot be served. The proposed system manages the IoT device as a oneM2M resource and advises the user to check the real-time resource information and log in the web environment.


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