• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.256-274
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• 2022

The continuous information technology and telecommunication (ICT) developments inspire several Saudi Arabia citizens to transact and interact online. However, when using online platforms, several people are likely to lose their personal information to cybercriminals. In the survey, 553 Saudi Arabia citizens and 103 information technology (IT) specialists confirm the expansion of digital economy and the need for smart cities with various services, including e-commerce and solid cyber security. 96.6% of the participants believe Saudi Arabia is digitalizing its economy; yet, 33.3% of the participants believe that residents are uninformed about living and operating in smart cities. Several people (47.29%) with medium internet speed are more aware about smart cities than those with fastest internet speed (34%). Besides, online transactions via credit cards subjected 55.5% of the participants to privacy and security issues. These findings validate the essence of cyber security awareness programs among Saudi Arabia citizens and IT professionals to boost public trust and acceptance of cybersecurity frameworks.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.242-250
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• 2013

Many information systems that provide useful services to people are connected to the Internet for convenience and efficiency. However, improper accessibility might make the systems susceptible to a variety of attacks. Although existing security solutions such as an intrusion detection system, intrusion prevention system, and firewalls have been designed to protect against such attacks, it is impossible to block all kinds of attacks. Furthermore, most of the proposed solutions require information about attacks for efficient prevention. Research on intrusion-tolerant systems (ITSs) have been conducted in order to continue providing proper services in threatening environments. The purpose of an ITS is to survive against every intrusion, rather than to prevent them. In this paper, previous studies on ITS are introduced and classified according to the centric scheme as middleware-based ITS, hardware-based ITS, and recovery-based ITS. Recent research focusing on adaptive transformation schemes is also introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.155-162
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• 2022

Over the last 10 years, there has been rapid growth in the use of Machine Learning (ML) techniques to automate the process of intrusion threat detection at a scale never imagined before. This has prompted researchers, software engineers, and network specialists to rethink the applications of machine ML techniques particularly in the area of cybersecurity. As a result there exists numerous research documentations on the use ML techniques to detect and block cyber-attacks. This article is a systematic review involving the identification of published scholarly articles as found on IEEE Explore and Scopus databases. The articles exclusively related to the use of machine learning in Intrusion Detection Systems (IDS). Methods, concepts, results, and conclusions as found in the texts are analyzed. A description on the process taken in the identification of the research articles included: First, an introduction to the topic which is followed by a methodology section. A table is used to list identified research articles in the form of title, authors, methodology, and key findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1078-1099
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• 2021

Traditional image steganography hides secret information by embedding, which inevitably leaves modification traces and is easy to be detected by steganography analysis tools. Since coverless steganography can effectively resist steganalysis, it has become a hotspot in information hiding research recently. Most coverless image steganography (CIS) methods are based on mapping rules, which not only exposes the vulnerability to geometric attacks, but also are less secure due to the revelation of mapping rules. To address the above issues, we introduced camouflage images for steganography instead of directly sending stego-image, which further improves the security performance and information hiding ability of steganography scheme. In particular, based on the different sub-features of stego-image and potential camouflage images, we try to find a larger similarity between them so as to achieve the reversible steganography. Specifically, based on the existing CIS mapping algorithm, we first can establish the correlation between stego-image and secret information and then transmit the camouflage images, which are obtained by reversible sub-feature retrieval algorithm. The received camouflage image can be used to reverse retrieve the stego-image in a public image database. Finally, we can use the same mapping rules to restore secret information. Extensive experimental results demonstrate the better robustness and security of the proposed approach in comparison to state-of-art CIS methods, especially in the robustness of geometric attacks.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.84-89
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• 2021

Medical tests are very important part of the health monitoring process. It is performed for various reasons like diagnosing diseases, determining medications effectiveness, etc. Due to that, patients should be able to read and understand the available online tests and results in order to take proper decisions regarding their health condition. In fact, people are varying in their educational level and health backgrounds that make providing such information in an easily readable format by the majority of people considered as a challenge in the health domain since ever. This paper describes the MTReadable corpus which constructed for evaluating the readability of online medical tests. It covered 32 basic periodic check-up tests with over 36k words. These tests information are annotated and labelled based on three readability levels which are easy, neutral and difficult by three non-specialists native Arabic speakers. This paper contributes to enriching the Arabic health research community with an investigation of the level of readability of online medical tests and to be a baseline for further complex health online reports and information.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.207-208
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• 2007

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.331-333
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• 2006

본 논문에서는 작업장 감지 시스템 WMS(Workshop Monitoring System)의 센서로부터 수집된 정보를 통하여 작업장 상황(Situation)을 지능적으로 인식할 수 있는 시스템을 개발하였다. 기존의 시스템은 개별 센서가 보낸 정보에 기반한 작업장 상황파악이 그 주된 기능이다. 본 연구에서는 센서 정보의 연관성을 파악하고 정상 및 비정상 상황을 구분함과 아울러 비정상 상황이 발생할 수 있는 원인을 분석하여 센서 온톨로지(Sensor Ontology)를 구축하였다. 이러한 지능적 상황인식을 통하여 유비쿼터스 환경에서 센서 융합(Sensor Fusion)형 상황인지를 가능하게 하는 시스템 구현 기초기술을 확보하였다.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.254-266
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• 2021

The Internet of Medical Things (IoMTs) are to be considered an investment and an improvement to respond effectively and efficiently to patient needs, as it reduces healthcare costs, provides the timely attendance of medical responses, and increases the quality of medical treatment. However, IoMT devices face exposure from several security threats that defer in function and thus can pose a significant risk to how private and safe a patient's data is. This document works as a comprehensive review of modern approaches to achieving security within the Internet of Things. Most of the papers cited here are used been carefully selected based on how recently it has been published. The paper highlights some common attacks on IoMTs. Also, highlighting the process by which secure authentication mechanisms can be achieved on IoMTs, we present several means to detect different attacks in IoMTs

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.115-122
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• 2023

Makkah Al-Mukarramah is the capital of Islamic world. It receives special attention from the Saudi government's rulers to transform it into a smart city for the benefit of millions of pilgrims. One of the 2030 vision objectives is to transform specific cities to smart ones with advanced technological facilitation, Makkah is one of these cities. The history of Makkah is not well known for some Muslims. As a result, we built the concepts of our application "Ain Makkah" to enable visitors of Makkah to know the history of Makkah by using technology. In particular "Ain Makkah" uses Augmented Reality to view the history of Al-Kaaba. A 3D model will overlay Al-Kaaba to show it in the last years. Our project will use Augmented Reality to build a 3D model to overlay Al-Kaaba. Future work will expand the number of historical landmarks of Makkah.