scholarly journals Cyber Security in the Maritime Industry: A Systematic Survey of Recent Advances and Future Trends

Information ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 22
Author(s):  
Mohamed Amine Ben Farah ◽  
Elochukwu Ukwandu ◽  
Hanan Hindy ◽  
David Brosset ◽  
Miroslav Bures ◽  
...  
Keyword(s):  
Cyber Security ◽  
State Of The Art ◽  
Satellite System ◽  
Cyber Attacks ◽  
Future Research ◽  
Maritime Industry ◽  
Cyber Crimes ◽  
Global Navigation Satellite ◽  
Levels Of Integration

The paper presents a classification of cyber attacks within the context of the state of the art in the maritime industry. A systematic categorization of vessel components has been conducted, complemented by an analysis of key services delivered within ports. The vulnerabilities of the Global Navigation Satellite System (GNSS) have been given particular consideration since it is a critical subcategory of many maritime infrastructures and, consequently, a target for cyber attacks. Recent research confirms that the dramatic proliferation of cyber crimes is fueled by increased levels of integration of new enabling technologies, such as IoT and Big Data. The trend to greater systems integration is, however, compelling, yielding significant business value by facilitating the operation of autonomous vessels, greater exploitation of smart ports, a reduction in the level of manpower and a marked improvement in fuel consumption and efficiency of services. Finally, practical challenges and future research trends have been highlighted.

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

scholarly journals Kinematic PPP Using Mixed GPS/Glonass Single-Frequency Observations

2019 ◽  
Vol 54 (3) ◽  
pp. 97-112
Author(s):  
Mostafa Hamed ◽  
Ashraf Abdallah ◽  
Ashraf Farah
Keyword(s):  
Low Cost ◽  
Satellite System ◽  
Single Frequency ◽  
Future Research ◽  
Frequency Data ◽  
Dual Frequency ◽  
Trajectory Data ◽  
Average Improvement ◽  
Kinematic Ppp ◽  
Global Navigation Satellite

Abstract Nowadays, Precise Point Positioning (PPP) is a very popular technique for Global Navigation Satellite System (GNSS) positioning. The advantage of PPP is its low cost as well as no distance limitation when compared with the differential technique. Single-frequency receivers have the advantage of cost effectiveness when compared with the expensive dual-frequency receivers, but the ionosphere error makes a difficulty to be completely mitigated. This research aims to assess the effect of using observations from both GPS and GLONASS constellations in comparison with GPS only for kinematic purposes using single-frequency observations. Six days of the year 2018 with single-frequency data for the Ethiopian IGS station named “ADIS” were processed epoch by epoch for 24 hours once with GPS-only observations and another with GPS/GLONASS observations. In addition to “ADIS” station, a kinematic track in the New Aswan City, Aswan, Egypt, has been observed using Leica GS15, geodetic type, dual-frequency, GPS/GLONASS GNSS receiver and single-frequency data have been processed. Net_Diff software was used for processing all the data. The results have been compared with a reference solution. Adding GLONASS satellites significantly improved the satellite number and Position Dilution Of Precision (PDOP) value and accordingly improved the accuracy of positioning. In the case of “ADIS” data, the 3D Root Mean Square Error (RMSE) ranged between 0.273 and 0.816 m for GPS only and improved to a range from 0.256 to 0.550 m for GPS/GLONASS for the 6 processed days. An average improvement ratio of 24%, 29%, 30%, and 29% in the east, north, height, and 3D position components, respectively, was achieved. For the kinematic trajectory, the 3D position RMSE improved from 0.733 m for GPS only to 0.638 m for GPS/GLONASS. The improvement ratios were 7%, 5%, 28%, and 13% in the east, north, height, and 3D position components, respectively, for the kinematic trajectory data. This opens the way to add observations from the other two constellations (Galileo and BeiDou) for more accuracy in future research.

scholarly journals Hybridized-GNSS Approaches to Train Positioning: Challenges and Open Issues on Uncertainty

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1885 ◽  
Author(s):  
Susanna Spinsante ◽  
Cosimo Stallo
Keyword(s):  
Global Navigation Satellite System ◽  
Satellite System ◽  
Future Research ◽  
Navigation Satellite ◽  
Railway Traffic ◽  
Research Activities ◽  
Global Navigation ◽  
Train Positioning ◽  
Global Navigation Satellite ◽  
Open Issues

In recent years, the development of advanced systems and applications has propelled the adoption of autonomous railway traffic and train positioning, with several ongoing initiatives and experimental testbeds aimed at proving the suitability and reliability of the Global Navigation Satellite System signals and services, in this specific application domain. To satisfy the strict safety and accuracy requirements aimed at assuring the position solution’s integrity, availability, accuracy and reliability, recent proposals suggest the hybridization of the Global Navigation Satellite System with other technologies. The integration with localization techniques that are expected to be available with the upcoming fifth generation mobile communication networks is among the most promising approaches. In this work, different approaches to the design of hybrid positioning solutions for the railway sector are examined, under the perspective of the uncertainty evaluation of the attained results and performance. In fact, the way the uncertainty associated to the positioning measurements performed by different studies is reported is often not consistent with the Guide to the Expression of Uncertainty in Measurement, and this makes it very difficult to fairly compare the different approaches in order to identify the best emerging solution. Under this perspective, the review provided by this work highlights a number of open issues that should drive future research activities in this field.

Cyber security risks in globalized supply chains: conceptual framework

2020 ◽  
Vol 13 (1) ◽  
pp. 103-128 ◽  
Author(s):  
Shipra Pandey ◽  
Rajesh Kumar Singh ◽  
Angappa Gunasekaran ◽  
Anjali Kaushik
Keyword(s):  
Supply Chains ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Point Of View ◽  
Mitigation Strategies ◽  
Future Research ◽  
Security Risk ◽  
Security Risks ◽  
Content Type ◽  
Efficiency And Effectiveness

Purpose The purpose of this study is to examine cyber security risks in globalized supply chains (SCs). It has been seen to have a greater impact on the performance of SCs. The information and communication technology of a firm, which enhances the efficiency and effectiveness in the SC, could simultaneously be the cause of vulnerabilities and exposure to security threats. Researchers have primarily focussed on the cyber-physical system (CPS) vulnerabilities impacting SC. This paper tries to categorize the cyber security risks occurring because of the SCs operating in CPS. Design/methodology/approach Based on the flow of information along the upstream and downstream SC, this paper tries to identify cyber security risks in the global SCs. It has further tried to categorize these cyber security risks from a strategic point of view. Findings This paper tries to identify the various cyber security risk and cyber-attacks in globalized SC for improving the performance. The 16 cyber security risks have been categorized into three categories, namely, supply risk, operational risk and demand risk. The paper proposes a framework consisting of different cyber-attacks across the information that flows in global SCs along-with suitable mitigation strategies. Research limitations/implications The paper presents the conceptual model of cyber security risks and cyber-attacks in globalized SCs based on literature review and industry experts. Further validation and scale development of these risks can be done through empirical study. Practical implications This paper provides significant managerial insights by developing a framework for understanding the cyber security risks in terms of the drivers of these risks and how to deal with them. From a managerial perspective, this framework can be used as a decision-making process while considering different cyber security risks across the stages of globalized SCs. Originality/value The major contribution of this study is the identification and categorization of cyber security risks across the global SCs in the digital age. Thus, this paper introduces a new phenomenon to the field of management that has the potential to investigate new areas of future research. Based on the categorization, the paper provides insights on how cyber security risks impact the continuity of SC operations.

A Systematic Study of Feature Selection Methods for Learning to Rank Algorithms

2018 ◽  
Vol 8 (3) ◽  
pp. 46-67 ◽  
Author(s):  
Mehrnoush Barani Shirzad ◽  
Mohammad Reza Keyvanpour
Keyword(s):  
Feature Selection ◽  
State Of The Art ◽  
Learning To Rank ◽  
Future Research ◽  
Selection Methods ◽  
Ranking Models ◽  
Ranking Systems ◽  
Efficiency And Effectiveness ◽  
Selection For

This article describes how feature selection for learning to rank algorithms has become an interesting issue. While noisy and irrelevant features influence performance, and result in an overfitting problem in ranking systems, reducing the number of features by illuminating irrelevant and noisy features is a solution. Several studies have applied feature selection for learning to rank, which promote efficiency and effectiveness of ranking models. As the number of features and consequently the number of irrelevant and noisy features is increasing, systematic a review of Feature selection for learning to rank methods is required. In this article, a framework to examine research on feature selection for learning to rank (FSLR) is proposed. Under this framework, the authors review the most state-of-the-art methods and suggest several criteria to analyze them. FSLR offers a structured classification of current algorithms for future research to: a) properly select strategies from existing algorithms using certain criteria or b) to find ways to develop existing methodologies.

SIGNIFICANT ROLE OF AI & ML TECHNIQUES USED IN IMPROVEMENT OF CYBER SECURITY

2021 ◽  
Vol 12 (1) ◽  
pp. 80-89
Author(s):  
Muskan Kumari ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Current Status ◽  
Future Research ◽  
Engineering Managers ◽  
Network Protection ◽  
Machine Leaning ◽  
Expert Community

Cyber Security has become an arising challenge for business information system in current era. AI (Artificial Intelligence) is broadly utilized in various field, however it is still generally new in cyber security. Nonetheless, the applications in network protection are significant for everybody`s day by day life. In this paper, we present the current status of AI in cyber security field, and afterward portray a few contextual investigations and uses of AI to help the community including engineering managers, teachers, educators, business people, and understudies to more readily comprehend this field, for example, the difficulties and uncertain issues of AI in online protection. According to the new challenges, the expert community has two main approaches: to adopt the philosophy and methods of Military Intelligence, and to use Artificial Intelligence methods for counteraction of Cyber Attacks. Cyber security is a vital danger for any business as the quantity of attacks is expanding. Developing of attacks on cyber security is undermining our reality. AI (Artificial Intelligence) and ML (Machine Leaning) can help identify dangers and give proposals to cyber Analyst. Advancement of appropriation of AI/ML applied to cyber security requires banding together of industry, the scholarly community, and government on a worldwide scale. We also discuss future research opportunities associated with the development of AI techniques in the cyber security ?eld across a scope of utilization areas.

scholarly journals Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

2013 ◽  
Vol 2013 ◽  
pp. 1-22 ◽  
Author(s):  
Ammara Masood ◽  
Adel Ali Al-Jumaily
Keyword(s):  
Skin Cancer ◽  
State Of The Art ◽  
Comparative Assessment ◽  
Future Research ◽  
Feature Extraction And Selection ◽  
Diagnostic Models ◽  
Computer Aided ◽  
Aided Diagnosis ◽  
Diagnostic Support

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique’s performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.

Modelling competitive advantage of nation: a literature review

2017 ◽  
Vol 27 (4) ◽  
pp. 335-365 ◽  
Author(s):  
Muhammad Hanafi ◽  
Dermawan Wibisono ◽  
Kuntoro Mangkusubroto ◽  
Manahan Siallagan ◽  
Mila Jamilah Khatun Badriyah
Keyword(s):  
Literature Review ◽  
Competitive Advantage ◽  
Design Methodology ◽  
State Of The Art ◽  
Future Research ◽  
Content Type ◽  
Research And Teaching ◽  
Research Gap ◽  
Solution Methodology

Purpose This paper aims to create a mapping of competitive advantage of nations (CAN) from research using some previous studies and recommend future research. Design/methodology/approach This paper applies a systematic literature review on the most recent studies of CAN. The research gap is analysed based on several categories: implication (strategy and policy, portrait); general characteristics (fundamental issues, indicators and patterns); solution methodology and strategic level (nation and industry). Then, the state-of-the-art analysis is used to develop future research. Findings The results of this study recommend future research of CAN based on the following CAN categories: implication (strategy and policy, portrait); general characteristics (fundamental issues, indicators and patterns); solution methodology and strategic level (nation and industry). Research limitations/implications This literature review has important implications and gives direction for research and teaching, as well as for further investigation of CAN. The limitation lies in the classification of patterns, which requires further study to avoid the ambiguity of grouping. Originality/value This is the first literature review about CAN using categories. It is of value in building future research of CAN in different industries and nations.

scholarly journals Establishment and Evaluation of a New Meteorological Observation-Based Grid Model for Estimating Zenith Wet Delay in Ground-Based Global Navigation Satellite System (GNSS)

2018 ◽  
Vol 10 (11) ◽  
pp. 1718 ◽  
Author(s):  
Yibin Yao ◽  
Zhangyu Sun ◽  
Chaoqian Xu
Keyword(s):  
Global Navigation Satellite System ◽  
State Of The Art ◽  
Satellite System ◽  
The State ◽  
Radiosonde Data ◽  
Navigation Satellite ◽  
Meteorological Observation ◽  
Grid Model ◽  
Zenith Wet Delay ◽  
Global Navigation Satellite

With the availability to high-accuracy a priori zenith wet delay (ZWD) data, the positioning efficiency of the precise point positioning (PPP) processing can be effectively improved, including accelerating the convergence time and improving the positioning precision, in ground-based Global Navigation Satellite System (GNSS) technology. Considering the limitations existing in the state-of-the-art ZWD models, this paper established and evaluated a new in-situ meteorological observation-based grid model for estimating ZWD named GridZWD using the radiosonde data and the European Centre for Medium-Range Weather Forecasts (ECWMF) data. The results show that ZWD has a strong correlation with the meteorological parameter water vapor pressure in continental and high-latitude regions. The root of mean square error (RMS) of 24.6 mm and 36.0 mm are achievable by the GridZWD model when evaluated with the ECWMF data and the radiosonde data, respectively. An accuracy improvement of approximately 10%~30% compared with the state-of-the-art models (e.g., the Saastamoinen, Hopfield and GPT2w models) can be found for the new built model.

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