scholarly journals AIS Data Vulnerability Indicated by a Spoofing Case-Study

2021 ◽  
Vol 11 (11) ◽  
pp. 5015
Author(s):  
Andrej Androjna ◽  
Marko Perkovič ◽  
Ivica Pavic ◽  
Jakša Mišković
Keyword(s):  
Situational Awareness ◽  
Automatic Identification ◽  
Identification System ◽  
Maritime Industry ◽  
Position Information ◽  
Safe Navigation ◽  
The Face ◽  
The Impact ◽  
Source Of Information

This paper takes a close look at the landscape of the Automatic Identification System (AIS) as a major source of information for maritime situational awareness (MSA) and identifies its vulnerabilities and challenges for safe navigation and shipping. As an important subset of cyber threats affecting many maritime systems, the AIS is subject to problems of tampering and reliability; indeed, the messages received may be inadvertently false, jammed, or intentionally spoofed. A systematic literature review was conducted for this article, complemented by a case study of a specific spoofing event near Elba in December 2019, which confirmed that the typical maritime AIS could be easily spoofed and generate erroneous position information. This intentional spoofing has affected navigation in international waters and passage through territorial waters. The maritime industry is neither immune to cyberattacks nor fully prepared for the risks associated with the use of modern digital systems. Maintaining seaworthiness in the face of the impact of digital technologies requires a robust cybersecurity framework.

Securing the Automatic Identification System (AIS): Using public key cryptography to prevent spoofing whilst retaining backwards compatibility

2021 ◽  
pp. 1-13
Author(s):  
Gareth Wimpenny ◽  
Jan Šafář ◽  
Alan Grant ◽  
Martin Bransby
Keyword(s):  
Data Exchange ◽  
Situational Awareness ◽  
Public Key Cryptography ◽  
Satellite System ◽  
Public Key ◽  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Safe Navigation ◽  
Global Navigation Satellite

Abstract The civilian Automatic Identification System (AIS) has no inherent protection against spoofing. Spoofed AIS messages have the potential to interfere with the safe navigation of a vessel by, amongst other approaches, spoofing maritime virtual aids to navigation and/or differential global navigation satellite system (DGNSS) correction data conveyed across it. Acting maliciously, a single transmitter may spoof thousands of AIS messages per minute with the potential to cause considerable nuisance; compromising information provided by AIS intended to enhance the mariner's situational awareness. This work describes an approach to authenticate AIS messages using public key cryptography (PKC) and thus provide unequivocal evidence that AIS messages originate from genuine sources and so can be trusted. Improvements to the proposed AIS authentication scheme are identified which address a security weakness and help avoid false positives to spoofing caused by changes to message syntax. A channel loading investigation concludes that sufficient bandwidth is available to routinely authenticate all AIS messages whilst retaining backwards compatibility by carrying PKC ‘digital signatures’ in a separate VHF Data Exchange System (VDES) side channel.

scholarly journals Single-Vessel Plume Dispersion Simulation: Method and a Case Study Using CALPUFF in the Yantian Port Area, Shenzhen (China)

2020 ◽  
Vol 17 (21) ◽  
pp. 7831
Author(s):  
Shubin Bai ◽  
Yuanqiao Wen ◽  
Li He ◽  
Yiming Liu ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Simulation Method ◽  
Atmospheric Environment ◽  
Automatic Identification ◽  
Identification System ◽  
Plume Dispersion ◽  
Single Vessel ◽  
Port Area ◽  
Site Monitoring ◽  
The Impact

To study the impact of vessel pollution on the atmospheric environment of the surrounding area, we present a numerical simulation method based on regional emissions inventories. The general spatial resolution is ≥1 km and the temporal resolution is ≥1 h; parameters which are suitable for the study of larger space–time scales. In this paper, the WRF/CALMET/CALPUFF model and Automatic Identification System (AIS) data are employed to develop a single-vessel atmospheric pollution diffusion model. The goal of this research uses existing meteorological models and diffusion models to provide a simulation technology method for studying the diffusion of SO2 from a single ship. We take the outgoing phase of ocean-going container vessels in Yantian Port as an example. It can be used to set the position of sensitive receptors near the port area. Simulations are implemented with CALPUFF and the results are compared with data derived from on-site monitoring instrument. The CALPUFF modelling domain covers an area of 925 km2 with a grid spacing of 500 m. The simulation results demonstrated agreement with the measured data. The ground concentration contribution value ranged from 10 to 102 μg/m3, while the affected area was about 4–26 km2 and the high-value area of the ground concentration contribution was distributed within 1–2 km from the ship track. Emissions generated by the vessels represent a considerable contribution to SO2 pollution around the harbor areas.

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

scholarly journals Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

2021 ◽  
Vol 9 (2) ◽  
pp. 180
Author(s):  
Lei Du ◽  
Osiris A. Valdez Banda ◽  
Floris Goerlandt ◽  
Pentti Kujala ◽  
Weibin Zhang
Keyword(s):  
Baltic Sea ◽  
Perceived Risk ◽  
Maritime Transportation ◽  
Near Miss ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Ship Collision ◽  
The Impact ◽  
Ship Behavior

Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

Research on Ship Classification Based on Trajectory Features

2017 ◽  
Vol 71 (1) ◽  
pp. 100-116 ◽  
Author(s):  
Kai Sheng ◽  
Zhong Liu ◽  
Dechao Zhou ◽  
Ailin He ◽  
Chengxu Feng
Keyword(s):  
Pattern Mining ◽  
Extraction Methods ◽  
Behaviour Pattern ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Trajectory Features ◽  
Ship Classification ◽  
Historical Trajectory

It is important for maritime authorities to effectively classify and identify unknown types of ships in historical trajectory data. This paper uses a logistic regression model to construct a ship classifier by utilising the features extracted from ship trajectories. First of all, three basic movement patterns are proposed according to ship sailing characteristics, with related sub-trajectory partitioning algorithms. Subsequently, three categories of trajectory features with their extraction methods are presented. Finally, a case study on building a model for classifying fishing boats and cargo ships based on real Automatic Identification System (AIS) data is given. Experimental results indicate that the proposed classification method can meet the needs of recognising uncertain types of targets in historical trajectory data, laying a foundation for further research on camouflaged ship identification, behaviour pattern mining, outlier behaviour detection and other applications.

scholarly journals An unmanned aircraft system for maritime operations

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878633 ◽  
Author(s):  
Mario Monteiro Marques ◽  
Victor Lobo ◽  
R Batista ◽  
J Oliveira ◽  
A Pedro Aguiar ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Situational Awareness ◽  
Traffic Monitoring ◽  
Unmanned Aircraft ◽  
Automatic Identification ◽  
Identification System ◽  
Time Operation ◽  
Air System ◽  
Unmanned Air System ◽  
Aircraft System

Unmanned air systems are becoming ever more important in modern societies but raise a number of unresolved problems. There are legal issues with the operation of these vehicles in nonsegregated airspace, and a pressing requirement to solve these issues is the development and testing of reliable and safe mechanisms to avoid collision in flight. In this article, we describe a sense and avoid subsystem developed for a maritime patrol unmanned air system. The article starts with a description of the unmanned air system, that was developed specifically for maritime patrol operations, and proceeds with a discussion of possible ways to guarantee that the unmanned air system does not collide with other flying objects. In the system developed, the position of the unmanned air system is obtained by the global positioning system and that of other flying objects is reported via a data link with a ground control station. This assumes that the detection of those flying objects is done by a radar in the ground or by self-reporting via a traffic monitoring system (such as automatic identification system). The algorithm developed is based on game theory. The approach is to handle both the procedures, threat detection phase and collision avoidance maneuver, in a unified fashion, where the optimal command for each possible relative attitude of the obstacle is computed off-line, therefore requiring low processing power for real-time operation. This work was done under the research project named SEAGULL that aims to improve maritime situational awareness using fleets of unmanned air system, where collision avoidance becomes a major concern.

scholarly journals Pengelolaan Keuangan Pemerintah di Masa Pandemi Covid 19 (Kasus Pada Pemerintah Provinsi Riau)

2021 ◽  
Vol 4 (1) ◽  
pp. 33-48
Author(s):  
Yesi Mutia Basri ◽  
Gusnardi Gusnardi
Keyword(s):  
Financial Management ◽  
Sampling Technique ◽  
Provincial Government ◽  
Data Display ◽  
Snowball Sampling ◽  
Key Informants ◽  
The Face ◽  
The Government ◽  
The Impact

This study aims to observe how local government financial management is in the face of the Covid-19 Pandemic—in particular, observing how budgeting, administration, and accountability of the Riau Provincial Government regarding the Covid-19 Pandemic. The research method used is a qualitative method with a type of case study. The data collection techniques used in-depth interviews, observation, and documentation. To ensure the validity of the data, triangulation was carried out by carrying out source triangulation and technical triangulation. The informants in this study consisted of key informants, primary informants, and supporting informants. Key informants are the head of the budget, the head of the treasury, and the head of the accounting and reporting sub-section. While the primary informants and supporting informants were selected using the snowball sampling technique. Data analysis was carried out by collecting data, reducing data display data, and making conclusions. The results of the analysis show that the impact of the Covid-19 Pandemic caused the Riau Provincial Government to refocus and reallocate the budget four times. At the administrative and accountability stages, there are problems with recording Unexpected Expenditures, namely the absence of technical guidelines regarding the administration of Unexpected Expenditures, determining spending limits for emergencies and urgency. Another problem is the absence of valid data for the distribution of aid funds for MSMEs affected by Covid-19 as well as valid documents in the recording of grant assistance from third parties. This research contributes to the government in making policies in financial management in a disaster emergency.Keyword: The Covid-19 Pandemic, Financial Management, Refocusing, Reallocation, Administration, Accountability AbstrakPenelitian ini bertujuan untuk mengobservasi bagaimana pengelolaan keuangan Pemerintah Daerah dalam menghadapi Pandemi Covid-19 ini. Secara khusus mengobservasi bagaimana penganggaran, penatausahaan dan pertanggungjawan Pemerintah Provinsi Riau terkait Pandemi Covid-19. Metode penelitian yang digunakan adalah metode kualitatif dengan jenis studi kasus. Teknik pengumpulan data menggunakan teknik wawancara medalam, observasi dan dokumentasi. Untuk meyakinkan keabsahan data, triangilasi dilakukan dengan melaksanakan triangulasi sumber dan triangulasi teknik. Informan dalam penelitian ini terdiri dari informan kunci, informan utama dan informan pendukung. Informan kunci adalah Kabid anggaran, kabid perbendaharaan dan kasubid akuntansi dan pelaporan. Sedangkan informan utama dan informan pendukung dipilih dengan teknik snowball sampling. Analisis data dilakukan  dengan tahap pengumpulan data, reduksi data display data dan melakukan membuat kesimpulan. Hasil analisis menunjukkan bahwa Dampak Pandemi Covid-19 menyebabkan Pemerintah Provinsi Riau melakukan refocusing dan realokasi anggaran sebanyak empat kali pergeseran anggaran. Pada tahap penatausahaan dan pertanggungjawaban terdapat permasalahan pencatatan pada Belanja Tidak Terduga yaitu tidak adanya juknis tentang penatausahaan Belanja Tidak Terduga, penentuan batasan belanja untuk keadaan darurat dan mendesak.  Permasalahan lainnya yaitu tidak  adanya data yang valid untuk penyaluran dana  bantuan bagi UMKM yang terdampak Covid-19 serta dokumen yang valid dalam pencatatan bantuan hibah dari pihak ke tiga. Penelitian ini memberikan kontribusi kepada pemerintah dalam membuat kebijakan dalam pengelolaan keuangan pada keadaan darurat bencana. Kata Kunci :  Pandemi Covid-19, Pengelolaan Keungan, Refocusing, Realokasi, Penatausahaan, Pertanggungjawaban

scholarly journals Learning With Heterogeneous Misspecified Models: Characterization and Robustness

Econometrica ◽  
2021 ◽  
Vol 89 (6) ◽  
pp. 3025-3077 ◽  
Author(s):  
J. Aislinn Bohren ◽  
Daniel N. Hauser
Keyword(s):  
Learning Environments ◽  
Unified Framework ◽  
Simple Criterion ◽  
Partisan Bias ◽  
Misspecified Models ◽  
Long Run ◽  
The Face ◽  
Parametric Specification ◽  
The Impact ◽  
Source Of Information

This paper develops a general framework to study how misinterpreting information impacts learning. Our main result is a simple criterion to characterize long‐run beliefs based on the underlying form of misspecification. We present this characterization in the context of social learning, then highlight how it applies to other learning environments, including individual learning. A key contribution is that our characterization applies to settings with model heterogeneity and provides conditions for entrenched disagreement. Our characterization can be used to determine whether a representative agent approach is valid in the face of heterogeneity, study how differing levels of bias or unawareness of others' biases impact learning, and explore whether the impact of a bias is sensitive to parametric specification or the source of information. This unified framework synthesizes insights gleaned from previously studied forms of misspecification and provides novel insights in specific applications, as we demonstrate in settings with partisan bias, overreaction, naive learning, and level‐k reasoning.

Performance Bounds for VDES R-mode

2019 ◽  
Vol 73 (1) ◽  
pp. 92-114 ◽  
Author(s):  
Jan Šafář ◽  
Alan Grant ◽  
Paul Williams ◽  
Nick Ward
Keyword(s):  
Data Exchange ◽  
Estimation Error ◽  
Additive White Gaussian Noise ◽  
Automatic Identification ◽  
Identification System ◽  
Performance Bounds ◽  
Radio Communication ◽  
Very High Frequency ◽  
Radio Communication System ◽  
The Impact

The Very High Frequency (VHF) Data Exchange System (VDES) is a new radio communication system being developed by the international maritime community, with the principal objectives to safeguard existing Automatic Identification System (AIS) core functions and enhance maritime communication applications, based on robust, efficient and secure data transmission with wider bandwidth than the AIS. VDES is also being considered as a potential component of the R-mode concept, where the same signals used for communication are also used for ranging, thus mitigating the impact of disruptions to satellite positioning services. This paper establishes statistical performance bounds on the ranging precision of VDES R-mode, assuming an additive white Gaussian noise propagation channel. Modified Cramér-Rao bounds on the pseudorange estimation error are provided for all waveforms currently proposed for use in terrestrial VDES communications. These are then used to estimate the maximum usable ranges for AIS/VDES R-mode stations. The results show that, under the assumed channel conditions, all of the new VDES waveforms provide better ranging performance than the AIS waveform, with the best performance being achieved using the 100 kHz bandwidth terrestrial VDE waveforms.

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