Current Status of Cyber Security in the Surveillance Data Processing Systems in Europe

2018 ◽  
Author(s):  
Marian Jancik ◽  
Simon Holoda ◽  
Milan DZUNDA ◽  
Branislav Kandera
Keyword(s):  
Data Processing ◽  
Cyber Security ◽  
Surveillance Data ◽  
Current Status

scholarly journals Current Status of Cyber Security in Artas Surveeillance Data Processing System

2019 ◽  
pp. 12-17
Author(s):  
Marián Jančík ◽  
Peter Dzurovčin
Keyword(s):  
Data Processing ◽  
Cyber Security ◽  
Processing System ◽  
Current Status ◽  
Security Assessment ◽  
Data Processing System ◽  
Security Vulnerabilities ◽  
Security Challenges ◽  
Critical Issues ◽  
Traffic Systems

The objective of this paper is to present a comprehensive status of cyber security challenges in ARTAS surveillance data processing system. The cyber security is a major concern of current Air Traffic Systems. It is mandated by European Union as well as national law. Therefore, EUROCONTROL as the provider the ARTAS application conducted a comprehensive security assessment is to identify security vulnerabilities of the systems. For this purpose, a grey-box penetration testing was conducted by EUROCONTROL’s security experts. The numerous findings are currently mitigated by the fact that ARTAS systems should be isolated and restricted in a secure architecture. The next version of ARTAS application is addressing the most critical issues.

scholarly journals The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview

2016 ◽  
Vol 9 (3) ◽  
pp. 1279-1301 ◽  
Author(s):  
Rosemary Munro ◽  
Rüdiger Lang ◽  
Dieter Klaes ◽  
Gabriele Poli ◽  
Christian Retscher ◽  
...  
Keyword(s):  
Data Processing ◽  
Instrument Design ◽  
Data Consistency ◽  
Current Status ◽  
Web Pages ◽  
Ozone Monitoring ◽  
Level 1 ◽  
Future Work ◽  
Ground Calibration

Abstract. The Global Ozone Monitoring Experiment-2 (GOME-2) flies on the Metop series of satellites, the space component of the EUMETSAT Polar System. In this paper we will provide an overview of the instrument design, the on-ground calibration and characterization activities, in-flight calibration, and level 0 to 1 data processing. The current status of the level 1 data is presented and points of specific relevance to users are highlighted. Long-term level 1 data consistency is also discussed and plans for future work are outlined. The information contained in this paper summarizes a large number of technical reports and related documents containing information that is not currently available in the published literature. These reports and documents are however made available on the EUMETSAT web pages and readers requiring more details than can be provided in this overview paper will find appropriate references at relevant points in the text.

scholarly journals Improved Testing of AI-Based Anomaly Detection Systems Using Synthetic Surveillance Data

Proceedings ◽  
2020 ◽  
Vol 59 (1) ◽  
pp. 9
Author(s):  
Antoine Chevrot ◽  
Alexandre Vernotte ◽  
Pierre Bernabe ◽  
Aymeric Cretin ◽  
Fabien Peureux ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Cyber Security ◽  
Surveillance Data ◽  
Automatic Identification ◽  
Identification System ◽  
Surveillance Systems ◽  
Sea Transport ◽  
Detection Model ◽  
Detection Systems ◽  
Anomalous Data

Major transportation surveillance protocols have not been specified with cyber security in mind and therefore provide no encryption nor identification. These issues expose air and sea transport to false data injection attacks (FDIAs), in which an attacker modifies, blocks or emits fake surveillance messages to dupe controllers and surveillance systems. There has been growing interest in conducting research on machine learning-based anomaly detection systems that address these new threats. However, significant amounts of data are needed to achieve meaningful results with this type of model. Raw, genuine data can be obtained from existing databases but need to be preprocessed before being fed to a model. Acquiring anomalous data is another challenge: such data is much too scarce for both the Automatic Dependent Surveillance–Broadcast (ADS-B) and the Automatic Identification System (AIS). Crafting anomalous data by hand, which has been the sole method applied to date, is hardly suitable for broad detection model testing. This paper proposes an approach built upon existing libraries and ideas that offers ML researchers the necessary tools to facilitate the access and processing of genuine data as well as to automatically generate synthetic anomalous surveillance data to constitute broad, elaborated test datasets. We demonstrate the usability of the approach by discussing work in progress that includes the reproduction of related work, creation of relevant datasets and design of advanced anomaly detection models for both domains of application.

Current Status of an On-Line Computer Data Processing System for High Energy Counter and Spark Chamber Experiments

1965 ◽  
Vol 12 (4) ◽  
pp. 222-223 ◽  
Author(s):  
K. J. Foley ◽  
R. S. Jones ◽  
S. J. Lindenbaum ◽  
W. A. Love ◽  
S. Ozaki ◽  
...  
Keyword(s):  
Data Processing ◽  
Processing System ◽  
High Energy ◽  
Current Status ◽  
Data Processing System ◽  
Computer Data ◽  
On Line ◽  
Computer Data Processing

scholarly journals Gaia: Astrometric performance and current status of the project

2009 ◽  
Vol 5 (S261) ◽  
pp. 296-305 ◽  
Author(s):  
Lennart Lindegren
Keyword(s):  
Solar System ◽  
Data Processing ◽  
Preliminary Data ◽  
Scientific Data ◽  
Current Status ◽  
Fundamental Physics ◽  
Implementation Phase ◽  
Optical Reference ◽  
Measurement Principle

AbstractThe scientific objectives of the Gaia mission cover areas of galactic structure and evolution, stellar astrophysics, exoplanets, solar system physics, and fundamental physics. Astrometrically, its main contribution will be the determination of millions of absolute stellar parallaxes and the establishment of a very accurate, dense and faint non-rotating optical reference frame. With a planned launch in spring 2012, the project is in its advanced implementation phase. In parallel, preparations for the scientific data processing are well under way within the Gaia Data Processing and Analysis Consortium. Final mission results are expected around 2021, but early releases of preliminary data are expected. This review summarizes the main science goals and overall organisation of the project, the measurement principle and core astrometric solution, and provide an updated overview of the expected astrometric performance.

scholarly journals Industry 4.0 : India’s Defence Industry Needs Smart Manufacturing

2019 ◽  
Vol 8 (11S) ◽  
pp. 476-485
Keyword(s):  
Cyber Security ◽  
Production Management ◽  
Industrial Revolution ◽  
Secondary Data ◽  
Current Status ◽  
Primary Data ◽  
Smart Manufacturing ◽  
Sample Population ◽  
Private Industry ◽  
Defence Industry

The Fourth Industrial Revolution (I4.0) envisages fusion of technologies across the physical, digital and biological worlds, and is transforming production, management and governance into a Smart Manufacturing paradigm. It is based on exploitation of current and futuristic technologies such as Internet of Things, 3D Printing (Additive Manufacturing), 5 G connectivity, cyber security, robotics and automation. More than any other industry, defence innovation and manufacturing demand high quality and precision products. This paper brings out the need and current status of India’s defence manufacturing sector (state-controlled Defence Research and Development Organisation(DRDO), Ordnance Factories (OFs), Defence Public Sector Undertakings (DPSUs), and Private Industry including MSMEs) with regard to I4.0, and seeks to establish what needs to be done in adopting features of smart manufacturing, to make it globally competitive. Primary data obtained from a small but knowledgeable sample population, duly analysed with descriptive statistics; followed by secondary data sources, establish the influencing factors. Interpretive Structural Modelling helped formulate a framework for smart manufacturing in India’s defence industry. The paper concludes with recommendations with regard to governmental, and industry stakeholders.

scholarly journals The Cherenkov Telescope Array production system proto-type for large-scale data processing and simulations

2021 ◽  
Vol 251 ◽  
pp. 02029
Author(s):  
Luisa Arrabito ◽  
Johan Bregeon ◽  
Patrick Maeght ◽  
Michèle Sanguillon ◽  
Andrei Tsaregorodtsev ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Data Processing ◽  
Production System ◽  
Large Scale ◽  
Current System ◽  
High Energy ◽  
Current Status ◽  
Telescope Array ◽  
Cherenkov Telescope ◽  
Very High

The Cherenkov Telescope Array (CTA) is the next-generation instrument in the very-high energy gamma ray astronomy domain. It will consist of tens of Cherenkov telescopes deployed in 2 arrays at La Palma (Spain) and Paranal (ESO, Chile) respectively. Currently under construction, CTA will start operations around 2023 for a duration of about 30 years. During operations CTA is expected to produce about 2 PB of raw data per year plus 5-20 PB of Monte Carlo data. The global data volume to be managed by the CTA archive, including all versions and copies, is of the order of 100 PB with a smooth growing profile. The associated processing needs are also very high, of the order of hundreds of millions of CPU HS06 hours per year. In order to optimize the instrument design and study its performances, during the preparatory phase (2010-2017) and the current construction phase, the CTA consortium has run massive Monte Carlo productions on the EGI grid infrastructure. In order to handle these productions and the future data processing, we have developed a production system based on the DIRAC framework. The current system is the result of several years of hardware infrastructure upgrades, software development and integration of different services like CVMFS and FTS. In this paper we present the current status of the CTA production system and its exploitation during the latest large-scale Monte Carlo campaigns.

Towards Intelligent Data Processing for Automated Determination of Information System Assets

2020 ◽  
pp. 147-160
Author(s):  
Andrey Fedorchenko ◽  
Elena Doynikova ◽  
Igor Kotenko
Keyword(s):  
Information System ◽  
Data Processing ◽  
Cyber Security ◽  
Risk Model ◽  
Security Assessment ◽  
Event Analysis ◽  
Event Correlation ◽  
Automated Discovery ◽  
Intelligent Data Processing ◽  
Processing Techniques

The chapter discusses how the intelligent data processing techniques, namely, the event correlation, can be used for automated discovery of information system assets. The authors believe that solving of this task will allow more accurate and detailed construction of the risk model for cyber security assessment. This task is complicated by the features of configuration and operation of modern information systems. The chapter describes different types of event analysis, including statistical, structural, dynamic, applied to this task. The authors propose a technique that incorporates determining the types of object characteristics, the types of objects (system assets), and their hierarchy based on the statistical analysis of system events. Significant attention is given to the stage of source data pre-processing. In addition, the developed technique has the broad application prospects to discover the inappropriate, dubious, and harmful information. The case studies and experiments that demonstrate an application of the developed technique are provided and analyzed.

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.

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