Maritime piracy situation modelling with dynamic Bayesian networks

A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a larger DBN. The application of synthetic data fabrication of maritime vessel behaviour is considered. Behaviour of various vessels in a maritime piracy situation is simulated. A means to integrate information from context based external factors that influence behaviour is provided. Simulated observations of the vessels kinematic states are generated. The generated data may be used for the purpose of developing and evaluating counter-piracy methods and algorithms. A novel methodology for evaluating and optimising behavioural models such as the proposed model is presented. The log-likelihood, cross entropy, Bayes factor and the Bhattacharyya distance measures are applied for evaluation. The results demonstrate that the generative model is able to model both spatial and temporal datasets.The Advanced Sensors and Electronics Defence (ASED) Centre of KACST through the Council for Scientific and Industrial Research (CSIR) and the South African National Research Foundation (NRF).http://www.elsevier.com/locate/inffushj201

A Bayesian network to manage risks of maritime piracy against offshore oil fields

International audienceIn recent years, pirate attacks against shipping and oil field installations have become more frequent and more serious. This article proposes an innovative solution to the problem of offshore piracy from the perspective of the entire processing chain: from the detection of a potential threat to the implementation of a response. The response to an attack must take into account multiple variables: the characteristics of the threat and the potential target, existing protection tools, environmental constraints, etc. The potential of Bayesian networks is used to manage this large number of parameters and identify appropriate counter-measures

Bayesian Networks in the Management of Oil Field Piracy Risk

International audienceIn recent years, pirate attacks against shipping and oil field installations have become more frequent and more serious. The SARGOS system provides an innovative solution that addresses the problem from the perspective of the entire processing chain; from the detection of a potential threat to the implementation of a response. The response to an attack must take into account multiple variables: the characteristics of the threat and the potential target, existing protection tools, environmental constraints, etc. The potential of Bayesian networks is used to manage this large number of parameters and identify appropriate counter-measures

Integration of a Bayesian network for response planning in a maritime piracy risk management system

International audienceThis article describes an innovative system to protect offshore oil infrastructure against maritime piracy. To detect and respond efficiently to this threat, many factors must be taken into account, including the potential target, the protection methods already in place and operational and environmental constraints, etc. To improve the handling of this complex issue, we have designed a system to manage the entire processing chain; from threat identification to implementation of the response. The system implements Bayesian networks in order to capture the multitude of parameters and their inherent uncertainties, and to identify and manage potential responses. This article describes the system architecture, the integrated Bayesian network and its contribution to response planning

The Contribution of Bayesian Networks to Manage Risks of Maritime Piracy against Oil Offshore Fields

International audienceIn recent years pirate attacks against shipping and oil fields have continued to increase in quantity and severity. For example, the attack against the Exxon Mobil oil rig in 2010 off the coast of Nigeria ended in the kidnap of 19 crew members and a reduction in daily oil production of 45,000 barrels, which resulted in an international rise in the price of oil. This example is a perfect illustration of current weaknesses in existing anti-piracy systems. The SARGOS project proposes an innovative system to address this problem. It takes into account the entire threat treatment process; from the detection of a potential threat to implementation of the response. The response to an attack must take into account all of the many parameters related to the threat, the potential target, the available protection resources, environmental constraints, etc. To manage these parameters, the power of Bayesian networks is harnessed to identify potential countermeasures and the means to manage them

Quantitative maritime security assessment: a 2020 vision

Maritime security assessment is moving towards a proactive risk-based regime. This opens the way for security analysts and managers to explore and exploit flexible and advanced risk modelling and decision-making approaches in maritime transport. In this article, following a review of maritime security risk assessment, a generic quantitative security assessment methodology is developed. Novel mathematical models for security risk analysis and management are outlined and integrated to demonstrate their use in the developed framework. Such approaches may be used to facilitate security risk modelling and decision making in situations where conventional quantitative risk analysis techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in risk and uncertainty modelling technology are suggested with respect to maritime security risk quantification and management

Loitering behaviour detection of boats at sea

We present in this paper a technique for Loitering detection based on the analysis of activity zones of the monitored area. Activity zones are learnt online employing a soft computing-based algorithm which takes as input the trajectory of object mobiles appearing on the scene. Statistical properties on zone occupancy and transition between zones makes it possible to discover abnormalities without the need to learn abnormal models beforehand. We have applied this approch to the PETS2017 IPATCH dataset and addressed the challenge on detecting skiff boats loitering around a protected ship, which eventually is attacked by the skiffs. Our results show that we can detect the suspicious behaviour on time to trigger an early warning

A unified model for context-based behavioural modelling and classification

A unified Bayesian model that simultaneously performs behavioural modelling, information fusion and classification is presented. The model is expressed in the form of a dynamic Bayesian network (DBN). Behavioural modelling is performed by tracking the continuous dynamics of a entity and incorporating various contextual elements that influence behaviour. The entity is classified according to its behaviour. Classification is expressed as a conditional probability of the entity class given its tracked trajectory and the contextual elements. Inference in the DBN is performed using a derived Gaussian sum filter. The model is applied to classify vessels, according to their behaviour, in a maritime piracy situation. The novel aspects of this work include the unified approach to behaviour modelling and classification, the way in which contextual information is fused, the unique approach to classification according to behaviour and the associated derived Gaussian sum filter inference algorithm.South African National Research Foundation (NRF) and the the Advanced Sensors and Electronics Defence (ASED) Centre of KACST through the Council for Scientific and Industrial Research (CSIR).http://www.elsevier.com/locate/eswa2016-11-30hb201

A novel flexible model for piracy and robbery assessment of merchant ship operations

Maritime piracy and robbery can not only cause logistics chain disruption leading to economic consequences but also result in loss of lives, and short- and long-term health problems of seafarers and passengers. There is a justified need for further investigation in this area of paramount importance. This study analyses maritime piracy and robbery related incidents in terms of the major influencing factors such as ship characteristics and geographical locations. An analytical model incorporating Bayesian reasoning is proposed to estimate the likelihood of a ship being hijacked in the Western Indian or Eastern African region. The proposed model takes into account the characteristics of the ship, environment conditions and the maritime security measures in place in an integrated manner. Available data collected from the Global Integrated Shipping Information System (GISIS) together with expert judgement is used to develop and demonstrate the proposed model. This model can be used by maritime stakeholders to make cost-effective anti-piracy decisions in their operations under uncertainties. Discussions are given on industrial response to maritime piracy in order to minimize the risk to ships exposed to attacks from pirates. Further recommendations on how maritime security and piracy may be best addressed in terms of maritime security measures are outlined

INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK

This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling