Rule based expert system for maritime anomaly detection software

There has been an increasing interest for anomaly detection within the maritime domain in recent years. The primary concern of this thesis is to investigate automated methods of anomaly detection within vessel track data. Rulebased expert system for maritime anomaly detection this mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc. The transit of goods occurs over the oceans that cover 23s of the planet and yet are inhabited by human beings.

Rulebased expert system for maritime anomaly detection. In this paper, we present the topology preserving mapping for maritime anomaly detection. Realtime maritime traffic anomaly detection based on. Decision frame designer is a rulebased system designer that allows you to design, debug, profile and generate code for your system. We would provide you an engine, the required development tools and a best practice methodology. An activity has thus been undertaken to implement, within the ckef, a proofofconcept prototype of a rule based expert system to support the analysts regarding this aspect. Then, a framework for ad based on the integration of open and closed data sources is proposed. Open data for anomaly detection in maritime surveillance. The general idea is for the potentials to represent typical patterns of vessels behaviors. A comparative evaluation of anomaly detection algorithms for maritime vi deo surveillance bryan auslander 1, kalyan moy gupta 1, and david w. An activity has thus been undertaken to develop and implement, within the ckef, a proofofconcept prototype of a rulebased expert system rbes to support anomaly detection in the maritime domain. Specifically, the topology preserving mapping is applied as an unsupervised learning method, which captures the vessel behaviors and visualizes the extracted underlying data structure. Rulebased expert system article about rulebased expert. As rulebased expert systems encounter problems, they can apply these rules to narrow down the causes and develop solutions.

This is achieved through the exploitation of techniques from the areas of machine learning and anomaly detection. Faculty of computer science, dalhousie university, halifax, ns, canada. Feature extraction for anomaly detection in maritime. A prototype for a rulebased expert system based on the maritime domain ontologies was developed by edlund et al. The objective of jamocha is to provide a high quality rule engine and expert system shell environment. Topology preserving mapping for maritime anomaly detection. Efficient online anomaly detection for ship systems in. To help governments with this task, since 2004, the international maritime organization imo requires automatic identi. Building a decision frame is a visual process, sparing you of the task of learning a new language. Find out information about rule based expert system. The knowledge patterns discovered from historical data serve as the normal profiles, or baselines or references hereinafter, called normal profiles. A comparative evaluation of anomaly detection algorithms for maritime vi deo surveillance bryan auslander 1, kalyan moy gupta 1. Data integrity assessment for maritime anomaly detection. Dns software is found to be prone to many types of transaction attacks, including.

Fastmaritime anomaly detection using kdtreegaussian. Maritime domain operators analysts have a mandate to be aware of all that is happening within their areas of responsibility. Including the experts knowledge about suspicious activities in the detection process can result in improved ad. Creating an anomaly detection rule anomaly detection rules test the result of saved flow or event searches to search for unusual traffic patterns that occur in your network. Pdf spatiotemporal rulebased analysis of maritime traffic. However, the problem with such a system is that it only incorporates the rules an expert uses to. Machine learning approaches to maritime anomaly detection. Feature extraction for anomaly detection in maritime trajectories joel sundholm masters thesis at csc. Expert systems that use surveillance cameras to detect suspicious behavior have also received attention from researchers. Rulebased expert systems ajith abraham oklahoma state university, stillwater, ok, usa 1 problem solving using heuristics 909 2 what are rulebased systems. Find out information about rulebased expert system. Knowledge based anomaly detection unsworks unsw sydney.

Maritime domain awareness mda is the effective understanding of activities, events and threats in the maritime environment that could impact global safety, security, economic activity or the environment. Rulebasedsupervised vs unsupervised anomaly detection and prediction. Scenariobased intrusion detection method has similar features based on state transition machine, however scenarios of compromise consist of not only sequential events but also random order events and certain scenarios. In particular, we examine hierarchical task network htn and case based algorithms for plan recognition, which detect anomalies by generating expected behaviors for use as a basis for threat detection. However, the problem with such a system is that it only incorporates the rules an expert uses to draw new conclusions. This quality makes pointbased anomaly detection techniques attractive for realtime tasks. The planned and purposing vessel movement should generate highlycorrelated ais data, and this can be used for movement anomaly detection. Apr 01, 2020 as rule based expert systems encounter problems, they can apply these rules to narrow down the causes and develop solutions. A limited subset of natural language supplemented by specified relations and operators is used to formulate the rules.

Hence, a rule based anomaly detection method based on a single threshold would not be able to detect the anomaly. Densitybased methods, data streaming methods, and time series methods. Maritime domain operatorsanalysts have a mandate to be aware of all that is happening within their areas of responsibility. The overall purpose of the knowledge acquisition facility is to provide a convenient and ef. The user interaction with the system is based on a userfriendly graphical interface. This program helps you build expert systems in decision frame, decision tree and decision table formats. Anomaly detection rules test the results of saved flow or events searches to detect when unusual traffic patterns occur in your network. The development of a rulebased expert system for anomaly detection can be valuable, as it incorporates expert knowledge in the detection of anomalies. Rulebased expert system for maritime anomaly detection nasaads. Analysis of full trajectory data and anomaly detection would require datadriven approaches such as artificial neural network based or statistical methods. Anomaly detection is an important part of datarelated studies and is often based on aforementioned data quality dimensions.

A formal methods approach austin jones, zhaodan kong, calin belta abstractas the complexity of cyberphysical systems increases, so does the number of ways an adversary can disrupt them. A framework for anomaly detection in maritime trajectory. Seecoast applies rulebased and learningbased pattern recognition. Anomaly detection in the maritime domain, proceedings of. A prototype for a rule based expert system based on the maritime domain ontologies was developed by edlund et al. Signature based detection on ip flows an intrusion detection system that could inspect every network packet would be ideal, but is impractical. Sensors, and command, control, communications, and intelligence c3i technologies for homeland security. Us20080215576a1 fusion and visualization for multiple. Each rule specifies a relation, recommendation, directive, strategy or heuristic and has the if condition then action structure.

This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc. In rulebased expert systems knowledge is represented in an ifthen form. However, it is mentioned that it could be used for the detection of anomalous cargo transshipment. Anomaly detection ad is one of the many techniques available. A rulebased fuzzy expert system was illustrated by jasinevicius, r. A rule based fuzzy expert system was illustrated by jasinevicius, r. Rule based expert system for maritime anomaly detection jean roy proc. Maritime anomaly detection through interactive visualization to improve the operators confidence in a system, an anomaly detection process where the user is involved is proposed in riveiro et al. Roy, j rulebased expert system for maritime anomaly detection. An expert system based on a collection of rules that a human expert would follow in dealing with a problem. Information retrieval techniques in rulebased expert systems. This comes with the intent to evaluate whether such a rbes is an appropriate approach for anomaly detection. The behavior rule based intrusion detection which uses correlations of packetpayload data patterns and communication patterns. Anomaly detection algorithms and techniques for realworld.

Anomaly detection is the identification of data points, items, observations or events that do not conform to the expected pattern of a given group. The system is able to identify a number of basic spatial and kinematical relations between objects, and then deduce different situations, e. Maritime security and anomaly detection bigdataocean. Unfortunately, there is no selflearning super software that takes care of all the predictive work of the it environment. The operational community has long identified anomaly detection systems as vital for. However, we need to be wary of the pitfalls of rulebased anomaly pattern detection.

A real time expert system for anomaly detection of. Without a doubt, anomaly detection techniques are also being incorporated into modern intrusion detection systems. On the other hand, a limited number of analyzed data points means realtime calculation and decision making. While the rulebased approach is conceptually simple and easy to implement, it. Rulebased expert system for maritime anomaly detection jean roy proc. A similar approach was also employed by edlund et al 14.

In a rulebased expert system, the knowledge is represented as a set of rules. Expert systems based on computer vision technology and surveillance cameras are widely used in various fields, e. Experiment results demonstrate that the proposed mtmad framework is capable of effectively detecting anomalies in maritime trajectories. Penny analytics operates an online analytics service, specializing in outlier detection, where you upload files online and get results when the job is complete. Trakker is a customizable datadriven software to identify process weaknesses through data analytics. Anomaly detection in the maritime domain, proceedings of spie. For example, a system might monitor an electrical grid, in which case it would have a number of rules to determine the cause of a fault, so it can recommend an action. Apr 03, 2008 an activity has thus been undertaken to develop and implement, within the ckef, a proofofconcept prototype of a rule based expert system rbes to support anomaly detection in the maritime domain. While they might not be advertised specifically as an ads, ids products of the near future will generate alerts based on deviant system behavior. We then developed an anomaly detection algorithm based on this model in which an indicator is used to evaluate suspicious behavior and scores trajectory behavior according to the defined outlying features. Open data for anomaly detection in maritime surveillance shahrooz abghari.

These anomalies occur very infrequently but may signify a large and significant threat such as cyber intrusions or fraud. Fastmaritime anomaly detection using kdtreegaussian processes. We observe that the test values, both in the regions with normal condition, and in the regions were we have altered the signals, lie within the normal operating mode of that specific signal. Proceedings paper anomaly detection in the maritime domain. The automated identification system of vessel movements receives a huge. On the other hand, maritime domain experts have the required knowledge and experience for finding maritime anomalies.

A comparative evaluation of anomaly detection algorithms. May 19, 2015 we then developed an anomaly detection algorithm based on this model in which an indicator is used to evaluate suspicious behavior and scores trajectory behavior according to the defined outlying features. Host based vs network bases intrusion detection systems. Interactive visualization applications for maritime anomaly. We propose a novel vessel anomaly detection framework for minimizing false alarms in the maritime domain with the help of contextual information. Sensors, and command, control, communications, and intelligence c3i technologies for homeland security and homeland defense ix, spie 7666. Associated to any study, a normality must be established as the assessment of an anomalous thing is relative, and a distance must be chosen for distance computation. Once we take this perspective on anomaly detection, it becomes clear that a simple rulebased approach is not sufcient.

Numenta, is inspired by machine learning technology and is based on a theory of the neocortex. This quality makes point based anomaly detection techniques attractive for realtime tasks. Rulebased expert systems 911 the explanation facility allows a user to understand how the expert system arrived at certain results. Laxhammar 6 uses a gaussian mixture model for maritime anomaly detection while johansson and falkman 7 use a bayesian network. Automatic identification system ais, anomaly detection, bayesian network, maritime environment, situational awareness, threat assessment, white shipping. These automated approaches produce very good results for. Interactive visualization applications for maritime. Anomaly detection in maritime data based on geometrical analysis of trajectories behrouz haji soleimani. Signature based detection systems such as snort have been widely deployed by enterprises for network security, but are limited by the scaling factors described above. Anomaly detection is heavily used in behavioral analysis and other forms of.

Behavioral rules test event and flow traffic according to seasonal traffic levels and trends. Anomaly detection rules typically the search needs to accumulate data before the anomaly rule returns any result that identifies. As a result, software vendors attempt to offer predictive analytics of the environment via software. May 05, 2010 maritime domain operatorsanalysts have a mandate to be aware of all that is happening within their areas of responsibility. At the core of the system lies a significantly modified version of the fuzzy artmap neural network classifier. International society for optics and photonics, 2010. A comparative evaluation of anomaly detection algorithms for. Anomaly detection in oceans is a priority for governmental organizations. Anomaly detection in maritime data based on geometrical. We compare their performance with a behavior recognition algorithm on simulated riverine maritime traffic. Along this line of thought, this paper describes a proofofconcept prototype of a rulebased expert system implementing automated rulebased reasoning in support of maritime anomaly detection. Realtime maritime traffic anomaly detection based on sensors. Knnlpe performs global densitybased anomaly detection.

Anomaly detection, deviation and fraud detection software. An activity has thus been undertaken to implement, within the ckef, a proofofconcept prototype of a rulebased expert system to support the analysts regarding this aspect. Science, princeton university, princeton, nj 08544 duf. This has been accomplished in the security space, known as intrusion detection and anomaly detection. An automated anomaly detection system should act as a reasoning prosthetic for military experts, by applying expert knowledge in the analysis of each track. The present invention is a method for detecting anomalies against normal profiles and for fusing and visualizing the results from multiple anomaly detection systems in a quantifying and unifying user interface. The best approach to detecting anomalies progress software. In essence we use ripple down rules to partition a domain, and add new. One of the major flaws of rulebased systems is that they dont adapt. Numenta, avora, splunk enterprise, loom systems, elastic xpack, anodot, crunchmetrics are some of the top anomaly detection software. In particular, we examine hierarchical task network htn and casebased algorithms for plan recognition, which detect anomalies by generating expected behaviors for use as a basis for threat detection. The novelty of the method lies in employing the technique of artificial potential fields for traffic pattern extraction.

When the condition part of a rule is satisfied, the rule is said to fire and the action part is executed. Machine analytics, anomaly detection and analytics for machine data and log files. The technology can be applied to anomaly detection in servers and. Rule based expert system for maritime anomaly detection. Rulebased anomaly pattern detection for detecting disease. In this talk, i will take about three different families of anomaly detection algorithms. The maritime anomaly or abnormal movement detection is one of the. The developed system is successfully designed as rule based expert system supported with object oriented modeling. This necessitates automated anomaly detection methods to detect possible threats. Anomaly detectors or event recognition systems for maritime situational.