To help governments with this task, since 2004, the international maritime organization imo requires automatic identi. Automatic identification system ais, anomaly detection, bayesian network, maritime environment, situational awareness, threat assessment, white shipping. We developed an anomaly detection tool using a based algorithm that can detect anomalies in a rule set of prerecorded tracks using their curvature, speed and weave. Machine learning approach to fraud detection the times. Rule based expert system for maritime anomaly detection. The general idea is for the potentials to represent typical patterns of vessels behaviors. 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.
Anomaly detection is heavily used in behavioral analysis and other forms of. A similar approach was also employed by edlund et al 14. The system enables experts in the maritime domain to characterise abnormal ship behaviour based on formal semantic properties. On the other hand, maritime domain experts have the required knowledge and experience for finding maritime anomalies. An intrusion detection system ids is a device or software application that monitors a network or systems for malicious activity or policy violations. A speaker recognition is one of the most useful biometric recognition techniques in this world where insecurity is a major threat. 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. The proposed potential field based method has been examined using a webbased anomaly detection system strand seafaring transport anomaly detection implemented for this study. The planned and purposing vessel movement should generate highlycorrelated ais data, and this can be used for movement anomaly detection. But when a rules based fraud detection system gets operationalised, one starts with say 100 fraud scenarios and 100 rules to handle it. These rules are used by the system to make conclusions about the securityrelated data from the intrusion detection system. However, it is not clear which a nomaly detection algorithms should be used for domain s such as groundbased maritime video surveillance. A signature detection system identifies traffic or application data patterns assumed to be malicious, while anomaly detection systems compare activities with normal baseline.
Absolute division distance, relative division distance, and cosine division distance. These anomalies occur very infrequently but may signify a large and significant threat such as cyber intrusions or fraud. An automated anomaly detection system should act as a reasoning prosthetic for military experts, by applying expert knowledge in the analysis of each track. Maritime anomaly detection using gaussian process active learning. Roy 8 proposed a rule based expert system implementing automated rule based reasoning in support of maritime anomaly detection. Including the experts knowledge about suspicious activities in the detection process can result in improved ad. We developed an anomaly detection tool using a based algorithm that can detect anomalies in a rule. Anomaly detection in maritime data based on geometrical. 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. We devised a method that can quantify the amount of curvature in a recorded surface track.
Rulebased expert system for maritime anomaly detection roy, jean 20100427 00. The output of the overall system is a set of rules that implement state transition logic on an expert system, and are able to determine if other time series signatures deviate significantly. The contribution in this paper is a gp based model for normal behaviour combined with a kdtree approximation for training and prediction. At saab systems, a prototype for a rule based expert system, based on an ontology for situation assessment in the domain of sea surveillance, has been developed 3. Deepmind beating lee sedol at go, as well as the use of neural networks to solve important fundamental ai tasks. Nextgeneration intrusion detection expert system nides afterwards, an improved version of ides called the next generation intrusion detection expert system nides was proposed in 1995, which is a hybrid system 4, 5 nides is a centralized, multihost based hybrid detection anomaly and misuse system that performs real. Sep 17, 2009 ebusiness technologies ebtech introduction to rulebased applications adrian giurca, ebusiness technologies, craiova, march 2009 dr. May 10, 2020 as rule based expert systems encounter problems, they can apply these rules to narrow down the causes and develop solutions. A self adaptive multiagent system for abnormal behavior detection in maritime surveillance. Topology preserving mapping for maritime anomaly detection. A rule based fuzzy expert system was illustrated by jasinevicius, r. The definitions of rule based system depend almost entirely on expert systems, which are system that mimic the reasoning of human expert in solving a knowledge intensive problem. Instead of representing knowledge in a declarative, static way as a set of things which are true, rulebased system represent knowledge in terms of a set of rules that tells what to do or what to conclude in different situations. Artificial neural networks for misuse detection essay.
Results the developed rule based expert system meets the user with a welcome screen. Maritime anomaly detection methods using the historical patterns of life as the reference can be distinguished into two main classes, based on the format of input trajectories. Wso2 cep, esper although simple, static rules based systems tend to be brittle and complex. Situation awareness with systems of systems springerprofessional. Specifically, the topology preserving mapping is applied as an unsupervised learning method, which captures the vessel behaviors and visualizes the extracted underlying data structure. A prototype for a rulebased expert system based on the maritime domain ontologies was developed by edlund, gronkvist, lingvall, and sviestins 2006 that could detect some of the anomalies regarding the spatial and kinematic relation between objects such as simple scenarios for hijacking, piloting and smuggling. Interactive visualization applications for maritime anomaly. Anomaly detection my views of the world and systems. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc. A huge innovation in data science over the past five years has been the ascendance of neural network models, rebranded as deep learning models, over symbolic, rule based expert systems. A rule based system uses rules as the knowledge representation for knowledge coded into the system 4 1416171820.
Expert systems are the most common form of rule based intrusion detection approaches 8, 24. Situation awareness, systems of systems, and maritime safety and security. If decisions need inference, then you can use a rule based or expert system e. Learning states and rules for time series anomaly detections. International society for optics and photonics, 2010. The novelty of the method lies in employing the technique of artificial potential fields for traffic pattern extraction. Unsupervised learning techniques using gaussian mixture models to learn patterns of motion behaviour are presented in 3. These automated approaches produce very good results for. Intrusion detection using mfcc, vqa and lbg algorithm.
Programming such systems requires a high level of skill and the incorporation of a big knowledge base. Elements of a rule based expert system artificial intelligence. Anomaly detection in the maritime domain, proceedings of. Rules are extremely easy to understand and are developed by domain experts and consultants who translate their experience and best practices to code to make automated decisions. Rulebased expert system for maritime anomaly detection how we measure reads a read is counted each time someone views a publication summary such as the title, abstract, and list of authors. Maritime domain operators analysts have a mandate to be aware of all that is happening within their areas of responsibility. Obtaining maritime anomaly data can be difficult or even impractical. The output of the overall system is a set of rules that implement state transition logic on an. Laxhammar 6 uses a gaussian mixture model for maritime anomaly detection while johansson and falkman 7 use a bayesian network. This book discusses various aspects, challenges, and solutions for developing. Open data for anomaly detection in maritime surveillance.
An expert system consists of a set of rules that encode the knowledge of a human expert. Anomaly detection in oceans is a priority for governmental organizations. 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. The ideas introduced in this book explore the relationships among rule based systems, machine. Then, a framework for ad based on the integration of open and closed data sources is proposed. In proceedings of spiethe international society for optical engineering, usa.
Expert systems permit the incorporation of an extensive amount of human. Jasinevicius and petrauskas 9 also used a rule based expert map. Maritime domain operatorsanalysts have a mandate to be aware of all that is happening within their areas of responsibility. Maritime abnormality detection using gaussian processes. Seecoast applies rule based and learningbased pattern recognition algorithms to alert illegal.
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. A rule based track anomaly detection algorithm for maritime force protection. I bought another copy, dismantled the second copy and read it this year in 2015, section by section, taking notes and mentally digesting the whole thing. Abnormal behavior recognition of inland river ferryboat. Theres a lot of hype and headline around this stuff just now. A complex event processing approach to detect abnormal. An enhanced spatial reasoning ontology for maritime anomaly detection arnaud vandecasteele, aldo napoli. A comparative evaluation of anomaly detection algorithms for.
Designed, configured and tested to be used in the extreme. Therefore, we use a generative approach to vary and control the difficulty of anomaly detection tasks. The input to our overall anomaly detection system is normal time series data like the graph at the top left corner of figure 1. This quality makes point based anomaly detection techniques attractive for realtime tasks. A siem system combines outputs from multiple sources and. Rule based expert systems solve problems by applying a set of programmed rules to available information. The algorithm for abnormal movement detection is based on three division distances. At the core of the system lies a significantly modified version of the fuzzy artmap neural network classifier. Rulebased anomaly pattern detection for detecting disease. Fastmaritime anomaly detection using kdtreegaussian processes. Most current approaches to the process of detecting intrusions utilize some form of rule based analysis. Abstract this paper presents a novel approach for pattern extraction and anomaly detection in maritime vessel traf. Next screen takes as input the student number and in order to match student name and record action logs of the user. Typically rarely necessary for end users to access, and often dangerous from a security standpoint.
A selfadaptive multiagent system for abnormal behavior detection. A comparative evaluation of anomaly detection algorithms. Dorothy elizabeth denning, born august 12, 1945, is a usamerican information security researcher known for latticebased access control lbac, intrusion detection systems ids, and other cyber security innovations. Densitybased anomaly detection in the maritime domain. Open data for anomaly detection in maritime surveillance shahrooz abghari. However, the expert human interaction is needed while setting movement tra. Part of the lecture notes in computer science book series lncs, volume. The speed and accuracy of the approximation is reported along with the results of anomaly detection. In this article, we propose a rulebased method for data integrity assessment, with rules built from the system technical specifications and by domain experts, and. Furthermore, identifying those rules is often a complex and subjective task. Multilayer perceptrons networks for an intelligent. Rule based analysis relies on sets of predefined rules that are provided by an administrator, automatically created by the system, or both. Event detection in marine time series data springerlink.
School of navigation,wuhan university of technology,wuhan 430063,china. Anomaly detection is the identification of data points, items, observations or events that do not conform to the expected pattern of a given group. While the rule based approach is conceptually simple and. Fastmaritime anomaly detection using kdtreegaussian. These generally take the form of conditional sentences the computer can use to logically check data to reach a conclusion.
In this paper, we present the topology preserving mapping for maritime anomaly detection. Signature based detection on ip flows an intrusion detection system that could inspect every network packet would be ideal, but is impractical. On the other hand, a limited number of analyzed data points means realtime calculation and decision making. Advantages of rule based expert systems modular nature. This allows encapsulating knowledge and expansion of the expert system done in a a easy way. Rulebased expert system for maritime anomaly detection. By gradually adjusting the limits, the system will improve its ability to recognize conditions that identify risks for casting defects. Users are able to specify and execute spatial rules that are directly integrated into the ontology and a map interface linked to the ontology displays the results of the inferences obtained. 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. Datadriven detection and contextbased classification of. Potential fields in maritime anomaly detection ewa osekowska, stefan axelsson, bengt carlsson blekinge institute of technology, karlskrona, sweden. A new maritime surveillance framework and expert based decision support system is presented in this article. There are several approaches to maritime domain awareness.
The open data anomaly detection system odads is designed for traffic monitoring and detecting anomalies in the maritime domain by using open and closed data sources. The definitions of rulebased system depend almost entirely on expert systems, which are system that mimic the reasoning of human expert in solving a knowledge intensive problem. With over 30 years of cbrn detection experience, bruker has developed a unique capability in. In rule based expert systems, knowledge base is also called production memory as rules in the form of ifthen are called productions. Realtime maritime traffic anomaly detection based on sensors. Webservice based systems for maritime situational a. For example, a two component rule would be gender male and age decile 4.
Seecoast applies rulebased and learningbased pattern recognition algorithms to. In paper presented at the proceedings of spie the international society for, optical engineering vol. For example, a knowledge based system, including a proposed representation of knowledge, inference engine, and series of rules is given in 1 and 2. Interactive visualization applications for maritime. Intelligent program encapsulates most of the knowledge, including possibly knowledge representations of rules, frames, defaults, and has a hierarchies, etc. Jasinevicius and petrauskas 9 also used a rule based expert map but combining with fuzzy logic for a port security system. Further, models for di erent kinds of anomalies may need to be combined or considered to increase the certainty of an anomaly being detected. Knowledge discovery using genetic algorithm for maritime. Once we take this perspective on anomaly detection, it becomes clear that a simple rulebased approach is not sufcient. Instead of representing knowledge in a declarative, static way as a set of things which are true, rulebased system represent knowledge in terms of a set of rules that tells what to do or what. Its applicability has been demonstrated in several publications, examining its scalability, modeling capabilities and detection performance. Rulebased expert systems for supporting university students.
We address these two issues by comparing families of global and local anomaly detection algorithms on tracks extracted from ground based maritime surveillance videos. We compare their performance with a behavior recognition algorithm on simulated riverine maritime traffic. Multiple components are joined together by alogical and. Data integrity assessment for maritime anomaly detection. Part of the lecture notes in computer science book series lncs. In this case, two further types of systems can be distinguished, that is, point and trajectory systems. Point based systems make decisions based on momentary parameters of vessels such as velocity, position, course, etc. The best and only book on rule based ai that describes in detail a real world rule based ai system.
Huang liang 1,liu yi 1,wen yuanqiao 1,2,zhou chunhui 1,2,zhang fan 1 1. A variety of anomaly detection algorithms have been applied to surveillance tasks for detecting threats with some success. Hubei key laboratory of inland shipping technology,wuhan 430063,china. Feature extraction for anomaly detection in maritime trajectories. An enhanced spatial reasoning ontology for maritime. Another categorization of maritime traffic anomaly detection systems refers to data that specify vessel behavior. Rule based expert system for maritime anomaly detection jean roy proc. These limits are stored in a database for alloys and are used in the condition part of the rule based expert system. Adrian giurca brandenbu slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Instead of operating on the lowlevel data from maritime sensors, the rule based expert system proposed in operates on a highlevel ontology. Abnormal ship behavior is detected by executing reasoning rules that refer directly to the ontology and which are defined by experts in the maritime domain.
I read this entire book when it first came out i am that old. Machine learning approaches to maritime anomaly detection. Rulebased expert system for maritime anomaly detection nasaads. Integration of a selforganizing map and a virtual pheromone. Third screen is designed for taking course list from the user figure 2. Maritime security and anomaly detection bigdataocean. Any malicious activity or violation is typically reported either to an administrator or collected centrally using a security information and event management siem system. Critical to marine anomaly detection is an interpretation of the data that allows the salient features of the desired anomaly to be identi ed, laxhammar et al 2009. An activity has thus been undertaken to implement, within the ckef, a proofofconcept prototype of a rule based expert system to. Drools if decisions have temporal conditions, you can use a complex event processing system e. A fuzzy expert system introduced by jasinevicius and petrauskas 3 that takes into account the vessel type. Rulebased expert system article about rulebased expert. The transit of goods occurs over the oceans that cover 23s of the planet and yet are inhabited by human beings. A prototype for a rulebased expert system based on the maritime domain ontologies was developed by edlund et al.
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. Based on the created model of normality, the system can then perform anomaly detection on current realworld maritime traf. Both signature detection and anomaly detection systems have advantages and drawbacks. Specifically, the topology preserving mapping is applied as an unsupervised learning method, which captures the vessel behaviors and visualizes the.
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