Piotr Szwed

A new lightweight method for security risk assessment based on fuzzy cognitive maps

Abstract For contemporary software systems, security is considered to be a key quality factor and the analysis of IT security risk becomes an indispensable stage during software deployment. However, performing risk assessment according to methodologies and standards issued for the public sector or large institutions can be too costly and time consuming. Current business practice tends to circumvent risk assessment by defining sets of standard safeguards and applying them to all developed systems. This leads to a substantial gap: threats are not re-evaluated for particular systems and the selection of security functions is not based on risk models. This paper discusses a new lightweight risk assessment method aimed at filling this gap. In this proposal, Fuzzy Cognitive Maps (FCMs) are used to capture dependencies between assets, and FCM-based reasoning is performed to calculate risks. An application of the method is studied using an example of an e-health system providing remote telemonitoring, data storage and teleconsultation services. Lessons learned indicate that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on the effectiveness of the security system.

IOEM - ontology engineering methodology for large systems

The paper presents IOEM, a methodology for ontology development elaborated for the INSIGMA project. Although prepared for a particular use, the methodology is quite general and can be used in a large variety of IT projects requiring ontology components. It is particularly suitable for large and geographically distributed software projects. The methodology is oriented towards applications of ontologies in various phases of a software lifecycle: development and run-time.

An Incremental Map-Matching Algorithm Based on Hidden Markov Model

Map-matching algorithms aim at establishing a vehicle location on a road segment based on positioning data from a variety of sensors: GPS receivers, WiFi or cellular radios. They are integral part of various Intelligent Transportation Systems (ITS) including fleet management, vehicle tracking, navigation services, traffic monitoring and congestion detection. Our work was motivated by an idea of developing an algorithm that can be both utilized for tracking individual vehicles and for monitoring traffic in real-time. We propose a new incremental map-matching algorithm that constructs of a sequence of Hidden-Markov Models (HMMs). Starting from an initial HMM, the next models are developed by alternating operations: expansion and contraction. In the later, the map-matched trace is output. We discuss results of initial experiments conducted for 20 GPS traces, which to test algorithm robustness, were modified by introduction of noise and/or downsampled.

FORMAL ANALYSIS OF USE CASE DIAGRAMS

Use case diagrams play an important role in modeling with UML. Careful modeling is crucialin obtaining a correct and efficient system architecture. The paper refers to the formalanalysis of the use case diagrams. A formal model of use cases is proposed and its constructionfor typical relationships between use cases is described. Two methods of formal analysis andverification are presented. The first one based on a states’ exploration represents a modelchecking approach. The second one refers to the symbolic reasoning using formal methodsof temporal logic. Simple but representative example of the use case scenario verification isdiscussed.

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.

Application of fuzzy ontological reasoning in an implementation of medical guidelines

In this paper we address two problems. The first pertains to implementation of medical guidelines in an e-health system supporting self-management of chronic diseases. The system allows patients to enter observed symptoms and measured parameters, then makes assessment of disease state and informs about necessary actions. We propose to formalize guidelines as sets of fuzzy rules. Fuzziness is introduced to cope with uncertainty resulting from self-observations bias, low quality of sensors and limited patients skills. The second problem is more general. It concerns the reuse of knowledge gathered in ontologies and an application of Semantic Web technologies to perform fuzzy inference. We show that, despite the fact that commonly used ontology languages and supporting tools are not intended to handle vagueness and uncertainty, they can be successfully integrated to represent and execute a set of fuzzy rules. The proposed method consists in refactoring a domain ontology, then introducing additional relations expressing fuzzy properties, encoding Mamdani fuzzy rules in SWRL language and executing them with use of Pellet OWL reasoner. We describe a fuzzy reasoning engine applying this approach and discuss translation of fuzzy rules to SWRL constructs taking as example a complete set of rules formalizing a medical guideline for asthma control assessment.

OpenCL Implementation of PSO Algorithm for the Quadratic Assignment Problem

This paper presents a Particle Swarm Optimization (PSO) algorithm for the Quadratic Assignment Problem (QAP) implemented on OpenCL platform. Motivations to our work were twofold: firstly we wanted to develop a dedicated algorithm to solve the QAP showing both time and optimization performance, secondly we planned to check, if the capabilities offered by popular GPUs can be exploited to accelerate hard optimization tasks requiring high computational power. We were specifically targeting low-cost popular devices, with limited capabilities. The paper discusses the algorithm and its parallel implementation, as well as reports results of tests.

Risk Assessment for SWOP Telemonitoring System Based on Fuzzy Cognitive Maps

For various IT systems security is considered to be a key quality factor. In particular, for health care systems security is of uttermost importance, as it is related to patients’ health and safety. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) approach. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. An application of the method is studied on an example of e-health system providing remote telemonitoring, data storage and teleconsultation services. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.

Video Event Recognition with Fuzzy Semantic Petri Nets

Automated recognition of video events is an important research area in computer vision having many potential applications, e.g. intelligent video surveillance systems or video indexing engines. In this paper we describe components of an event recognition system building up a full processing chain from low-level features extraction to high-level semantic information on detected events. It is comprised of three components: object detection and tracking algorithms, a fuzzy ontology and Fuzzy Semantic Petri Nets (FSPN), a formalism that can be used to specify events and to reason on their occurrence. FSPN are Petri nets coupled with an underlying fuzzy ontology. The ontology stores assertions (facts) concerning object classification and detected relations being an abstraction of the information originating from object tracking algorithms. Fuzzy predicates querying the ontology are used in Petri net transitions guards. Places in FSPN represent scenario steps. Tokens carry information on objects participating in an event and have weights expressing likelihood of an events step occurrence. Introduced fuzziness allow to cope with imprecise information delivered by image analysis algorithms. We describe the architecture of video event recognition system and show examples of successfully recognized events.

Ontology Oriented Storage, Retrieval and Interpretation for a Dynamic Map System

This paper presents the Dynamic Map system, one of the key products of the INSIGMA Project. The main focus is on the map and dynamic data storage subsystem, which utilizes a spatial database and is based on ontologies. First, the data models used are described, including the OpenStreetMap-based structure for the static map and the ontology-driven structure for dynamic parameters and events. The approach to generation of database structures from OWL is described in detail, followed by descriptions of the OSM import process, the GPS tracker module, the sensor state analyzer and the event interpreter. Finally, the planned future enhancements are outlined and discussed.