Concetta Pragliola

Quantitative Security Risk Assessment and Management for Railway Transportation Infrastructures

Scientists have been long investigating procedures, models and tools for the risk analysis in several domains, from economics to computer networks. This paper presents a quantitative method and a tool for the security risk assessment and management specifically tailored to the context of railway transportation systems, which are exposed to threats ranging from vandalism to terrorism. The method is based on a reference mathematical model and it is supported by a specifically developed tool. The tool allows for the management of data, including attributes of attack scenarios and effectiveness of protection mechanisms, and the computation of results, including risk and cost/benefit indices. The main focus is on the design of physical protection systems, but the analysis can be extended to logical threats as well. The cost/benefit analysis allows for the evaluation of the return on investment, which is a nowadays important issue to be addressed by risk analysts.

Wireless Sensor Data Fusion for Critical Infrastructure Security

Wireless Sensor Networks (WSN) are being investigated by the research community for resilient distributed monitoring. Multiple sensor data fusion has proven as a valid technique to improve detection effectiveness and reliability. In this paper we propose a theoretical framework for correlating events detected by WSN in the context of critical infrastructure protection. The aim is to develop a decision support and early warning system used to effectively face security threats by exploiting the advantages of WSN. The research addresses two relevant issues: the development of a middleware for the integration of heterogeneous WSN (SeNsIM, Sensor Networks Integration and Management) and the design of a model-based event correlation engine for the early detection of security threats (DETECT, DEcision Triggering Event Composer & Tracker). The paper proposes an overall system architecture for the integration of the SeNsIM and DETECT frameworks and provides example scenarios in which the system features can be exploited.

White Paper on Industrial Applications of Computer Vision and Pattern Recognition

The paper provides a summary of the contributions to the industrial session at ICIAP2013, describing a few practical applications of Video Analy- sis, in the Surveillance and Security field. The session has been organized to stimulate an open discussion within the scientific community of CVPR on new emerging research areas which deserve particular attention, and may contribute to the improvement of industrial applications in the near future.

Evaluating the effects of MJPEG compression on motion tracking in metro railway surveillance

Video content analytics is being increasingly employed for the security surveillance of mass-transit systems. The growing number of cameras, the presence of legacy networks, the limited bandwidth of wireless links, are some of the issues which highlight the importance of evaluating the performance of motion tracking against different levels of video compression. In this paper, we report the results of such an evaluation considering false-negative and false-positive metrics applied to videos captured from cameras installed in a real metro-railway environment. The evaluation methodology is based on the manual generation of the Ground Truth on selected videos at growing levels of MJPEG compression, and on its comparison with the Algorithm Result automatically generated by the Motion Tracker. The computation of reference performance metrics is automated by a tool developed in Matlab. Results are discussed with respect to the main causes of false detections, and hints are provided for further industrial applications.

Trustworthiness Evaluation of Multi-sensor Situation Recognition in Transit Surveillance Scenarios

Physical Security Information Management (PSIM) systems are a recent introduction in the surveillance of critical infrastructures, like those used for mass-transit. In those systems, different sensors are integrated as separate event detection devices, each of them generating independent alarms. In order to lower the rate of false alarms and provide greater situation awareness for surveillance operators, we have developed a framework – namely DETECT – for correlating information coming from multiple heterogeneous sensors. DETECT uses detection models based on (extended) Event Trees in order to generate higher level warnings when a known threat scenario is being detected. In this paper we extend DETECT by adopting probabilistic models for the evaluation of threat detection trustworthiness on reference scenarios. The approach also allows for a quantitative evaluation of model sensitivity to sensor faults. The results of a case-study in the transit system domain demonstrate the increase of trust one could expect when using scenarios characterized in a probabilistic way for the threat detection instead of single-sensor alarms. Furthermore, we show how a model analysis can serve at design time to support decisions about the type and redundancy of detectors.

A Study on Multiformalism Modeling of Critical Infrastructures

This paper explores the possibility of using multiformalism techniques for critical infrastructure modeling and proposes a general scheme for intra and inter infrastructure models. Multiformalism approaches allow modelers to adapt the choice of formal languages to the nature, complexity and abstraction layer of the subsystems to be modeled. Another advantage is the possibility of reusing existing (and validated) dependability models and solvers. Complexity and heterogeneity are managed through modularity, and composition allows for representing structural or functional dependencies.

A robust approach for on-line and off-line threat detection based on event tree similarity analysis

The security of railway and mass-transit systems is increasingly dependant on the effectiveness of integrated Security Management Systems (SMS), which are meant to detect threats and to provide operators with information required for alarm verification purposes. In order to lower the false alarm rate and improve the detection reliability of threat scenarios, event correlation capabilities need to be integrated into the SMS. In this paper an existing approach based on a-priori defined event patterns is extended using a heuristic situation recognition approach which is more robust to both imperfect scenario modeling (human faults) and missed detections (sensor faults). The approach is based on similarity analysis between the event trees representing scenarios and it is effective both on-line and off-line. Applied on-line, it allows for an earlier and more fault-tolerant threat detection, since scenario matching is not required to be complete nor exact. Applied off-line, its effectiveness is twofold: first, it allows for detecting redundancies when updating the scenario repository; secondly, it enhances the post-event forensic search of suspicious behaviors not previously stored in the scenario repository. The strategy is being experimented in the context of railway protection.

Railway Infrastructure Security

This comprehensive monograph addresses crucial issues in the protection of railway systems, with the objective of enhancing the understanding of railway infrastructure security. Based on analyses by academics, technology providers and railway operators, it explains how to assess terrorist and criminal threats, design countermeasures, and implement effective security strategies. In so doing, it draws upon a range of experiences from different countries in Europe and beyond. The book is the first to be devoted entirely to this subject. It will serve as a timely reminder of the attractiveness of the railway infrastructure system as a target for criminals and terrorists and, more importantly, as a valuable resource for stakeholders and professionals in the railway security field aiming to develop effective security based on a mix of methodological, technological and organizational tools. Besides researchers and decision makers in the field, the book will appeal to students interested in critical infrastructure protection.

Towards Automated Drone Surveillance in Railways: State-of-the-Art and Future Directions

The usage of UAV (Unmanned Aerial Vehicles) – widely known as ‘drones’ – is being increasingly investigated in a variety of surveillance scenarios. Being an emerging technology, several challenges still need to be tackled in order to make drones suitable in real applications with strict performance, dependability and privacy requirements. In particular, the monitoring of transit infrastructures represents one critical domain in which drones could be of huge help to reduce costs and possibly increase the granularity of surveillance. Furthermore, drones pave the way to the implementation of smart-sensing functionalities expanding current capabilities in railway monitoring, to support automation, safety of operations, prognostics and even forensic analyses. In this paper we provide a survey of current drone technology and their possible applications to automated railway surveillance, taking into account technical issues and environmental constraints. A current experimentation with drone intelligent video will be addressed, highlighting some preliminary results and future perspectives.

Optimisation of security system design by quantitative risk assessment and genetic algorithms

The design of physical security systems for critical infrastructures is a delicate task that requires a balance between the cost of protection mechanisms and their expected effect on risk mitigation. This paper presents an approach usable to support the design of security systems by automatically optimising some parameters, basing on external constraints (e.g., limited available budget) and using quantitative risk assessment. Risk assessment is performed using a software tool that implements a quantitative methodology. The methodology accounts for the attributes of threats (frequency, system vulnerability, expected consequences) and protection mechanisms (cost, effectiveness, coverage, etc.). The optimisation is performed by means of genetic algorithms with the objective of achieving the set of parameters that minimises the risk while fitting external budget constraints, hence maximising the return on investment. The paper also describes an example application of the approach to the design of physical security systems for metro railways.