118 resultados para Detection system

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The use of a charged-particle microbeam provides a unique opportunity to control precisely, the number of particles traversing individual cells and the localization of dose within the cell. The accuracy of 'aiming' and of delivering a precise number of particles crucially depends on the design and implementation of the collimation and detection system. This report describes the methods available for collimating and detecting energetic particles in the context of a radiobiological microbeam. The arrangement developed at the Gray Laboratory uses either a 'V'-groove or a thick-walled glass capillary to achieve 2-5 mu m spatial resolution. The particle detection system uses an 18 mu m thick transmission scintillator and photomultiplier tube to detect particles with >99% efficiency.

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Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified using a ruled based method.

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Synchrophasor systems will play a crucial role in next generation Smart Grid monitoring, protection and control. However these systems also introduce a multitude of potential vulnerabilities from malicious and inadvertent attacks, which may render erroneous operation or severe damage. This paper proposes a Synchrophasor Specific Intrusion Detection System (SSIDS) for malicious cyber attack and unintended misuse. The SSIDS comprises a heterogeneous whitelist and behavior-based approach to detect known attack types and unknown and so-called ‘zero-day’ vulnerabilities and attacks. The paper describes reconnaissance, Man-in-the-Middle (MITM) and Denial-of-Service (DoS) attack types executed against a practical synchrophasor system which are used to validate the real-time effectiveness of the proposed SSIDS cyber detection method.

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Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified via Snort rules.

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The increased interconnectivity and complexity of supervisory control and data acquisition (SCADA) systems in power system networks has exposed the systems to a multitude of potential vulnerabilities. In this paper, we present a novel approach for a next-generation SCADA-specific intrusion detection system (IDS). The proposed system analyzes multiple attributes in order to provide a comprehensive solution that is able to mitigate varied cyber-attack threats. The multiattribute IDS comprises a heterogeneous white list and behavior-based concept in order to make SCADA cybersystems more secure. This paper also proposes a multilayer cyber-security framework based on IDS for protecting SCADA cybersecurity in smart grids without compromising the availability of normal data. In addition, this paper presents a SCADA-specific cybersecurity testbed to investigate simulated attacks, which has been used in this paper to validate the proposed approach.

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In modern semiconductor manufacturing facilities maintenance strategies are increasingly shifting from traditional preventive maintenance (PM) based approaches to more efficient and sustainable predictive maintenance (PdM) approaches. This paper describes the development of such an online PdM module for the endpoint detection system of an ion beam etch tool in semiconductor manufacturing. The developed system uses optical emission spectroscopy (OES) data from the endpoint detection system to estimate the RUL of lenses, a key detector component that degrades over time. Simulation studies for historical data for the use case demonstrate the effectiveness of the proposed PdM solution and the potential for improved sustainability that it affords.

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A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

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Emerging cybersecurity vulnerabilities in supervisory control and data acquisition (SCADA) systems are becoming urgent engineering issues for modern substations. This paper proposes a novel intrusion detection system (IDS) tailored for cybersecurity of IEC 61850 based substations. The proposed IDS integrates physical knowledge, protocol specifications and logical behaviours to provide a comprehensive and effective solution that is able to mitigate various cyberattacks. The proposed approach comprises access control detection, protocol whitelisting, model-based detection, and multi-parameter based detection. This SCADA-specific IDS is implemented and validated using a comprehensive and realistic cyber-physical test-bed and data from a real 500kV smart substation.

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The spontaneous formation of the neurotoxic carcinogen acrylamide in a wide range of cooked foods has recently been discovered. These foods include bread and other bakery products, crisps, chips, breakfast cereals, and coffee. To date, the diminutive size of acrylamide (71.08Da) has prevented the development of screening immunoassays for this chemical. In this study, a polyclonal antibody capable of binding the carcinogen was produced by the synthesis of an immunogen comprising acrylamide derivatised with 3-mercaptobenzoic acid (3-MBA), and its conjugation to the carrier protein bovine thyroglobulin. Antiserum from the immunised rabbit was harvested and fully characterised. it displayed no binding affinity for acrylamide or 3-MBA but had a high affinity for 3-MBA-derivitised acrylamide. The antisera produced was utilised in the development of an ELISA based detection system for acrylamide. Spiked water samples were assayed for acrylamide content using a previously published extraction method validated for coffee, crispbread, potato, milk chocolate and potato crisp matrices. Extracted acrylamide was then subjected to a rapid 1-h derivatisation with 3-MBA, pre-analysis. The ELISA was shown to have a high specificity for acrylamide, with a limit of detection in water samples of 65.7 mu g kg(-1), i.e. potentially suitable for acrylamide detection in a wide range of food commodities. Future development of this assay will increase sensitivity further. This is the first report of an immunoassay capable of detecting the carcinogen, as its small size has necessitated current analytical detection via expensive, slower, physico-chemical techniques such as Gas or Liquid Chromatography coupled to Mass Spectrometry. (c) 2007 Elsevier B.V. All rights reserved.

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The Intrusion Detection System (IDS) is a common means of protecting networked systems from attack or malicious misuse. The deployment of an IDS can take many different forms dependent on protocols, usage and cost. This is particularly true of Wireless Intrusion Detection Systems (WIDS) which have many detection challenges associated with data transmission through an open, shared medium, facilitated by fundamental changes at the Physical and MAC layers. WIDS need to be considered in more detail at these lower layers than their wired counterparts as they face unique challenges. The remainder of this chapter will investigate three of these challenges where WiFi deviates significantly from that of wired counterparts:

• Attacks Specific to WiFi Networks: Outlining the additional threats which WIDS must account for: Denial of Service, Encryption Bypass and AP Masquerading attacks.

• The Effect of Deployment Architecture on WIDS Performance: Demonstrating that the deployment environment of a network protected by a WIDS can influence the prioritisation of attacks.

• The Importance of Live Data in WiFi Research: Investigating the different choices for research data sources with an emphasis on encouraging live network data collection for future WiFi research.

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The IDS (Intrusion Detection System) is a common means of protecting networked systems from attack or malicious misuse. The development and rollout of an IDS can take many different forms in terms of equipment, protocols, connectivity, cost and automation. This is particularly true of WIDS (Wireless Intrusion Detection Systems) which have many more opportunities and challenges associated with data transmission through an open, shared medium.
The operation of a WIDS is a multistep process from origination of an attack through to human readable evaluation. Attention to the performance of each of the processes in the chain from attack detection to evaluation is imperative if an optimum solution is to be sought. At present, research focuses very much on each discrete aspect of a WIDS with little consideration to the operation of the whole system. Taking a holistic view of the technology shows the interconnectivity and inter-dependence between stages, leading to improvements and novel research areas for investigation.
This chapter will outline the general structure of Wireless Intrusion Detection Systems and briefly describe the functions of each development stage, categorised into the following 6 areas:
• Threat Identification,
• Architecture,
• Data Collection,
• Intrusion Detection,
• Alert Correlation,
• Evaluation.
These topics will be considered in broad terms designed for those new to the area. Focus will be placed on ensuring the readers are aware of the impact of choices made at early stages in WIDS development on future stages.

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A proof-of-concept study was reported on analysis of antigen-antibody recognition based on resonant Rayleigh scattering response of single Au nanoparticles on a microimaging chamber. As benefited by a traditional dark-field microscope and a spectrograph, tiny 30 nm Au nanoparticles were effectively used as nanosensors to monitor changes in refractive index induced by every single binding of the adsorbates. The individual Au nanoparticles were observed with very high signal-to-noise ratio, and a LSPR ?max shift of about 2.5 nm accounting for the detection of PSA antigen with concentration as low as 0.1 pg ml-1 was recorded. This resulted in the successful demonstration of a non-labelling detection system for proteins as well as thousands of different chemical or biological species with possibility of miniaturization and multiplexing scheme.

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Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.