Grid Enabled Internet Instruments

Komisarczuk, Peter; Seifert, Christian; Pemberton, Dean

doi:10.1109/glocom.2007.366

Cited by 8 publications

(7 citation statements)

References 7 publications

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“…to optimize weight settings for traffic engineering [19], or placed in a data warehouse using a data Grid for later analysis of the network. Our proposed GEII framework [1] is planned to employ Grid technology integrated with sensors/instruments to detect and analyse various aspects of Internet behaviour. We have created a network telescope and an analysis engine based on GT2 and have experimented with client honeypots for detecting malicious web servers using GT2 and the Amazon EC2 experimental compute infrastructure [1].…”

Section: Figure 1 Rtcp Extended Record (Xr)mentioning

confidence: 99%

Effect of rerouting on NGN VoIP quality

Komisarczuk

Koudrin

2007

2007 Australasian Telecommunication Networks and Applications Conference

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In this paper we explore Next Generation Network (NGN) VoIP service quality measurements from end-points as a basis for measuring NGN network quality. Thousand or even millions of end point sensors could be envisaged within an NGN, where each end point could collect data through the RTCP eXtended Record (XR) and using network based data aggregation, sorting and analysis the quality of an NGN could be measured and form part of an NGN control plane. A simulation study provides a basis for determining some of the data that could be gathered within an NGN and analysed within a measurement and control system. An NGN is simulated using layer 3 and layer 2 resiliency techniques with a VOIP mesh overlay acting as a measurement instrument across the network. The data from the simulated measurement grid can be used in conjunction with tomography techniques to detect issues within the NGN and potentially optimise network performance. It is postulated that such a system may include a mesh of active long term sensors as well as consumer end systems and its core may be effectively realized using a Grid computing based analysis engine which is briefly outlined.

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Section: Figure 1 Rtcp Extended Record (Xr)mentioning

confidence: 99%

Effect of rerouting on NGN VoIP quality

Komisarczuk

Koudrin

2007

2007 Australasian Telecommunication Networks and Applications Conference

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“…We identify an Internet sensor grid [17] comprising active and passive measurement systems that encompasses a wide range of malicious activity measurements, allowing potential correlation between different attack components to be determined. Political, business, social, economic and technical difficulties, make a wide scale federated Internet sensor grid a difficult system to build and run.…”

Section: The Internet Sensor Gridmentioning

confidence: 99%

“…Existing work on collective intelligence [26] may also be incorporated but needs to be evaluated to fit with this problem space. Key areas to be developed cover the creation of collaborative sensors and actuators [25,17,28,29], detection and classification of emergent behaviour [3,4], inventing and testing system response and counter-measures. Current basic systems are proving successful, e.g.…”

Section: The Internet Sensor Gridmentioning

confidence: 99%

Internet Sensor Grid: Experiences with Passive and Active Instruments

Komisarczuk

Welch

2010

Communications: Wireless in Developing Countries and Networks of the Future

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Abstract. The Internet is constantly evolving with new emergent behaviours arising; some of them malicious. This paper discusses opportunities and research direction in an Internet sensor grid for malicious behaviour detection, analysis and countermeasures. We use two example sensors as a basis; firstly the honeyclient for malicious server and content identification (i.e. drive-bydownloads, the most prevalent attack vector for client systems) and secondly the network telescope for Internet Background Radiation detection (IBRwhich is classified as unsolicited, non-productive traffic that traverses the Internet, often malicious in nature or origin). Large amounts of security data can be collected from such sensors for analysis and federating honeyclient and telescope data provides a worldwide picture of attacks that could enable the provision of countermeasures. In this paper we outline some experiences with these sensors and analyzing network telescope data through Grid computing as part of an "intelligence layer" within the Internet.

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“…The goal of the Grid Enabled Internet Instruments (GEII) research project [22] is to develop a framework for using Grid technology combined with emerging Internet instrumentation to provide large scale Internet measurement mechanisms, thus enable new quality measures by which we could determine the state of the Internet. Such measures might include a 'Safety Index' or 'Compromise Index' which indicates the potential for a vulnerable computer to be compromised, a "Malicious Web Server Index" being the percentage or attack capacity of malicious web servers on the Internet.…”

Section: Grid Enabled Internet Instrumentsmentioning

confidence: 99%

“…Figure 2.5 shows the proposed architecture of the GEII framework [22]. This shows a number of example instruments (with wrapper envelopes), the central Federated Data Manager, and the Grid services offering processing, storage, security and user interfaces.…”

Section: Grid Enabled Internet Instrumentsmentioning

confidence: 99%

Enhancing Client Honeypots with Grid Services and Workflows

Stirling¹

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<p>Client honeypots are devices for detecting malicious servers on a network. They interact with potentially malicious servers and analyse the Web pages returned to assess whether these pages contain an attack. This type of attack is termed a 'drive-by-download'. Low-interaction client honeypots operate a signature-based approach to detecting known malicious code. High- interaction client honeypots run client applications in full operating systems that are usually hosted by a virtual machine. The operating systems are either internally or externally monitored for anomalous behaviour. In recent years there have been a growing number of client honeypot systems being developed, but there is little interoperability between systems because each has its own custom operational scripts and data formats. By creating interoperability through standard interfaces we could more easily share usage of client honeypots and the data collected. Another problem is providing a simple means of managing an installation of client honeypots. Work ows are a popular technology for allowing end-users to co-ordinate e-science experiments, so these work ow systems can potentially be utilised for client honeypot management. To formulate requirements for management we ran moderate-scale scans of the .nz domain over several months using a manual script-based approach. The main requirements were a system that is user-oriented, loosely-coupled, and integrated with Grid computing|allowing for resource sharing across organisations. Our system design uses Grid services (extensions to Web services) to wrap client honeypots, a manager component acts as a broker for user access, and workflows orchestrate the Grid services. Our prototype wraps our case study - Capture-HPC -with these services, using the Taverna workflow system, and a Web portal for user access. When evaluating our experiences we found that while our system design met our requirements, currently a Java-based application operating on our Web services provides some advantages over our Taverna approach - particularly for modifying workflows, maintainability, and dealing with failure. The Taverna workflows, however, are better suited for the data analysis phase and have some usability advantages. Workflow languages such as Taverna are still relatively immature, so improvements are likely to be made. Both of these approaches are significantly easier to manage and deploy than the previous manual script-based method.</p>

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Grid Enabled Internet Instruments

Cited by 8 publications

References 7 publications

Effect of rerouting on NGN VoIP quality

Effect of rerouting on NGN VoIP quality

Internet Sensor Grid: Experiences with Passive and Active Instruments

Enhancing Client Honeypots with Grid Services and Workflows

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