Assessing Data Usefulness for Failure Analysis in Anonymized System Logs

System logs are a valuable source of information for the analysis and understanding of systems behavior for the purpose of improving their performance. Such logs contain various types of information, including sensitive information. Information deemed sensitive can either directly be extracted from system log entries by correlation of several log entries, or can be inferred from the combination of the (non-sensitive) information contained within system logs with other logs and/or additional datasets. The analysis of system logs containing sensitive information compromises data privacy. Therefore, various anonymization techniques, such as generalization and suppression have been employed, over the years, by data and computing centers to protect the privacy of their users, their data, and the system as a whole. Privacy-preserving data resulting from anonymization via generalization and suppression may lead to significantly decreased data usefulness, thus, hindering the intended analysis for understanding the system behavior. Maintaining a balance between data usefulness and privacy preservation, therefore, remains an open and important challenge. Irreversible encoding of system logs using collision-resistant hashing algorithms, such as SHAKE-128, is a novel approach previously introduced by the authors to mitigate data privacy concerns. The present work describes a study of the applicability of the encoding approach from earlier work on the system logs of a production high performance computing system. Moreover, a metric is introduced to assess the data usefulness of the anonymized system logs to detect and identify the failures encountered in the system.Comment: 11 pages, 3 figures, submitted to 17th IEEE International Symposium on Parallel and Distributed Computin

Toward understanding crowd mobility in smart cities through the Internet of Things

Understanding crowd mobility behaviors would be a key enabler for crowd management in smart cities, benefiting various sectors such as public safety, tourism and transportation. This article discusses the existing challenges and the recent advances to overcome them and allow sharing information across stakeholders of crowd management through Internet of Things (IoT) technologies. The article proposes the usage of the new federated interoperable semantic IoT platform (FIESTA-IoT), which is considered as "a system of systems". The platform can support various IoT applications for crowd management in smart cities. In particular, the article discusses two integrated IoT systems for crowd mobility: 1) Crowd Mobility Analytics System, 2) Crowd Counting and Location System (from the SmartSantander testbed). Pilot studies are conducted in Gold Coast, Australia and Santander, Spain to fulfill various requirements such as providing online and offline crowd mobility analyses with various sensors in different regions. The analyses provided by these systems are shared across applications in order to provide insights and support crowd management in smart city environments.The pilot study in Gold Coast is conducted in collaboration with NEC Australia. This work has been partially funded by the Spanish Government (MINECO) under Grant Agreement No. TEC2015-71329-C2-1-R ADVICE (Dynamic Provisioning of Connectivity in High Density 5G Wireless Scenarios) project and by the EU Horizon 2020 Programme under Grant Agreements No. 731993 AUTOPILOT (Automated Driving Progressed by Internet Of Things), 643943 FIESTAIoT (Federated Interoperable Semantic IoT Testbeds and Applications), and 643275 FESTIVAL (Federated Interoperable Smart ICT Services Development and Testing Platforms) projects and the joint project by NEC Laboratories Europe and Technische Universität Dortmund. The content of this paper does not reflect the official opinion of the Spanish Government or European Union. Responsibility for the information and views expressed therein lies entirely with the authors

A model-driven privacy compliance decision support for medical data sharing in Europe

Objectives: Clinical practitioners and medical researchers often have to share health data with other colleagues across Europe. Privacy compliance in this context is very important but challenging. Automated privacy guidelines are a practical way of increasing users' awareness of privacy obligations and help eliminating unintentional breaches of privacy. In this paper we present an ontology-plus-rules based approach to privacy decision support for the sharing of patient data across European platforms. Methods: We use ontologies to model the required domain and context information about data sharing and privacy requirements. In addition, we use a set of Semantic Web Rule Language rules to reason about legal privacy requirements that are applicable to a specific context of data disclosure. We make the complete set invocable through the use of a semantic web application acting as an interactive privacy guideline system can then invoke the full model in order to provide decision support. Results: When asked, the system will generate privacy reports applicable to a specific case of data disclosure described by the user. Also reports showing guidelines per Member State may be obtained. Conclusion: The advantage of this approach lies in the expressiveness and extensibility of the modelling and inference languages adopted and the ability they confer to reason with complex requirements interpreted from high level regulations. However, the system cannot at this stage fully simulate the role of an ethics committee or review board. © Schattauer 2011

Beyond categorisation:Refining the relationship between subjects and objects in health research regulation

In this article, we argue that the relationship between ‘subject’ and ‘object’ is poorly understood in health research regulation (HRR), and that it is a fallacy to suppose that they can operate in separate, fixed silos. By seeking to perpetuate this fallacy, HRR risks, among other things, objectifying persons by paying insufficient attention to human subjectivity, and the experiences and interests related to being involved in research. We deploy the anthropological concept of liminality – concerned with processes of transformation and change over time – to emphasise the enduring connectedness between subject and object in these contexts. By these means, we posit that regulatory frameworks based on processual regulation can better recognise and encompass the fluidity and significance of these relationships, and so ground more securely the moral legitimacy and social licence for human health research

Stakeholder involvement, motivation, responsibility, communication: How to design usable security in e-Science

e-Science projects face a difficult challenge in providing access to valuable computational resources, data and software to large communities of distributed users. Oil the one hand, the raison d'etre of the projects is to encourage members of their research communities to use the resources provided. Oil the other hand, the threats to these resources from online attacks require robust and effective Security to mitigate the risks faced. This raises two issues: ensuring that (I) the security mechanisms put in place are usable by the different users of the system, and (2) the security of the overall system satisfies the security needs of all its different stakeholders. A failure to address either of these issues call seriously jeopardise the success of e-Science projects.The aim of this paper is to firstly provide a detailed understanding of how these challenges call present themselves in practice in the development of e-Science applications. Secondly, this paper examines the steps that projects can undertake to ensure that security requirements are correctly identified, and security measures are usable by the intended research community. The research presented in this paper is based Oil four case studies of c-Science projects. Security design traditionally uses expert analysis of risks to the technology and deploys appropriate countermeasures to deal with them. However, these case studies highlight the importance of involving all stakeholders in the process of identifying security needs and designing secure and usable systems.For each case study, transcripts of the security analysis and design sessions were analysed to gain insight into the issues and factors that surround the design of usable security. The analysis concludes with a model explaining the relationships between the most important factors identified. This includes a detailed examination of the roles of responsibility, motivation and communication of stakeholders in the ongoing process of designing usable secure socio-technical systems such as e-Science. (C) 2007 Elsevier Ltd. All rights reserved

Advancing security information and event management frameworks in managed enterprises using geolocation

Includes bibliographical referencesSecurity Information and Event Management (SIEM) technology supports security threat detection and response through real-time and historical analysis of security events from a range of data sources. Through the retrieval of mass feedback from many components and security systems within a computing environment, SIEMs are able to correlate and analyse events with a view to incident detection. The hypothesis of this study is that existing Security Information and Event Management techniques and solutions can be complemented by location-based information provided by feeder systems. In addition, and associated with the introduction of location information, it is hypothesised that privacy-enforcing procedures on geolocation data in SIEMs and meta- systems alike are necessary and enforceable. The method for the study was to augment a SIEM, established for the collection of events in an enterprise service management environment, with geo-location data. Through introducing the location dimension, it was possible to expand the correlation rules of the SIEM with location attributes and to see how this improved security confidence. An important co-consideration is the effect on privacy, where location information of an individual or system is propagated to a SIEM. With a theoretical consideration of the current privacy directives and regulations (specifically as promulgated in the European Union), privacy supporting techniques are introduced to diminish the accuracy of the location information - while still enabling enhanced security analysis. In the context of a European Union FP7 project relating to next generation SIEMs, the results of this work have been implemented based on systems, data, techniques and resilient features of the MASSIF project. In particular, AlienVault has been used as a platform for augmentation of a SIEM and an event set of several million events, collected over a three month period, have formed the basis for the implementation and experimentation. A "brute-force attack" misuse case scenario was selected to highlight the benefits of geolocation information as an enhancement to SIEM detection (and false-positive prevention). With respect to privacy, a privacy model is introduced for SIEM frameworks. This model utilises existing privacy legislation, that is most stringent in terms of privacy, as a basis. An analysis of the implementation and testing is conducted, focusing equally on data security and privacy, that is, assessing location-based information in enhancing SIEM capability in advanced security detection, and, determining if privacy-enforcing procedures on geolocation in SIEMs and other meta-systems are achievable and enforceable. Opportunities for geolocation enhancing various security techniques are considered, specifically for solving misuse cases identified as existing problems in enterprise environments. In summary, the research shows that additional security confidence and insight can be achieved through the augmentation of SIEM event information with geo-location information. Through the use of spatial cloaking it is also possible to incorporate location information without com- promising individual privacy. Overall the research reveals that there are significant benefits for SIEMs to make use of geo-location in their analysis calculations, and that this can be effectively conducted in ways which are acceptable to privacy considerations when considered against prevailing privacy legislation and guidelines

People want reassurance when making privacy-related decisions — Not technicalities

Online service users sometimes need support when making privacy-related decisions. Humans make decisions either slowly, by painstakingly consulting all possible information, or quickly, by relying on cues to trigger heuristics. Human emotions elicited by the decision context affects decisions, often without the decision maker being aware of it. We wanted to determine how an information-based decision can be supported, and also to understand which cues are used by a heuristics-based approach. Our first study enhanced understanding of underlying encryption mechanisms using metaphors. Our participants objected to efforts to make them ‘technical experts’, expressing a need for reassurance instead. We fed their free-text responses into a Q-sort, to determine which cues they rely on to make heuristic-based decisions. We confirmed the desire for reassurance. Our third study elicited ‘cyber stories’: Unprompted narratives about cyber-related experiences to detect emotional undertones in this domain. Responses revealed a general negativity, which is bound to influence cybersecurity-related decisions