{"title":"A Context-Aware, Confidence-Disclosing and Fail-Operational Dynamic Risk Assessment Architecture","authors":"Patrik Feth, R. Adler, D. Schneider","doi":"10.1109/EDCC.2018.00041","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00041","url":null,"abstract":"Future automotive systems will be highly automated and they will cooperate to optimize important system qualities and performance. Established safety assurance approaches and standards have been designed with manually controlled stand-alone systems in mind and are thus not fit to ensure safety of this next generation of systems. We argue that, given frequent dynamic changes and unknown contexts, systems need to be enabled to dynamically assess and manage their risks. In doing so, systems become resilient from a safety perspective, i.e. they are able to maintain a state of acceptable risk even when facing changes. This work presents a Dynamic Risk Assessment architecture that implements the concepts of context-awareness, confidence-disclosure and fail-operational. In particular, we demonstrate the utilization of these concepts for the calculation of automotive collision risk metrics, which are at the heart of our architecture.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128935665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mostafa Farshchi, I. Weber, Raffaele Della Corte, A. Pecchia, M. Cinque, Jean-Guy Schneider, J. Grundy
{"title":"Contextual Anomaly Detection for a Critical Industrial System Based on Logs and Metrics","authors":"Mostafa Farshchi, I. Weber, Raffaele Della Corte, A. Pecchia, M. Cinque, Jean-Guy Schneider, J. Grundy","doi":"10.1109/EDCC.2018.00033","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00033","url":null,"abstract":"Recent advances in contextual anomaly detection attempt to combine resource metrics and event logs to uncover unexpected system behaviors at run-time. This is highly relevant for critical software systems, where monitoring is often mandated by international standards and guidelines. In this paper, we analyze the effectiveness of a metrics-logs contextual anomaly detection technique in a middleware for Air Traffic Control systems. Our study addresses the challenges of applying such techniques to a new case study with a dense volume of logs, and finer monitoring sampling rate. Guided by our experimental results, we propose and evaluate several actionable improvements, which include a change detection algorithm and the use of time windows on contextual anomaly detection.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126819626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How to Assess the Dependability of Applications on Top of the Blockchain: Novel Research Challenges","authors":"M. Cinque, C. Esposito","doi":"10.1109/EDCC.2018.00037","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00037","url":null,"abstract":"It is nowadays extremely popular to devise applications of top of the blockchain technology, due to the flourishing of several open-source platforms and the progressive success of this technology outside its traditional cryptocurrency domain. Testing these applications is particularly challenging and traditionally limited to the performance and functionality verification. How-ever, the progressive adoption of such a technology in critical domains is calling for dependability guarantees. This paper highlights the challenges related to the dependability assessment of these applications, and sketches a possible research direction.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122936254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gerhard Habiger, F. Hauck, Johannes Köstler, Hans P. Reiser
{"title":"Resource-Efficient State-Machine Replication with Multithreading and Vertical Scaling","authors":"Gerhard Habiger, F. Hauck, Johannes Köstler, Hans P. Reiser","doi":"10.1109/EDCC.2018.00024","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00024","url":null,"abstract":"State-machine replication (SMR) enables transparent and delayless masking of node faults. It can tolerate crash faults and malicious misbehavior, but usually comes with high resource costs, not only by requiring multiple active replicas, but also by providing the replicas with enough resources for the expected peak load. This paper presents a vertical resource-scaling solution for SMR systems in virtualized environments, which can dynamically adapt the number of available cores to current load. In similar approaches, benefits of CPU core scaling are usually small due to the inherent sequential execution of SMR systems in order to achieve determinism. In our approach, we utilize sophisticated deterministic multithreading to avoid this bottleneck and experimentally demonstrate that core scaling then allows SMR systems to effectively tailor resources to service load, dramatically reducing service provider costs.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121588991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploratory Study of Machine Learning Techniques for Supporting Failure Prediction","authors":"João R. Campos, M. Vieira, E. Costa","doi":"10.1109/EDCC.2018.00014","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00014","url":null,"abstract":"The growing complexity of software makes it difficult or even impossible to detect all faults before deployment, and such residual faults eventually lead to failures at runtime. Online Failure Prediction (OFP) is a technique that attempts to avoid or mitigate such failures by predicting their occurrence based on the analysis of past data and the current state of a system. Given recent technological developments, Machine Learning (ML) algorithms have shown their ability to adapt and extract knowledge in a variety of complex problems, and thus have been used for OFP. Still, they are highly dependent on the problem at hand, and their performance can be influenced by different factors. The problem with most works using ML for OFP is that they focus only on a small set of prediction algorithms and techniques, although there is no comprehensive study to support their choice. In this paper, we present an exploratory analysis of various ML algorithms and techniques on a dataset containing failure data. The results show that, for the same data, different algorithms and techniques directly influence the prediction performance and thus should be carefully selected.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132246631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal Deployment of Security Policies: Application to Industrial Control Systems","authors":"Z. Ismail, J. Leneutre, A. Fourati","doi":"10.1109/EDCC.2018.00030","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00030","url":null,"abstract":"The management of security resources in a system always comes with a tradeoff. Given technical and budget constraints, the defender focuses on deploying the set of security countermeasures that offer the best level of system protection. However, optimizing the configuration and deployment of defense countermeasures for efficient attack detection and mitigation remains a challenging task. In this paper, we leverage the information present in an attack graph, representing the evolution of the state of the attacker in the system, to tackle the problem of finding the optimal security policy that offers the maximum level of system protection. Our solution can be used to assist asset owners to prioritize the deployment of security countermeasures and respond to intrusions efficiently. We validate our approach on an Advanced Metering Infrastructure (AMI) case study.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123635498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Silva, Tânia Basso, Regina L. O. Moraes, D. Elia, S. Fiore
{"title":"A Re-Identification Risk-Based Anonymization Framework for Data Analytics Platforms","authors":"H. Silva, Tânia Basso, Regina L. O. Moraes, D. Elia, S. Fiore","doi":"10.1109/EDCC.2018.00026","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00026","url":null,"abstract":"Preserving individual privacy is one of the major issues in the context of Big Data, since handling huge volumes of data may contribute to the disclosure of sensitive or personally identifiable information. In fact, even when data is anonymized there is a risk of re-identification through privacy attacks. This paper presents a re-identification risk-based anonymization framework for big data analytics platforms. This framework is based on anonymization policies and allows applying anonymization techniques and models in two stages: during the ETL process and before exporting the statistical results of data analytics. This second stage evaluates the data re-identification risk and increases the anonymity level if it is necessary to reduce this risk. Although generic, the implementation of the framework reported in this work was integrated into Ophidia as a case study. Privacy attacks were performed to check the effectiveness of the re-identification process. Results are promising, showing a low probability of re-identification in two different scenarios.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114820533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Coppolino, S. D'Antonio, Giovanni Mazzeo, L. Romano, Luigi Sgaglione
{"title":"Exploiting New CPU Extensions for Secure Exchange of eHealth Data at the EU Level","authors":"L. Coppolino, S. D'Antonio, Giovanni Mazzeo, L. Romano, Luigi Sgaglione","doi":"10.1109/EDCC.2018.00015","DOIUrl":"https://doi.org/10.1109/EDCC.2018.00015","url":null,"abstract":"Cross-border healthcare requires that secure mechanisms for patient data exchange among distinct eHealth infrastructures be implemented. OpenNCP is a major initiative for achieving interoperability of eHealth data among European Member States. It is an Open Source implementation of a broker-based solution that enables the exchange of clinical data among countries having different languages and regulations. It provides some level of protection - using common security technologies (e.g., TLS) - but it has not been designed with the specific goal of achieving high levels of security, and therefore it is vulnerable to more subtle attacks, such as those by privileged users and/or software. In this paper we discuss how the new extension of COTS processors - namely Software Guard eXtension (SGX) - can be exploited to implement effective mechanisms against this specific category of attacks, which is particularly challenging. We present a general approach to harden systems, and discuss in detail how we implemented it in the context of OpenNCP. Also importantly, we evaluate the performance degradation induced by SGX.","PeriodicalId":129399,"journal":{"name":"2018 14th European Dependable Computing Conference (EDCC)","volume":"417 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131527704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}