Autonomous Pervasive Systems and the Policy Challenges of a Small World
Keynote IEEE Symposium on Policies for Distributed Systems and Networks 2007. Slides available from:
Detecting Malicious Data Injections in Wireless Sensor Networks: a Survey
Wireless Sensor Networks are widely advocated to monitor environmental parameters, structural integrity of the built environment and use of urban spaces, services and utilities. However, embedded sensors are vulnerable to compromise by external actors through malware but also through their wireless and physical interfaces. Compromised sensors can be made to report false measurements with the aim to produce inap- propriate and potentially dangerous responses. Such malicious data injections can be particularly difficult to detect if multiple sensors have been compromised as they could emulate plausible sensor behaviour such as failures or detection of events where none occur. This survey reviews the related work on malicious data injection in wireless sensor networks, derives general principles and a classification of approaches within this domain, compares related studies and identifies areas that require further investigation.
Vittorio P. Illiano and Emil C. Lupu: Detecting Malicious Data Injections in Wireless Sensor Networks: a Survey Published in ACM Computing Surveys Vol. 48, No. 2, Article 24, Publication date: October 2015
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Andrea Paudice
Andrea joined us from the University of Naples as a first year PhD student on the HiPEDS CDT.
Erisa Karafili
Erisa joined us after a PhD at the University of Verona and a Post-Doc at the Technical University of Denmark. She worked on Data Sharing Agreements and Argumentation and Logic Programming techniques applied to Security.
Detecting Malicious Data Injections In Event Detection Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are vulnerable and can be maliciously compromised, either physically or remotely, with potentially devastating effects. When sensor networks are used to detect the occurrence of events such as fires, intruders or heart-attacks, malicious data can be injected to create fake events and, thus, trigger an undesired response, or to mask the occurrence of actual events. We propose a novel algorithm to identify malicious data injections and build measurement estimates that are resistant to several compromised sensors even when they collude in the attack. We also propose a methodology to apply this algorithm in different application contexts and evaluate its results on three different datasets drawn from distinct WSN deployments. This leads us to identify different trade-offs in the design of such algorithms and how they are influenced by the application context.
Vittorio P. Illiano and Emil C. Lupu: Detecting Malicious Data Injections In Event Detection Wireless Sensor Networks. To appear in IEEE Transactions on Network and Service Management
IEEE publication link
Open access link
Rodrigo Vieira Steiner
Rodrigo was a PhD student in the RISS group working on attestation techniques for sensor networks. He currently works in Brazil.
Sharing Data Through Confidential Clouds: An Architectural Perspective
Cloud and mobile are two major computing paradigms that are rapidly converging. However, these models still lack a way to manage the dissemination and control of personal and business-related data. To this end, we propose a framework to control the sharing, dissemination and usage of data based on mutually agreed Data Sharing Agreements (DSAs). These agreements are enforced uniformly, and end-to-end, both on Cloud and mobile platforms, and may reflect legal, contractual or user-defined preferences. We introduce an abstraction layer that makes available the enforcement functionality across different types of nodes whilst hiding the distribution of components and platform specifics. We also discuss a set of different types of nodes that may run such a layer.
Daniele Sgandurra, Francesco Di Cerbo, Slim Trabelsi, Fabio Martinelli, and Emil Lupu: Sharing Data Through Confidential Clouds: An Architectural Perspective. In proceedings of the 1st International Workshop on TEchnical and LEgal aspects of data pRivacy and SEcurity, 2015 IEEE/ACM, pp. 58-61, DOI: 10.1109/TELERISE.2015.19. Bibtex.
PhD Students
We are always looking for outstanding PhD students passionate about computer security and resilience for enterprise systems, large-scale infrastructures, or cyber-physical environments. The Department of Computing at Imperial College has a number of PhD studentships. Please check that your application meets the minimum entry requirements specified by the College before applying. Please don’t hesitate to contact (Professor Emil Lupu) if you would like to work with our group and include in your email a CV, transcripts, and examples of work that you have done e.g. papers or MSc/Bc thesis even if in draft form.
Topics of interest include:
- The resilience of Cyber-Physical Systems
- Robust information fusion
- Topics at the intersection of security and safety.
- The security of AR/VR environments.
- Designing security in very resource constrained environments e.g. implantable medical sensors.
- Adversarial Machine Learning with focus on: practical problems, toolchains for robustness, attack detection.
Compositional Reliability Analysis for Probabilistic Component Automata
In this paper we propose a modelling formalism, Probabilistic Component Automata (PCA), as a probabilistic extension to Interface Automata to represent the probabilistic behaviour of component-based systems. The aim is to support composition of component-based models for both behaviour and non-functional properties such as reliability. We show how addi- tional primitives for modelling failure scenarios, failure handling and failure propagation, as well as other algebraic operators, can be combined with models of the system architecture to automatically construct a system model by composing models of its subcomponents. The approach is supported by the tool LTSA-PCA, an extension of LTSA, which generates a composite DTMC model. The reliability of a particular system configuration can then be automatically analysed based on the corresponding composite model using the PRISM model checker. This approach facilitates configurability and adaptation in which the software configuration of components and the associated composition of component models are changed at run time.
P. Rodrigues, E. Lupu and J. Kramer, Compositional Reliability Analysis for Probabilistic Component Automata, to appear in International Workshop on Modelling in Software Engineering (MiSE), Florence, May 16-17, 2015.
On Re-Assembling Self-Managed Components
Self-managed systems need to adapt to changes in requirements and in operational conditions. New components or services may become available, others may become unreliable or fail. Non-functional aspects, such as reliability or other quality-of- service parameters usually drive the selection of new architectural configurations. However, in existing approaches, the link between non-functional aspects and software models is established through manual annotations that require human intervention on each re-configuration and adaptation is enacted through fixed rules that require anticipation of all possible changes. We propose here a methodology to automatically re-assemble services and component-based applications to preserve their reliability. To achieve this we define architectural and behavioural models that are composable, account for non-functional aspects and correspond closely to the implementation. Our approach enables autonomous components to locally adapt and control their inter- nal configuration whilst exposing interface models to upstream components.
P. Rodrigues, J. Kramer and E. Lupu, On Re-Assembling Self-Managed Components, to appear in International Symposium on Integrated Network and Service Management (IM), Ottawa, May 11-15, 2015
Hybrid Human and Machine Learning
A short video clip discussing how humans and machines can learn from each other in a continuous feedback system.
Martín Barrère
Martín has recently joined the group after receiving a PhD degree in Computer Science from the University of Lorraine, France, in 2014. His current research work focuses on intelligent protection mechanisms for cloud environments at run-time. His topics of interest include computer security, autonomic computing, vulnerability management, mobile and cloud computing, distributed computing, digital evidence and forensics, formal models and languages, Linux-based systems and TCP/IP networks administration, Java technologies, logic and database systems.
Luis Muñoz González
Luis is a Research Associate in the Department of Computing at Imperial College London. He received his PhD from University Carlos III of Madrid (Spain) where he proposed novel Gaussian process models for non-stationary and heteroscedastic regression. His background includes machine learning and cyber-security. His current research interests are adversarial machine learning and security risk assessment with attack graph models. You can find more details about his current research activities and contact information at his personal web page, Google Scholar profile or Researchgate.
Federico Morini
Federico received his MSc in Engineering in Computer Science from University of Ferrara. He joined the group in 2014 and is working towards a PHD. He is interested in Protocol Modelling, in particular applied to SCADA Networks. His work is focused on listening to the communication between two hosts and trying to extract information on the message format and state machine of the protocol.
Federating Policy-Driven Autonomous Systems: Interaction Specification and Management Patterns
Ubiquitous systems and applications involve interactions between multiple autonomous entities—for example, robots in a mobile ad-hoc network collaborating to achieve a goal, communications between teams of emergency workers involved in disaster relief operations or interactions between patients’ and healthcare workers’ mobile devices. We have previously proposed the Self-Managed Cell (SMC) as an architectural pattern for managing autonomous ubiquitous systems that comprise both hardware and software components and that implement policy-based adaptation strategies. We have also shown how basic management interactions between autonomous SMCs can be realised through exchanges of notifications and policies, to effectively program management and context-aware adaptations. We present here how autonomous SMCs can be composed and federated into complex structures through the systematic composition of interaction patterns. By composing simpler abstractions as building blocks of more complex interactions it is possible to leverage commonalities across the structural, control and communication views to manage a broad variety of composite autonomous systems including peer-to-peer collaborations, federations and aggregations with varying degrees of devolution of control. Although the approach is more broadly applicable, we focus on systems where declarative policies are used to specify adaptation and on context-aware ubiquitous systems that present some degree of autonomy in the physical world, such as body sensor networks and autonomous vehicles. Finally, we present a formalisation of our model that allows a rigorous verification of the properties satisfied by the SMC interactions before policies are deployed in physical devices.
Schaeffer-Filho, Alberto and Lupu, Emil and Sloman, Morris. Federating Policy-Driven Autonomous Systems: Interaction Specification and Management Patterns, Journal of Network and Systems Management, Springer, http://dx.doi.org/10.1007/s10922-014-9317-5
Vittorio Illiano
Vittorio Illiano is PhD student in the Department of Computing at Imperial College London, as part of the Intel ICRI on Sustainable and Connected Cities.
His main research area is security in Wireless Sensor Networks, with a focus on anomaly detection and related data analysis techniques.
He received the B.Sc. and M.Sc. in Computer Engineering from the University of Naples “Federico II”.
Vittorio left the group after completing and defending successfully his PhD Thesis. He is now working with Novartis.
CIPART: Cloud Intelligent Protection at Run-Time
Organisations, small and large, increasingly rely upon cloud environments to supply their ICT needs because clouds provide a better incremental cost structure, resource elasticity and simpler management. This trend is set to continue as increasingly information collected from mobile devices and smart environments including homes, infrastructures and smart-cities is uploaded and processed in cloud environments. Services delivered to users are also deployed in the cloud as this provides better scaleability and in some cases permits migration closer to the point of access for reduced latency.
Clouds are therefore an attractive target for organised and skilled cyber-attacks. They are also more vulnerable as they host environments from multiple tenant organisations with different interests and different risk aversion profiles. Yet clouds also offer opportunities for better protection both pro-actively and reactively in response to a persistent attack.
…Pedro Rodrigues
Pedro has obtained his PhD in the RISS group working on composable techniques for reliability analysis.