Author Archives: eclupu

Dr. Emil Lupu is a Reader in Adaptive Computing Systems in the Department of Computing at Imperial College London and an Associate Director with the Institute for Security Science and Technology, where he leads the Academic Centre of Excellence in Cyber Security Research. Dr Lupu also leads the Policy-Based Autonomous Systems Research group as well as several research projects in the areas of pervasive computing, trust and security and policy-based network and systems management. He has numerous publications in these areas, serves on the editorial boards of the IEEE Transactions on Network and Service Management, Journal of Network and Systems Management and the International Journal of Network Management, and on the program committee of several conferences. Dr Lupu obtained his PhD from Imperial College London under the the supervision of Prof Morris Sloman and his first degree from the ENSIMAG (Ecole Nationale Superieure d’Informatique and Mathematiques Appliquees de Grenoble). Lists of my publications can be found on Google Scholar and DBLP amongst others.

Ensuring the resilience of WSN to Malicious Data Injections through Measurements Inspection

Malicious data injections pose a severe threat to the systems based on Wireless Sensor Networks (WSNs) since they give the attacker control over the measurements, and on the system’s status and response in turn. Malicious measurements are particularly threatening when used to spoof or mask events of interest, thus eliciting or preventing desirable responses. Spoofing and masking attacks are particularly difficult to detect since they depict plausible behaviours, especially if multiple sensors have been compromised and collude to inject a coherent set of malicious measurements. Previous work has tackled the problem through measurements inspection, which analyses the inter-measurements correlations induced by the physical phenomena. However, these techniques consider simplistic attacks and are not robust to collusion. Moreover, they assume highly predictable patterns in the measurements distribution, which are invalidated by the unpredictability of events. We design a set of techniques that effectively detect malicious data injections in the presence of sophisticated collusion strategies, when one or more events manifest. Moreover, we build a methodology to characterise the likely compromised sensors. We also design diagnosis criteria that allow us to distinguish anomalies arising from malicious interference and faults. In contrast with previous work, we test the robustness of our methodology with automated and sophisticated attacks, where the attacker aims to evade detection. We conclude that our approach outperforms state-of-the-a
rt approaches. Moreover, we estimate quantitatively the WSN degree of resilience and provide a methodology to give a WSN owner an assured degree of resilience by automatically designing the WSN deployment. To deal also with the extreme scenario where the attacker has compromised most of the WSN, we propose a combination with software attestation techniques, which are more reliable when malicious data is originated by a compromised software, but also more expensive, and achieve an excellent trade-off between cost and resilience.


Download Thesis from here. 

Determining Resilience Gains From Anomaly Detection for Event Integrity in Wireless Sensor Networks

Vittorio P. Illiano, Andrea Paudice, Luis Muñoz-González, and Emil C. Lupu. 2018. Determining Resilience Gains From Anomaly Detection for Event Integrity in Wireless Sensor Networks. ACM Trans. Sen. Netw. 14, 1, Article 5 (February 2018), 35 pages. DOI:

Abstract: Measurements collected in a wireless sensor network (WSN) can be maliciously compromised through several attacks, but anomaly detection algorithms may provide resilience by detecting inconsistencies in the data. Anomaly detection can identify severe threats to WSN applications, provided that there is a sufficient amount of genuine information. This article presents a novel method to calculate an assurance measure for the network by estimating the maximum number of malicious measurements that can be tolerated. In previous work, the resilience of anomaly detection to malicious measurements has been tested only against arbitrary attacks, which are not necessarily sophisticated. The novel method presented here is based on an optimization algorithm, which maximizes the attack’s chance of staying undetected while causing damage to the application, thus seeking the worst-case scenario for the anomaly detection algorithm. The algorithm is tested on a wildfire monitoring WSN to estimate the benefits of anomaly detection on the system’s resilience. The algorithm also returns the measurements that the attacker needs to synthesize, which are studied to highlight the weak spots of anomaly detection. Finally, this article presents a novel methodology that takes in input the degree of resilience required and automatically designs the deployment that satisfies such a requirement.

Jukka Soikkeli

Jukka joined the group as a PhD student on the HiPEDS CDT.
His current research interests are improving the resilience of partially compromised networks, and network forensics.
Jukka holds an MSc in Computing Science from Imperial College London, and degrees in economics from the University of Oxford and the University of St Andrews.

Hassan Chizari

Dr. Hassan Chizari has joined the RISS Group in February 2017, coming from Universiti Teknologi Malaysia (UTM). Hassan is a Post Doctorate Research Associate (PDRA) in Imperial College London. He did his bachelor and master degree in Shiraz University (IRAN) on ‘Computer Hardware’ and ‘Artificial Intelligence and Robotics’ respectively. He was a PhD candidate in UTM studying on Wireless Sensor Networks and he was awarded the PhD on Computer Networks. He worked in Imam Khomeini International University (IKIU) and Universiti Teknologi Malaysia (UTM) as a Lecturer and a Senior Lecturer for about 9 years. His main research interest is Wireless Sensor Network both in hardware and software perspectives and mainly in cyber-security area.


Google scholar profile is here.

Research Gate link is here.

ORCiD link is here.

Attestation in Wireless Sensor Networks: A Survey

Attestation is a mechanism used by a trusted entity to validate the software integrity of an untrusted platform. Over the past few years, several attestation techniques have been proposed. While they all use variants of a challenge-response protocol, they make different assumptions about what an attacker can and cannot do. …

PETRAS Hub for the IoT

PETRAS_logo_black smallWe are thrilled to be part of the PETRAS IoT Hub which aims to ensure that the UK remains a global leader in the Internet of Things. PETRAS (Privacy, Ethics, Trust, Reliability, Acceptability and Security) groups together 9 leading UK universities and has more than 47 user partners from industry and the public sector. The consortium has received a £9.8M grant from the EPSRC. Dr Emil Lupu is to serve as Deputy Director of the Hub and lead for the Security and Safety Theme.

Konstantina Spanaki

Konstantina joined Imperial College Business School as a Research Associate in 2014. Her main research interests focus on topics of IT adoption, business integration and information management. She worked on joint projects between this group and the Business School in particular on value aspects of data and adoption of cloud security services. Konstantina is now a Lecturer at School of Business and Economics, Loughborough University.