The University of Southampton
Telephone:
+442380593271
Email:
l.aniello@soton.ac.uk

Dr Leonardo Aniello 

Dr. Leonardo Aniello is a Lecturer at the University of Southampton, where he is also member of the Cyber Security group. He obtained a Ph.D. in Engineering in Computer Science in 2014 from "La Sapienza" University of Rome, with a thesis about techniques for processing Big Data in large-scale collaborative environments, with the aim of improving performance. His research is currently focused on cyber security aspects, including malware analysis, blockchain-based systems, IoT security and privacy-preserving data sharing. Leonardo is author of more than 30 papers about these topics, published on international conferences, workshops, journals and books.

Research

Research interests

Blockchain-based Systems

IoT Security

Malware Analysis

Publications

Gaetani, Edoardo, Aniello, Leonardo, Baldoni, Roberto, Lombardi, Federico, Margheri, Andrea and Sassone, Vladimiro (2017) Blockchain-based database to ensure data integrity in cloud computing environments. Italian Conference on Cybersecurity, Venice, Italy. 17 - 20 Jan 2017. 10 pp .

De Angelis, Stefano, Aniello, Leonardo, Baldoni, Roberto, Lombardi, Federico, Margheri, Andrea and Sassone, Vladimiro (2018) PBFT vs proof-of-authority: applying the CAP theorem to permissioned blockchain. Italian Conference on Cyber Security. 11 pp .

Lombardi, Federico, Aniello, Leonardo, De Angelis, Stefano, Margheri, Andrea and Sassone, Vladimiro (2018) A blockchain-based infrastructure for reliable and cost-effective IoT-aided smart grids. Living in the Internet of Things Conference: Cybersecurity of the IoT - A PETRAS, IoTUK & IET Event, London, United Kingdom. 28 - 29 Mar 2018. 6 pp .

Aniello, Leonardo, Bonomi, Silvia, Lombardi, Federico, Zelli, Alessandro and Baldoni, Roberto (2014) An architecture for automatic scaling of replicated services. In Network Systems NETYS 2014. Springer. 122 pp . (doi:10.1007/978-3-319-09581-3_9).

Heinze, Thomas, Aniello, Leonardo, Querzoni, Leonardo and Jerzak, Zbigniew (2014) Tutorial: cloud-based data stream processing. In DEBS 14 : Proceedings of the 8th ACM International Conference on Distributed Event-based Systems. 8 pp . (In Press)

Lombardi, Federico, Aniello, Leonardo, Bonomi, Silvia and Querzoni, Leonardo (2018) Elastic symbiotic scaling of operators and resources in stream processing systems. IEEE Transactions on Parallel and Distributed Systems, 29 (3), 572-585. (doi:10.1109/TPDS.2017.2762683).

Lodi, Giorgia, Aniello, Leonardo, Di Lunca, Giuseppe Antonio and Baldoni, Roberto (2014) An event-based platform for collaborative threats detection and monitoring. Information Systems, 39, 175-195. (doi:10.1016/j.is.2013.07.005).

Ucci, Daniele, Aniello, Leonardo and Baldoni, Roberto (2019) Survey of machine learning techniques for malware analysis. Computers and Security, 81, 123-147. (doi:10.1016/j.cose.2018.11.001).

Lombardi, Federico, Muti, Andrea, Aniello, Leonardo, Baldoni, Roberto, Bonomi, Silvia and Querzoni, Leonardo (2019) PASCAL: An architecture for proactive auto-scaling of distributed services. Future Generation Computer Systems, 98, 342-361. (doi:10.1016/j.future.2019.03.003).

Fadhel, Nawfal, Lombardi, Federico, Aniello, Leonardo, Margheri, Andrea and Sassone, Vladimiro (2019) Towards a semantic modelling for threat analysis of IoT applications: a case study on transactive energy. In IET Living in the Internet of Things 2019. Institute of Engineering and Technology, IET..

Lombardi, Federico, Baldoni, Roberto and Aniello, Leonardo (2016) A blockchain-based solution for enabling log-based resolution of disputes in multi-party transactions. Ciancarini, P., Litvinov, S., Messina, A., Sillitti, A. and Succi, G. (eds.) In Proceedings of 5th International Conference in Software Engineering for Defence Applications. SEDA 2016. vol. 717, Springer. pp. 53-58 . (doi:10.1007/978-3-319-70578-1_6).

Ciccotelli, Claudio, Aniello, Leonardo, Lombardi, Federico, Montanari, Luca, Querzoni, Leonardo and Baldoni, Roberto (2015) Nirvana: A non-intrusive black-box monitoring framework for rack-level fault detection. In 2015 IEEE 21st Pacific Rim International Symposium on Dependable Computing (PRDC). IEEE.. (doi:10.1109/PRDC.2015.22).

Aniello, Leonardo, Querzoni, Leonardo and Baldoni, Roberto (2015) High frequency batch-oriented computations over large sliding time windows. Future Generation Computer Systems, 43-44, 1-11. (doi:10.1016/j.future.2014.09.008).

Contact

Telephone: 23271

Email: l.aniello

Share this profile FacebookGoogle+TwitterWeibo

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×