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Two projects from CSE on IVA´s list

Two projects from Computer Science and Engineering on IVA's 100 list

​A system for protection against cyber-attacks and a new tool for using and sharing data analytics based on personal data are two of the 100 research projects that the Royal Swedish Academy of Engineering presented today on its 100 list for 2021.
In this year's 100 list, IVA has called for projects focusing on sustainable preparedness for future crises. Behind these two innovations from Computer Science and Engineering are Magnus Almgren together with his doctoral student Wissam Aoudi and Alejandro Russo together with his colleague Marco Gaboardi.

- It is fantastic to be on IVA's 100 list. Cyber security is a major challenge for the connected society. Our research has led to new technology that can, among other things, protect self-driving cars, and we are now looking for more actors who want to initiate a dialogue and contribute to a secure connected society, says Magnus Almgren, associate professor at the Department of Computer Science and Engineering.

The purpose of the 100 list is to shed light on current research and make it easier for researchers and companies to find each other to create innovation and new business opportunities together. The research must be ready to be utilized within the foreseeable future and create value for Swedish business and society.

- My colleague Marco Gaboardi, research assistant at Boston University, and I have developed a 'deep tech' method to offer a tool for creating privacy-preserving analytics. Performing analytics on personal data can bring new value propositions and business opportunities! Still, the challenge is to do it while respecting the privacy of individuals and complying with GDPR . Our research will enable companies' cooperation around data, break data silos, and open data insights that otherwise would have remained closed, says Alejandro Russo, Associate Professor at Computer Science and Engineering.

Read more about the projects:

Protection against cyber attacks - new efficient technology that is suitable for running both locally in cyber-physical systems and in the cloud.

Magnus AlmgrenIn a research effort to protect safety-critical systems on which societies depend in light of the increasing trend of digitalization, Magnus Almgren and Wissam Aoudi have developed algorithms that can detect attacks in real time and which can run both locally and on the cloud. While bringing systems that people interact with on a daily basis online has its benefits, it comes at the risk of exposing such systems as self-driving vehicles, which lack basic security mechanisms, to cyber criminals. Upon successful attacks, cyber criminals are capable of no less than compromising and taking full control of these systems remotely, which can have devastating consequences on society. Magnus and Wissam have relentlessly validated the applicability of their algorithms to connected vehicles, industrial control systems, and various types of IoT systems.​

New tool for privacy-preserving analyzes

Alejandro RussoUsing and sharing data analytics based on personal data can create competitive advantages and lead to new business opportunities for companies and organizations. However, the possibilities are limited due to rules regulating the processing of personal data, such as the GDPR. Alejandro Russo has together with Marco Gaboardi developed a 'deep tech' method to offer a tool, based on Differential Privacy, for creating privacy-preserving analysis.

Companies and authorities collect large amounts of information (data) about individuals, e.g. customers and citizens. However, a large part of the information collected consists of personal data, that is, it contains information about individuals and their private behavior. For many companies, it is a challenge to use and share data analytics based on personal data and at the same time respect the individual's privacy in accordance with the GDPR. The ability to freely use such data analytics would in many cases create competitive advantages and lead to new business opportunities.

Alejandro explains “To protect the privacy of an individual, our approach uses random noise to change the results of analytics. The addition of noise must be done very carefully and, for that, we  use the mathematical method for Differential Privacy, which is a gold standard for data privacy. We have recently founded a company with the goal of helping out Swedish industry and authorities to perform analytics on personal data at the same time that privacy gets respected. We are currently working with GU Ventures to reach out to potential interested stakeholders. ”

Read more about the project at www.dpella.io​

Page manager Published: Fri 14 May 2021.