Cloud, Networking and Security

The Cloud, Network and Security (CNS) team is BTH’s Center-of -Excellence (CoE) for researching and teaching novel methods and techniques for a secure and efficient design, implementation and operation of next generation Cloud systems, Next Generation Internet (NGI) systems and applications, and networks (including the Future Internet, FI). Hereby, the CNS cluster focuses on:

Functionalities and infrastructures for future network, the NGI and Cloud computing, such as virtualisation, autonomic operation, self-protection, Software-Defined Networking (SDN), Network Function Virtualisation (NFV), and Internet-of- Things (IoT).

An Internet for the People and its applications, which fulfil user and societal requirements such as reliability, safety, security and privacy, including EU’s GDPR.

Machine learning techniques and Anomaly Detection for Security, i.e. finding patterns in data that do not conform to an established “normal” behaviour. are used to analyse irregularities in large sets of data.

The CNS team applies a wide range of methods, comprising techniques for distributed systems, Clouds and networks, distributed algorithms and protocols, software engineering, performance evaluation, Big Data analysis, social network analysis, computer system forensics, malware analysis, and penetration testing.

The team is constantly growing. It comprises two full professors, one associated professor, four assistant professors, two university adjuncts, and four Ph.D. students. The CNS team hosts currently four larger and funded research and teaching  projects in security and privacy.

• Emiliano Casalicchio: A Study on Performance Measures for Auto-scaling CPU-intensive Containerized Applications, Cluster Computing, Springer, 2018, TO APPEAR.
• V. Ahmadi Mehri, D. Ilie, and K. Tutschku: Privacy and DRM Requirements for Collaborative Development of AI Applications. Proceedings of the 13th International Conference on Availability, Reliability and Security. ACM, 2018.
• T. Llewellyn, et al.: BONSEYES: Platform for Open Development of Systems of Artificial Intelligence
• V. Ahmadi Mehri, K. Tutschku: Privacy and trust in cloud-based marketplaces for AI and data resources, IFIP Advances in Information and Communication Technology, Springer New York LLC, 2017
• M. Boldt, A. Jacobsson, D. Baca and B. Carlsson, ”Introducing a novel security-enhanced agile software development process”,  in International Journal of Secure Software Engineering, to appear, volume 8, issue 2, 2017.
• A. Jacobsson, M. Boldt and B. Carlsson, ”A risk analysis of a smart home automation systems”, in Future Generation Computer Systems 56 (2016): 719-733.

• Remote Security Lab (ReSeLa)
  • Key features
    • Open virtual testbed for research and teaching security method
    • Permit concurrent security experiments in slices
    • Based on OpenStack
  • Usage:
    • Cybersecurity education in Sweden, Poland, Russia and Ukrain
    • Part of Testbed Blekinge

• Network Performance Lab
  • Key features
    • Open platform for precise network performance management
    • Test area for next generation software defined infrastructure
    • Emulation of user devices (desktop, laptop, smartphones) and  different network/system conditions
  • Usage:
    • Developed within and contributed to over five EU and national research projects
    • Supported of three Phd thesis and more than 30 MSc thesis