@article{SiddiqiDoerrStrydis2020,
  author    = {Siddiqi, Muhammad Ali and D{\"o}rr, Christian and Strydis, Christos},
  title     = {IMDfence},
  series = {IEEE access},
  volume    = {8},
  journal   = {IEEE access},
  publisher = {Institute of Electrical and Electronics Engineers},
  address   = {Piscataway},
  issn      = {2169-3536},
  doi       = {10.1109/ACCESS.2020.3015686},
  pages     = {147948 -- 147964},
  year      = {2020},
  abstract  = {Over the past decade, focus on the security and privacy aspects of implantable medical devices (IMDs) has intensified, driven by the multitude of cybersecurity vulnerabilities found in various existing devices. However, due to their strict computational, energy and physical constraints, conventional security protocols are not directly applicable to IMDs. Custom-tailored schemes have been proposed instead which, however, fail to cover the full spectrum of security features that modern IMDs and their ecosystems so critically require. In this paper we propose IMDfence, a security protocol for IMD ecosystems that provides a comprehensive yet practical security portfolio, which includes availability, non-repudiation, access control, entity authentication, remote monitoring and system scalability. The protocol also allows emergency access that results in the graceful degradation of offered services without compromising security and patient safety. The performance of the security protocol as well as its feasibility and impact on modern IMDs are extensively analyzed and evaluated. We find that IMDfence achieves the above security requirements at a mere less than 7\% increase in total IMD energy consumption, and less than 14 ms and 9 kB increase in system delay and memory footprint, respectively.},
  language  = {en}
}
@article{GhahremaniGieseVogel2020,
  author    = {Ghahremani, Sona and Giese, Holger and Vogel, Thomas},
  title     = {Improving scalability and reward of utility-driven self-healing for large dynamic architectures},
  series = {ACM transactions on autonomous and adaptive systems},
  volume    = {14},
  journal   = {ACM transactions on autonomous and adaptive systems},
  number    = {3},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  issn      = {1556-4665},
  doi       = {10.1145/3380965},
  pages     = {41},
  year      = {2020},
  abstract  = {Self-adaptation can be realized in various ways. Rule-based approaches prescribe the adaptation to be executed if the system or environment satisfies certain conditions. They result in scalable solutions but often with merely satisfying adaptation decisions. In contrast, utility-driven approaches determine optimal decisions by using an often costly optimization, which typically does not scale for large problems. We propose a rule-based and utility-driven adaptation scheme that achieves the benefits of both directions such that the adaptation decisions are optimal, whereas the computation scales by avoiding an expensive optimization. We use this adaptation scheme for architecture-based self-healing of large software systems. For this purpose, we define the utility for large dynamic architectures of such systems based on patterns that define issues the self-healing must address. Moreover, we use pattern-based adaptation rules to resolve these issues. Using a pattern-based scheme to define the utility and adaptation rules allows us to compute the impact of each rule application on the overall utility and to realize an incremental and efficient utility-driven self-healing. In addition to formally analyzing the computational effort and optimality of the proposed scheme, we thoroughly demonstrate its scalability and optimality in terms of reward in comparative experiments with a static rule-based approach as a baseline and a utility-driven approach using a constraint solver. These experiments are based on different failure profiles derived from real-world failure logs. We also investigate the impact of different failure profile characteristics on the scalability and reward to evaluate the robustness of the different approaches.},
  language  = {en}
}