Genomic data leaks are irreversible. Leaked DNA cannot be changed, stays disclosed indefinitely, and affects the owner's family members as well. The recent large-scale genomic data collections [1], [2] render the traditional privacy protection mechanisms, like the Health Insurance Portability and Accountability Act (HIPAA), inadequate for protection against the novel security attacks [3]. On the other hand, data access restrictions hinder important clinical research that requires large datasets to operate [4]. These concerns can be naturally addressed by the employment of privacy-enhancing technologies, such as a secure multiparty computation (MPC) [5]–[10]. Secure MPC enables computation on data without disclosing the data itself by dividing the data and computation between multiple computing parties in a distributed manner to prevent individual computing parties from accessing raw data. MPC systems are being increasingly adopted in fields that operate on sensitive datasets [11]–[13], such as computational genomics and biomedical research [14]–[22].

All processes in the production and distribution of material goods, which include material and interactive information flows, are united by the term “Logistics” and are realized within the logistics processes. Logistics processes hide large technological and economic reserves that need to be identified, located and used. At the EU level, a new philosophy of realization of quality logistics processes has been created in the past decades, and it is increasingly including the environmental aspect by introducing the term Green Logistics, which highlights the demand for a healthy environment. The level of logistics process technology is still far below the level of development of material production technology, which is the main reason for giving strategic importance to the rationalization and optimization of logistics processes at the global level in order at reducing the costs of all participants in the implementation of the process, and especially in the direction of raising the quality of services and meeting the increasingly stringent requirements of service users.

The fourth industrial revolution (Industry 4.0) anticipates frequent synthesis and optimization of different architectural design decisions (ADDs) – such as deployment of software components to hardware components, service composition, production planning, and topology (plant layout) synthesis. The frequent manual search for valid and optimal architectural designs is a time- and cognition-consuming task for an engineer. This asks for automating the process of deriving different ADDs. Although automating different ADDs is intensely investigated in other domains, the current research works 1) require higher engineering effort for specifying architecture optimization problems; 2) conduct (only) sequential ADDs, leading to lower solution quality (i.e., sub-optimal production); 3) neglect re-configurability and reliability of architectures, and, thereby, offer no solution for production downtime; 4) neglect event-based execution semantics while considering timing-related issues. Therefore, I propose a Satisfiability Modulo Theories (SMT)-based framework for joint synthesis and optimization of multi-dimensional ADDs using industrial automation domain models (e.g., plant topology, product recipes, stations capabilities, etc.). This research should bring following benefits for the practitioners and researchers: 1) reduction of engineering effort for conducting different ADDs; 2) improvement of different quality attributes (e.g., production performance, reconfigurability, reliability, etc.); 3) guideline/support for a practitioner in choosing ADDs workflow to improve given quality attributes.

Self-adaptive systems offer several attack surfaces due to the communication via different channels and the different sensors required to observe the environment. Often, attacks cause safety to be compromised as well, making it necessary to consider these two aspects together. Furthermore, the approaches currently used for safety and security analysis do not sufficient take into account the intermediate steps of an adaptation. Current work in this area ignores the fact that a self-adaptive system also reveals possible vulnerabilities (even if only temporarily) during the adaptation. To address this issue, we propose a modeling approach that takes into account the different relevant aspects of a system, its adaptation process, as well as safety hazards and security attacks. We present several models that describe different aspects of a self-adaptive system and we outline our idea of how these models can then be combined into an Attack-Fault Tree. This allows modeling aspects of the system on different levels of abstraction and co-evolve the models using transformations according to the adaptation of the system. Finally, analyses can then be performed as usual on the resulting Attack-Fault Tree.CCS CONCEPTS• Software and its engineering → System description languages; Fault tree analysis; • Computer systems organization → Embedded and cyber-physical systems; Dependable and fault-tolerant systems and networks.