COVID-19 has prompted a rise in telecommuting practices in most companies worldwide. Meanwhile, companies are struggling to cope with the new and evolving security threats in telecommuting using old control methods. Specifically, there is an increased danger of hacking attacks in telecommuting environments. Furthermore, corporate concerns regarding telecommuting security have led to a questioning of existing control methods that no longer seem adequate. Significant research has been conducted on the factors that improve the effectiveness of corporate security policies, such as formal control, informal control, and extrarole behaviors. However, these studies did not consider telecommuting environments, which surged after the COVID-19 outbreak. Telecommuting loosens the physical control over employees and eliminates the collegial environment in which employees encourage each other to protect system information. This study determined how the factors that influence the effectiveness of existing information security policies behave in a telecommuting environment. Our study shows that specification and mandatoriness are the most important factors for an effective telecommuting security policy. We conclude that this sudden change in the working environment has rendered existing security controls obsolete, and specification and mandatoriness are likely to receive increasingly more attention in the growing field of telecommuting security policy.

One of the core principles of the SAP HANA database system is the comprehensive support of distributed query facility. Supporting scale-out scenarios was one of the major design principles of the system from the very beginning. Within this paper, we first give an overview of the overall functionality with respect to data allocation, metadata caching and query routing. We then dive into some level of detail for specific topics and explain features and methods not common in traditional disk-based database systems. In summary, the paper provides a comprehensive overview of distributed query processing in SAP HANA database to achieve scalability to handle large databases and heterogeneous types of workloads.

MaxStream is a federated stream processing system that seamlessly integrates multiple autonomous and heterogeneous Stream Processing Engines (SPEs) and databases. In this paper, we propose to demonstrate the key features of MaxStream using two application scenarios, namely the Sales Map & Spikes business monitoring scenario and the Linear Road Benchmark, each with a different set of requirements. More specifically, we will show how the MaxStream Federator can translate and forward the application queries to two different commercial SPEs (Coral8 and StreamBase), as well as how it does so under various persistency requirements.