performance and security
Towards Automated Homomorphic Encryption Parameter Selection with Fuzzy Logic and Linear Programming
Cabrero-Holgueras, José, Pastrana, Sergio
Homomorphic Encryption (HE) is a set of powerful properties of certain cryptosystems that allow for privacy-preserving operation over the encrypted text. Still, HE is not widespread due to limitations in terms of efficiency and usability. Among the challenges of HE, scheme parametrization (i.e., the selection of appropriate parameters within the algorithms) is a relevant multi-faced problem. First, the parametrization needs to comply with a set of properties to guarantee the security of the underlying scheme. Second, parametrization requires a deep understanding of the low-level primitives since the parameters have a confronting impact on the precision, performance, and security of the scheme. Finally, the circuit to be executed influences, and it is influenced by, the parametrization. Thus, there is no general optimal selection of parameters, and this selection depends on the circuit and the scenario of the application. Currently, most of the existing HE frameworks require cryptographers to address these considerations manually. It requires a minimum of expertise acquired through a steep learning curve. In this paper, we propose a unified solution for the aforementioned challenges. Concretely, we present an expert system combining Fuzzy Logic and Linear Programming. The Fuzzy Logic Modules receive a user selection of high-level priorities for the security, efficiency, and performance of the cryptosystem. Based on these preferences, the expert system generates a Linear Programming Model that obtains optimal combinations of parameters by considering those priorities while preserving a minimum level of security for the cryptosystem. We conduct an extended evaluation where we show that an expert system generates optimal parameter selections that maintain user preferences without undergoing the inherent complexity of analyzing the circuit.
FastCycle: A Message Sharing Framework for Modular Automated Driving Systems
Testouri, Mehdi, Elghazaly, Gamal, Frank, Raphael
Automated Driving Systems (ADS) have rapidly evolved in recent years and their architecture becomes sophisticated. Ensuring robustness, reliability and safety of performance is particularly important. The main challenge in building an ADS is the ability to meet certain stringent performance requirements in terms of both making safe operational decisions and finishing processing in real-time. Middlewares play a crucial role to handle these requirements in ADS. The way middlewares share data between the different system components has a direct impact on the overall performance, particularly the latency overhead. To this end, this paper presents FastCycle as a lightweight multi-threaded zero-copy messaging broker to meet the requirements of a high fidelity ADS in terms of modularity, real-time performance and security. We discuss the architecture and the main features of the proposed framework. Evaluation of the proposed framework based on standard metrics in comparison with popular middlewares used in robotics and automated driving shows the improved performance of our framework. The implementation of FastCycle and the associated comparisons with other frameworks are open sourced.
Bracing For IoT In The Enterprise
If you thought the bring-your-own-device (BYOD) experience was a challenge for companies, brace yourself. The mid-2000s brought waves of heterogeneous, non-sanctioned devices into the network. By 2009, workers had made it clear that they preferred BYOD, as CIOs began feeling the pressure of personal devices flooding the workplace. The result has been the creation of so-called "shadow IT" -- projects (applications and systems) managed outside of, and without the knowledge of, the IT department. The BYOD phenomenon went hand in hand with the adoption of non-sanctioned, cloud-based software as a service (SaaS) applications to address a line of business needs.
Cloud data and AI services training roundup
To help you stay up to date on online training opportunities, we're releasing a monthly list of the latest free data and artificial intelligence (AI) sessions in one convenient post. Whether on Windows, Linux, or Docker containers, you have the flexibility of leveraging SQL Server 2017's industry-leading performance and security wherever you like. Here's a rundown of recent and upcoming training sessions to help you learn more. Extended support for SQL Server 2008 and 2008 R2 is coming to an end on July 9, 2019, which means it's time to choose your path to modernization. Without support, security updates will no longer be available, and you may run the risk of non-compliance with industry regulations such as GDPR (General Data Protection Regulation).