Random path sampling applied to vector models of magnetism

The recently reported Monte Carlo Random Path Sampling method (RPS) is here improved and its application is expanded to the study of the 2D and 3D Ising and discrete Heisenberg models. The methodology was implemented to allow use in both CPU-based high-performance computing infrastructures (C/MPI) and GPU-based (CUDA) parallel computation, with significant computational performance gains. Convergence is discussed, both in terms of free energy and magnetization dependence on field/temperature. From the calculated magnetization-energy joint density of states, fast calculations of field and temperature dependent thermodynamic properties are performed, including the effects of anisotropy on coercivity, and the magnetocaloric effect. The emergence of first-order magneto-volume transitions in the compressible Ising model is interpreted using the Landau theory of phase transitions. Using metallic Gadolinium as a real-world example, the possibility of using RPS as a tool for computational magnetic materials design is discussed. Experimental magnetic and structural properties of a Gadolinium single crystal are compared to RPS-based calculations using microscopic parameters obtained from Density Functional Theory.

Protecting databases from schema disclosure: a CRUD-based protection model

Database schemas, in many organizations, are considered one of the critical assets to be protected. From database schemas, it is not only possible to infer the information being collected but also the way organizations manage their businesses and/or activities. One of the ways to disclose database schemas is through the Create, Read, Update and Delete (CRUD) expressions. In fact, their use can follow strict security rules or be unregulated by malicious users. In the first case, users are required to master database schemas. This can be critical when applications that access the database directly, which we call database interface applications (DIA), are developed by third party organizations via outsourcing. In the second case, users can disclose partially or totally database schemas following malicious algorithms based on CRUD expressions. To overcome this vulnerability, we propose a new technique where CRUD expressions cannot be directly manipulated by DIAs any more. Whenever a DIA starts-up, the associated database server generates a random codified token for each CRUD expression and sends it to the DIA that the database servers can use to execute the correspondent CRUD expression. In order to validate our proposal, we present a conceptual architectural model and a proof of concept.