Space Station communications and tracking systems modeling and RF link simulation

In this final report, the effort spent on Space Station Communications and Tracking System Modeling and RF Link Simulation is described in detail. The effort is mainly divided into three parts: frequency division multiple access (FDMA) system simulation modeling and software implementation; a study on design and evaluation of a functional computerized RF link simulation/analysis system for Space Station; and a study on design and evaluation of simulation system architecture. This report documents the results of these studies. In addition, a separate User's Manual on Space Communications Simulation System (SCSS) (Version 1) documents the software developed for the Space Station FDMA communications system simulation. The final report, SCSS user's manual, and the software located in the NASA JSC system analysis division's VAX 750 computer together serve as the deliverables from LinCom for this project effort

Software for malicious macro detection

The objective of this work is to give a detailed study of the development process of a software tool for the detection of the Emotet virus in Microsoft Office files, Emotet is a virus that has been wreaking havoc mainly in the business environment, from its beginnings as a banking Trojan to nowadays. In fact, this polymorphic family has managed to generate evident, incalculable and global inconveniences in the business activity without discriminating by corporate typology, affecting any company regardless of its size or sector, even entering into government agencies, as well as the citizens themselves as a whole. The existence of two main obstacles for the detection of this virus, constitute an intrinsic reality to it, on the one hand, the obfuscation in its macros and on the other, its polymorphism, are essential pieces of the analysis, focusing our tool in facing precisely two obstacles, descending to the analysis of the macros features and the creation of a neuron network that uses machine learning to recognize the detection patterns and deliberate its malicious nature. With Emotet's in-depth nature analysis, our goal is to draw out a set of features from the malicious macros and build a machine learning model for their detection. After the feasibility study of this project, its design and implementation, the results that emerge endorse the intention to detect Emotet starting only from the static analysis and with the application of machine learning techniques. The detection ratios shown by the tests performed on the final model, present a accuracy of 84% and only 3% of false positives during this detection process.Grado en Ingeniería Informátic

E‐ARK Dissemination Information Package (DIP) Final Specification

The primary aim of this report is to present the final version of the E-ARK Dissemination Information Package (DIP) formats. The secondary aim is to describe the access scenarios in which these DIP formats will be rendered for use

Analysis of systems hardware flown on LDEF. Results of the systems special investigation group

The Long Duration Exposure Facility (LDEF) was retrieved after spending 69 months in low Earth orbit (LEO). LDEF carried a remarkable variety of mechanical, electrical, thermal, and optical systems, subsystems, and components. The Systems Special Investigation Group (Systems SIG) was formed to investigate the effects of the long duration exposure to LEO on systems related hardware and to coordinate and collate all systems analysis of LDEF hardware. Discussed here is the status of the LDEF Systems SIG investigation through the end of 1991