Workshop proceedings: Information Systems for Space Astrophysics in the 21st Century, volume 1

The Astrophysical Information Systems Workshop was one of the three Integrated Technology Planning workshops. Its objectives were to develop an understanding of future mission requirements for information systems, the potential role of technology in meeting these requirements, and the areas in which NASA investment might have the greatest impact. Workshop participants were briefed on the astrophysical mission set with an emphasis on those missions that drive information systems technology, the existing NASA space-science operations infrastructure, and the ongoing and planned NASA information systems technology programs. Program plans and recommendations were prepared in five technical areas: Mission Planning and Operations; Space-Borne Data Processing; Space-to-Earth Communications; Science Data Systems; and Data Analysis, Integration, and Visualization

Content warehouses

Nowadays, content management systems are an established technology. Based on the experiences from several application scenarios we discuss the points of contact between content management systems and other disciplines of information systems engineering like data warehouses, data mining, and data integration. We derive a system architecture called "content warehouse" that integrates these technologies and defines a more general and more sophisticated view on content management. As an example, a system for the collection, maintenance, and evaluation of biological content like survey data or multimedia resources is shown as a case study

Primary User Emulation Detection in Cognitive Radio Networks

Cognitive radios (CRs) have been proposed as a promising solution for improving spectrum utilization via opportunistic spectrum sharing. In a CR network environment, primary (licensed) users have priority over secondary (unlicensed) users when accessing the wireless channel. Thus, if a malicious secondary user exploits this spectrum access etiquette by mimicking the spectral characteristics of a primary user, it can gain priority access to a wireless channel over other secondary users. This scenario is referred to in the literature as primary user emulation (PUE). This dissertation first covers three approaches for detecting primary user emulation attacks in cognitive radio networks, which can be classified in two categories. The first category is based on cyclostationary features, which employs a cyclostationary calculation to represent the modulation features of the user signals. The calculation results are then fed into an artificial neural network for classification. The second category is based on video processing method of action recognition in frequency domain, which includes two approaches. Both of them analyze the FFT sequences of wireless transmissions operating across a cognitive radio network environment, as well as classify their actions in the frequency domain. The first approach employs a covariance descriptor of motion-related features in the frequency domain, which is then fed into an artificial neural network for classification. The second approach is built upon the first approach, but employs a relational database system to record the motion-related feature vectors of primary users on this frequency band. When a certain transmission does not have a match record in the database, a covariance descriptor will be calculated and fed into an artificial neural network for classification. This dissertation is completed by a novel PUE detection approach which employs a distributed sensor network, where each sensor node works as an independent PUE detector. The emphasis of this work is how these nodes collaborate to obtain the final detection results for the whole network. All these proposed approaches have been validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform