Topologies for satellite constellations in a cross-linked space backbone network

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.Includes bibliographical references (p. 101).An evolutionary space data network can be formed from satellites serving as both backbone and user-access nodes connected via high-speed cross-links. Such a space backbone network should support spacecraft-to-ground and spacecraft-to-spacecraft links for users of various altitudes (LEO, MEO, GEO and HEO). One main consideration in the design of such a space network is the physical altitude and topology of the backbone satellite constellation. In this thesis, different GEO, MEO, and LEO configurations are considered as backbone topologies to serve the projected user altitudes and requirements. First, exact constellations are determined for each proposed configuration that meet the user coverage requirements while maximizing coverage efficiency. The complexities of these constellations are then compared using constellation parameters such as altitude, and the number of orbital planes required, and the number of satellites required per plane, as well as individual satellite parameters like the number of antennae required, the necessary slewing rate of each antenna, the power required by each antenna, and the physical placement of these antennae on the satellites. The complexity parameters of each individual satellite will be determined for two of the types of communications links used on the satellite, namely links between the user satellites and backbone satellites and links between backbone satellites. These parameters are then used in a speculative cost model to determine the cost versus complexity of each constellation. Through these calculations, a GEO backbone consisting of three satellites is determined to require a minimum number of apertures for both types of links as well as allowing an optimal onboard placement of these apertures. Thus, it possesses cost vs. complexity characteristics superior to other constellations and should be the choice for a space-borne data backbone network.by Jason H. Bau.M.Eng

A Security Evaluation of DNSSEC with NSEC3

Domain Name System Security Extensions (DNSSEC) and Hashed Authenticated Denial of Existence (NSEC3) are slated for adoption by important parts of the DNS hierarchy, including the root zone, as a solution to vulnerabilities such as ”cache-poisoning” attacks. We study the security goals and operation of DNSSEC/NSEC3 using Murphi, a finite-state enumeration tool, to analyze security properties that may be relevant to various deployment scenarios. Our systematic study reveals several subtleties and potential pitfalls that can be avoided by proper configuration choices, including resource records that may remain valid after the expiration of relevant signatures and potential insertion of forged names into a DNSSEC-enabled domain via the opt-out option. We demonstrate the exploitability of DNSSEC opt-out options in an enterprise setting by constructing a browser cookie-stealing attack on a laboratory domain. Under recommended configuration settings, further Murphi model checking finds no vulnerabilities within our threat model, suggesting that DNSSEC with NSEC3 provides significant security benefits

Structural Learning of Attack Vectors for Generating Mutated XSS Attacks

Web applications suffer from cross-site scripting (XSS) attacks that resulting from incomplete or incorrect input sanitization. Learning the structure of attack vectors could enrich the variety of manifestations in generated XSS attacks. In this study, we focus on generating more threatening XSS attacks for the state-of-the-art detection approaches that can find potential XSS vulnerabilities in Web applications, and propose a mechanism for structural learning of attack vectors with the aim of generating mutated XSS attacks in a fully automatic way. Mutated XSS attack generation depends on the analysis of attack vectors and the structural learning mechanism. For the kernel of the learning mechanism, we use a Hidden Markov model (HMM) as the structure of the attack vector model to capture the implicit manner of the attack vector, and this manner is benefited from the syntax meanings that are labeled by the proposed tokenizing mechanism. Bayes theorem is used to determine the number of hidden states in the model for generalizing the structure model. The paper has the contributions as following: (1) automatically learn the structure of attack vectors from practical data analysis to modeling a structure model of attack vectors, (2) mimic the manners and the elements of attack vectors to extend the ability of testing tool for identifying XSS vulnerabilities, (3) be helpful to verify the flaws of blacklist sanitization procedures of Web applications. We evaluated the proposed mechanism by Burp Intruder with a dataset collected from public XSS archives. The results show that mutated XSS attack generation can identify potential vulnerabilities.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330

Winnowing DNA for Rare Sequences: Highly Specific Sequence and Methylation Based Enrichment

Rare mutations in cell populations are known to be hallmarks of many diseases and cancers. Similarly, differential DNA methylation patterns arise in rare cell populations with diagnostic potential such as fetal cells circulating in maternal blood. Unfortunately, the frequency of alleles with diagnostic potential, relative to wild-type background sequence, is often well below the frequency of errors in currently available methods for sequence analysis, including very high throughput DNA sequencing. We demonstrate a DNA preparation and purification method that through non-linear electrophoretic separation in media containing oligonucleotide probes, achieves 10,000 fold enrichment of target DNA with single nucleotide specificity, and 100 fold enrichment of unmodified methylated DNA differing from the background by the methylation of a single cytosine residue

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder:The ENIGMA adventure

International audienc

The Fifteenth Data Release of the Sloan Digital Sky Surveys: First Release of MaNGA-derived Quantities, Data Visualization Tools, and Stellar Library

Twenty years have passed since first light for the Sloan Digital Sky Survey (SDSS). Here, we release data taken by the fourth phase of SDSS (SDSS-IV) across its first three years of operation (2014 July–2017 July). This is the third data release for SDSS-IV, and the 15th from SDSS (Data Release Fifteen; DR15). New data come from MaNGA—we release 4824 data cubes, as well as the first stellar spectra in the MaNGA Stellar Library (MaStar), the first set of survey-supported analysis products (e.g., stellar and gas kinematics, emission-line and other maps) from the MaNGA Data Analysis Pipeline, and a new data visualization and access tool we call "Marvin." The next data release, DR16, will include new data from both APOGEE-2 and eBOSS; those surveys release no new data here, but we document updates and corrections to their data processing pipelines. The release is cumulative; it also includes the most recent reductions and calibrations of all data taken by SDSS since first light. In this paper, we describe the location and format of the data and tools and cite technical references describing how it was obtained and processed. The SDSS website (www.sdss.org) has also been updated, providing links to data downloads, tutorials, and examples of data use. Although SDSS-IV will continue to collect astronomical data until 2020, and will be followed by SDSS-V (2020–2025), we end this paper by describing plans to ensure the sustainability of the SDSS data archive for many years beyond the collection of data

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The 16th Data Release of the Sloan Digital Sky Surveys : First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).Peer reviewe