DOCSLIB.ORG

IDOL Connector Framework Server 11.3 Administration Guide

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
IDOL Connector Framework Server 11.3 Administration Guide HPE Connector Framework Server Software Version: 11.3 Administration Guide Document Release Date: February 2017 Software Release Date: February 2017 Administration Guide Legal Notices Warranty The only warranties for Hewlett Packard Enterprise Development LP products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. HPE shall not be liable for technical or editorial errors or omissions contained herein. The information contained herein is subject to change without notice. Restricted Rights Legend Confidential computer software. Valid license from HPE required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. Copyright Notice © Copyright 2017 Hewlett Packard Enterprise Development LP Trademark Notices Adobe™ is a trademark of Adobe Systems Incorporated. Microsoft® and Windows® are U.S. registered trademarks of Microsoft Corporation. UNIX® is a registered trademark of The Open Group. This product includes an interface of the 'zlib' general purpose compression library, which is Copyright © 1995-2002 Jean-loup Gailly and Mark Adler. Documentation updates The title page of this document contains the following identifying information: l Software Version number, which indicates the software version. l Document Release Date, which changes each time the document is updated. l Software Release Date, which indicates the release date of this version of the software. To check for recent software updates, go to https://downloads.autonomy.com/productDownloads.jsp. To verify that you are using the most recent edition of a document, go to https://softwaresupport.hpe.com/group/softwaresupport/search-result?doctype=online help. This site requires that you register for an HPE Passport and sign in. To register for an HPE Passport ID, go to https://hpp12.passport.hpe.com/hppcf/login.do. You will also receive updated or new editions if you subscribe to the appropriate product support service. Contact your HPE sales representative for details. Support Visit the HPE Software Support Online web site at https://softwaresupport.hpe.com. This web site provides contact information and details about the products, services, and support that HPE Software offers. HPE Connector Framework Server (11.3) Page 2 of 169 Administration Guide HPE Software online support provides customer self-solve capabilities. It provides a fast and efficient way to access interactive technical support tools needed to manage your business. As a valued support customer, you can benefit by using the support web site to: l Search for knowledge documents of interest l Submit and track support cases and enhancement requests l Access product documentation l Manage support contracts l Look up HPE support contacts l Review information about available services l Enter into discussions with other software customers l Research and register for software training Most of the support areas require that you register as an HPE Passport user and sign in. Many also require a support contract. To register for an HPE Passport ID, go to https://hpp12.passport.hpe.com/hppcf/login.do. To find more information about access levels, go to https://softwaresupport.hpe.com/web/softwaresupport/access-levels. To check for recent software updates, go to https://downloads.autonomy.com/productDownloads.jsp. About this PDF version of online Help This document is a PDF version of the online Help. This PDF file is provided so you can easily print multiple topics or read the online Help. Because this content was originally created to be viewed as online help in a web browser, some topics may not be formatted properly. Some interactive topics may not be present in this PDF version. Those topics can be successfully printed from within the online Help. HPE Connector Framework Server (11.3) Page 3 of 169 Administration Guide Contents Chapter 1: Introduction 9 HPE Connector Framework Server 9 Filter Documents and Extract Subfiles 9 Manipulate and Enrich Documents 10 Index Documents 10 Import Process 11 Display Online Help 11 OEM Certification 12 Related Documentation 12 HPE's IDOL Platform 12 System Architecture 13 Chapter 2: Configure Connector Framework Server 15 Connector Framework Server Configuration File 15 Modify Configuration Parameter Values 16 Configure Connector Framework Server 17 Include an External Configuration File 18 Include the Whole External Configuration File 19 Include Sections of an External Configuration File 19 Include a Parameter from an External Configuration File 20 Merge a Section from an External Configuration File 20 Customize Logging 21 Encrypt Passwords 22 Create a Key File 22 Encrypt a Password 23 Decrypt a Password 24 Example Configuration File 24 Chapter 3: Start and Stop HPE Connector Framework Server 27 Start Connector Framework Server 27 Stop Connector Framework Server 27 Chapter 4: Send Actions to HPE Connector Framework Server 29 Send Actions to HPE Connector Framework Server 29 Asynchronous Actions 29 HPE Connector Framework Server (11.3) Page 4 of 169 Administration Guide Check the Status of an Asynchronous Action 30 Cancel an Asynchronous Action that is Queued 30 Stop an Asynchronous Action that is Running 30 Store Action Queues in an External Database 31 Prerequisites 31 Configure HPE Connector Framework Server 31 Store Action Queues in Memory 33 Use XSL Templates to Transform Action Responses 34 Example XSL Templates 35 Chapter 5: Ingest Data 36 Ingest Data using Connectors 36 Ingest an IDX File 36 Ingest XML 37 Ingest PST Files 39 Ingest Password-Protected Files 39 Ingest Data for Testing 41 Chapter 6: Filter Documents and Extract Subfiles 42 Customize KeyView Filtering 42 Disable Filtering or Extraction for Specific Documents 42 Chapter 7: Manipulate and Enrich Documents 44 Introduction 44 Choose When to Run a Task 45 Create Import and Index Tasks 47 Document Fields for Import Tasks 48 Write and Run Lua Scripts 49 Write a Lua Script 50 Run a Lua Script 50 Debug a Lua Script 50 Lua Scripts Included With CFS 54 Use Named Parameters 55 Enable or Disable Lua Scripts During Testing 56 Example Lua Scripts 56 Add a Field to a Document 56 Count Sections 57 Merge Document Fields 57 Add Titles to Documents 58 Analyze Media 59 HPE Connector Framework Server (11.3) Page 5 of 169 Administration Guide Create a Media Server Configuration 59 Run Analysis on All Supported Files 61 Run Analysis on Specific Documents 62 Media Analysis Output 64 Troubleshoot Media Analysis 65 Analyze Speech 65 Run Analysis on All Audio and Video Files 66 Run Analysis on Specific Documents 67 Use Multiple Speech Servers 68 Language Identification 68 Transcode Audio 69 Speech-To-Text Results 69 Categorize Documents 70 Customize the Query 71 Customize the Output 72 Run Eduction 74 Redact Documents 74 Lua Post Processing 75 Extract Content from HTML 76 Extract Metadata from Files 76 Import Content Into a Document 77 Reject Invalid Documents 78 Reject Documents with Binary Content 78 Reject Documents with Import Errors 78 Reject Documents with Symbolic Content 79 Reject Documents by Word Length 79 Reject All Invalid Documents 80 Split Document Content into Sections 80 Split Files into Multiple Documents 81 Example 81 Write Documents to Disk 83 Write Documents to Disk in IDX Format 83 Write Documents to Disk in XML Format 84 Write Documents to Disk in JSON Format 84 Write Documents to Disk in CSV Format 84 Write Documents to Disk as SQL INSERT Statements 85 Standardize Document Fields 86 Customize Field Standardization 86 Normalize E-mail Addresses 90 Chapter 8: Index Documents 92 HPE Connector Framework Server (11.3) Page 6 of 169 Administration Guide Introduction 92 Configure the Batch Size and Time Interval 93 Index Documents into an IDOL Server 93 Index Documents into Haven OnDemand 94 Prepare Haven OnDemand 94 Configure CFS to Index into Haven OnDemand 95 Index Documents into Vertica 96 Prepare the Vertica Database 97 Configure CFS to Index into Vertica 98 Troubleshooting 99 Index Documents into another CFS 99 Index Documents into MetaStore 100 Document Fields for Indexing 101 AUTN_INDEXPRIORITY 101 Manipulate Documents Before Indexing 101 Set Up Document Tracking 102 Appendix A: KeyView Supported Formats 106 Supported Formats 106 Archive Formats 108 Binary Format 110 Computer-Aided Design Formats 110 Database Formats 112 Desktop Publishing 113 Display Formats 113 Graphic Formats 114 Mail Formats 117 Multimedia Formats 119 Presentation Formats 121 Spreadsheet Formats 123 Text and Markup Formats 125 Word Processing Formats 126 Supported Formats (Detected) 131 Appendix B: KeyView Format Codes 136 KeyView Classes 136 KeyView Formats 137 Appendix C: Document Fields 162 Document Fields 162 HPE Connector Framework Server (11.3) Page 7 of 169 Administration Guide AUTN_IDENTIFIER 163 Sub File Indexes 164 Append Sub File Indexes to the Document Identifier 165 Glossary 166 Send documentation feedback 169 HPE Connector Framework Server (11.3) Page 8 of 169 Chapter 1: Introduction This section provides an overview of Connector Framework Server. • HPE Connector Framework Server 9 • Related Documentation 12 • HPE's IDOL Platform 12 • System Architecture 13 HPE Connector Framework Server HPE Connector Framework Server (HPE CFS) processes the information that is retrieved by connectors, and then indexes the information into one or more indexes, such as IDOL Server or Haven OnDemand. When connectors send documents to CFS, the documents contain only metadata extracted from the repository, such as the location of a file or record that the connector has retrieved. CFS extracts the file- specific metadata and file content from the file and adds it to the document. This allows IDOL to search and extract meaning from the information contained in the repository, without needing to process the information in its native format. CFS also provides features to manipulate and enrich documents before they are indexed.
Load more

Recommended publications
  • Scalable Speculative Parallelization on Commodity Clusters
    Scalable Speculative Parallelization on Commodity Clusters Hanjun Kim Arun Raman Feng Liu Jae W. Leey David I. August Departments of Electrical Engineering and Computer Science y Parakinetics Inc. Princeton University Princeton, USA Princeton, USA [email protected] {hanjunk, rarun, fengliu, august}@princeton.edu Abstract by the cluster is difficult. For these reasons, such programs have been deemed unsuitable for execution on clusters. While clusters of commodity servers and switches are the most popular form of large-scale parallel computers, many programs are Recent research has demonstrated that a combination of not easily parallelized for execution upon them. In particular, high pipeline parallelism (DSWP), thread-level speculation (TLS), inter-node communication cost and lack of globally shared memory and speculative pipeline parallelism (Spec-DSWP) can un- appear to make clusters suitable only for server applications with lock significant amounts of parallelism in general-purpose abundant task-level parallelism and scientific applications with regu- programs on shared memory systems [6, 24, 27, 29, 30, 32, lar and independent units of work. Clever use of pipeline parallelism (DSWP), thread-level speculation (TLS), and speculative pipeline 36, 37]. Pipeline parallelization techniques such as DSWP parallelism (Spec-DSWP) can mitigate the costs of inter-thread partition a loop in such a way that the critical path is executed communication on shared memory multicore machines. This paper in a thread-local fashion, with off-critical path data flowing presents Distributed Software Multi-threaded Transactional memory unidirectionally through the pipeline. The combination of these (DSMTX), a runtime system which makes these techniques applicable two factors makes the program execution highly insensitive to non-shared memory clusters, allowing them to efficiently address inter-node communication costs.
    [Show full text]
  • Symantec Web Security Service Policy Guide
    Web Security Service Policy Guide Revision: NOV.07.2020 Symantec Web Security Service/Page 2 Policy Guide/Page 3 Copyrights Broadcom, the pulse logo, Connecting everything, and Symantec are among the trademarks of Broadcom. The term “Broadcom” refers to Broadcom Inc. and/or its subsidiaries. Copyright © 2020 Broadcom. All Rights Reserved. The term “Broadcom” refers to Broadcom Inc. and/or its subsidiaries. For more information, please visit www.broadcom.com. Broadcom reserves the right to make changes without further notice to any products or data herein to improve reliability, function, or design. Information furnished by Broadcom is believed to be accurate and reliable. However, Broadcom does not assume any liability arising out of the application or use of this information, nor the application or use of any product or circuit described herein, neither does it convey any license under its patent rights nor the rights of others. Policy Guide/Page 4 Symantec WSS Policy Guide The Symantec Web Security Service solutions provide real-time protection against web-borne threats. As a cloud-based product, the Web Security Service leverages Symantec's proven security technology, including the WebPulse™ cloud community. With extensive web application controls and detailed reporting features, IT administrators can use the Web Security Service to create and enforce granular policies that are applied to all covered users, including fixed locations and roaming users. If the WSS is the body, then the policy engine is the brain. While the WSS by default provides malware protection (blocks four categories: Phishing, Proxy Avoidance, Spyware Effects/Privacy Concerns, and Spyware/Malware Sources), the additional policy rules and options you create dictate exactly what content your employees can and cannot access—from global allows/denials to individual users at specific times from specific locations.
    [Show full text]
  • IDOL Connector Framework Server 12.0 Administration Guide
    Connector Framework Server Software Version 12.0 Administration Guide Document Release Date: June 2018 Software Release Date: June 2018 Administration Guide Legal notices Copyright notice © Copyright 2018 Micro Focus or one of its affiliates. The only warranties for products and services of Micro Focus and its affiliates and licensors (“Micro Focus”) are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. Micro Focus shall not be liable for technical or editorial errors or omissions contained herein. The information contained herein is subject to change without notice. Trademark notices Adobe™ is a trademark of Adobe Systems Incorporated. Microsoft® and Windows® are U.S. registered trademarks of Microsoft Corporation. UNIX® is a registered trademark of The Open Group. Documentation updates The title page of this document contains the following identifying information: l Software Version number, which indicates the software version. l Document Release Date, which changes each time the document is updated. l Software Release Date, which indicates the release date of this version of the software. To verify you are using the most recent edition of a document, go to https://softwaresupport.softwaregrp.com/group/softwaresupport/search-result?doctype=online help. You will also receive new or updated editions of documentation if you subscribe to the appropriate product support service. Contact your Micro Focus sales representative for details. To check for new versions of software, go to https://www.hpe.com/software/entitlements. To check for recent software patches, go to https://softwaresupport.softwaregrp.com/patches. The sites listed in this section require you to sign in with a Software Passport.
    [Show full text]
  • Migratory Compression
    Migratory Compression: Coarse-grained Data Reordering to Improve Compressibility Xing Lin, University of Utah; Guanlin Lu, Fred Douglis, Philip Shilane, and Grant Wallace, EMC Corporation— Data Protection and Availability Division https://www.usenix.org/conference/fast14/technical-sessions/presentation/lin This paper is included in the Proceedings of the 12th USENIX Conference on File and Storage Technologies (FAST ’14). February 17–20, 2014 • Santa Clara, CA USA ISBN 978-1-931971-08-9 Open access to the Proceedings of the 12th USENIX Conference on File and Storage Technologies (FAST ’14) is sponsored by Migratory Compression: Coarse-grained Data Reordering to Improve Compressibility Xing Lin1, Guanlin Lu2, Fred Douglis2, Philip Shilane2, Grant Wallace2 1University of Utah, 2EMC Corporation – Data Protection and Availability Division Abstract data; the larger the window size, the greater the opportu- nity to find redundant strings, leading to better compres- We propose Migratory Compression (MC), a coarse- sion. However, to limit the overhead in finding redun- grained data transformation, to improve the effectiveness dancy, most real-world implementations use small win- of traditional compressors in modern storage systems. dow sizes. For example, DEFLATE, used by gzip, has a In MC, similar data chunks are re-located together, to 64 KB sliding window [6] and the maximum window for improve compression factors. After decompression, bzip2 is 900 KB [8]. The only compression algorithm migrated chunks return to their previous locations. We we are aware of that uses larger window sizes is LZMA evaluate the compression effectiveness and overhead in 7z [1], which supports history up to 1 GB.1 It usually of MC, explore reorganization approaches on a variety compresses better than gzip and bzip2 but takes sig- of datasets, and present a prototype implementation of nificantly longer.
    [Show full text]
  • Oracle Universal Installer and Opatch User's Guide for Windows and UNIX
    Oracle® Universal Installer and OPatch User’s Guide 10g Release 2 (10.2) for Windows and UNIX B16227-12 August 2010 Oracle Universal Installer and OPatch User's Guide, 10g Release 2 (10.2) for Windows and UNIX B16227-12 Copyright © 1996, 2010, Oracle and/or its affiliates. All rights reserved. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this software or related documentation is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are "commercial computer software" or "commercial technical data" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation shall be subject to the restrictions and license terms set forth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License (December 2007).
    [Show full text]
  • Digital Forensics Formats: Seeking a Digital Preservation Storage Container Format for Web Archiving
    doi:10.2218/ijdc.v7i2.227 Digital Forensics Formats 21 The International Journal of Digital Curation Volume 7, Issue 2 | 2012 Digital Forensics Formats: Seeking a Digital Preservation Storage Container Format for Web Archiving Yunhyong Kim, Humanities Advanced Technology and Information Institute, University of Glasgow Seamus Ross, Faculty of Information, University of Toronto, Canada and Humanities Advanced Technology and Information Institute, University of Glasgow Abstract In this paper we discuss archival storage container formats from the point of view of digital curation and preservation, an aspect of preservation overlooked by most other studies. Considering established approaches to data management as our jumping off point, we selected seven container format attributes that are core to the long term accessibility of digital materials. We have labeled these core preservation attributes. These attributes are then used as evaluation criteria to compare storage container formats belonging to five common categories: formats for archiving selected content (e.g. tar, WARC), disk image formats that capture data for recovery or installation (partimage, dd raw image), these two types combined with a selected compression algorithm (e.g. tar+gzip), formats that combine packing and compression (e.g. 7-zip), and forensic file formats for data analysis in criminal investigations (e.g. aff – Advanced Forensic File format). We present a general discussion of the storage container format landscape in terms of the attributes we discuss, and make a direct comparison between the three most promising archival formats: tar, WARC, and aff. We conclude by suggesting the next steps to take the research forward and to validate the observations we have made.
    [Show full text]
  • Economic Value of Instream Flows in Montana: a Travel Cost Model Approach
    University of Montana ScholarWorks at University of Montana Graduate Student Theses, Dissertations, & Professional Papers Graduate School 1989 Economic value of instream flows in Montana: A travel cost model approach Christopher J. Neher The University of Montana Follow this and additional works at: https://scholarworks.umt.edu/etd Let us know how access to this document benefits ou.y Recommended Citation Neher, Christopher J., "Economic value of instream flows in Montana: A travel cost model approach" (1989). Graduate Student Theses, Dissertations, & Professional Papers. 8515. https://scholarworks.umt.edu/etd/8515 This Thesis is brought to you for free and open access by the Graduate School at ScholarWorks at University of Montana. It has been accepted for inclusion in Graduate Student Theses, Dissertations, & Professional Papers by an authorized administrator of ScholarWorks at University of Montana. For more information, please contact [email protected]. COPYRIGHT ACT OF 1976 Th is is an unpublished manuscript in which copyright SUBSISTS. Any further reprinting of its contents must be APPROVED BY THE AUTHOR. Mansfield Library Un iv e r s ity of Montana Date :____1989 __ Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. THE ECONOMIC VALUE OF INSTREAM FLOWS IN MONTANA: A TRAVEL COST MODEL APPROACH By Christopher J. Neher B.S. University of Idaho, 1979. Presented in partial fulfillment of the requirements for the degree of Master of Arts University of Montana 1989 Approved by Chairman, Board of Examiners Dean, Graduate School Date 7/ Reproduced with permission of the copyright owner.
    [Show full text]
  • Bogog00000000000000
    US 20190236273A1 ( 19) United States (12 ) Patent Application Publication (10 ) Pub. No. : US 2019 /0236273 A1 SAXE et al. (43 ) Pub. Date : Aug. 1 , 2019 ( 54 ) METHODS AND APPARATUS FOR GO6N 3 /04 (2006 .01 ) DETECTION OF MALICIOUS DOCUMENTS G06K 9 /62 (2006 .01 ) USING MACHINE LEARNING (52 ) U .S . CI. CPC .. G06F 21/ 563 ( 2013 .01 ) ; GO6N 20 / 20 (71 ) Applicant: Sophos Limited , Abingdon (GB ) (2019 .01 ) ; G06K 9 /6256 ( 2013 .01 ) ; G06K ( 72 ) Inventors: Joshua Daniel SAXE , Los Angeles, 9 /6267 ( 2013 .01 ) ; G06N 3 / 04 ( 2013 .01 ) CA (US ) ; Ethan M . RUDD , Colorado Springs , CO (US ) ; Richard HARANG , (57 ) ABSTRACT Alexandria , VA (US ) An apparatus for detecting malicious files includes a memory and a processor communicatively coupled to the ( 73 ) Assignee : Sophos Limited , Abingdon (GB ) memory. The processor receives multiple potentially mali cious files. A first potentially malicious file has a first file ( 21) Appl . No. : 16 /257 , 749 format , and a second potentially malicious file has a second file format different than the first file format. The processor ( 22 ) Filed : Jan . 25 , 2019 extracts a first set of strings from the first potentially malicious file , and extracts a second set of strings from the Related U . S . Application Data second potentially malicious file . First and second feature (60 ) Provisional application No . 62/ 622 ,440 , filed on Jan . vectors are defined based on lengths of each string from the 26 , 2018 . associated set of strings . The processor provides the first feature vector as an input to a machine learning model to Publication Classification produce a maliciousness classification of the first potentially (51 ) Int.
    [Show full text]
  • Using Data Compression for Energy-Efficient Reprogramming Of
    Using Data Compression for Energy-Efficient Reprogramming of Wireless Sensor Networks Nicolas Tsiftes <[email protected]> Swedish Institute of Computer Science Box 1263, SE-164 29 Kista, Sweden SICS Technical Report T2007:13 ISSN 1100-3154 ISRN:SICS-T–2007/13-SE December 18, 2007 Keywords: wireless sensor networks, data compression, reprogramming, experimental eval- uation, energy efficiency Abstract Software used in sensor networks to perform tasks such as sensing, network routing, and operating system services can be subject to changes or replacements during the long lifetimes of many sensor networks. The task of reprogramming the network nodes consumes a significant amount of energy and increases the network congestion because the software is sent over radio in an epidemic manner to all the nodes. In this thesis, I show that the use of data compression of dynamically link- able modules makes the reprogramming more energy-efficient and reduces the time needed for the software to propagate. The cost for using data compression is that the decompression algorithm must execute for a relatively long time, and that the software takes five to ten kilobytes to store on the sensor nodes. Contents 1 Introduction 5 1.1 Problem Statement . 5 1.2 Method ................................ 6 1.3 Limitations . 6 1.4 Alternative Approaches . 6 1.5 Scientific Contributions . 7 1.6 ReportStructure............................ 7 2 Background 8 2.1 WirelessSensorNetworks ...................... 8 2.1.1 Software Updates in Wireless Sensor Networks . 8 2.1.2 The Contiki Operating System . 10 2.2 Data Compression Algorithms . 12 2.2.1 Lossless and Lossy Algorithms . 12 2.2.2 Statistical Algorithms .
    [Show full text]
  • Data Description and Usage
    HEALTH AND RETIREMENT STUDY Respondent Cross-Year Benefits Restricted Data Data Description and Usage Version 5.2 October 2020 To the Restricted Data Investigator: This restricted data set is intended for exclusive use by you and the persons specified in the Agreement for Use of Restricted Data from the Health and Retirement Study and/or the Supplemental Agreement with Research Staff for Use of Restricted Data from the Health and Retirement Study. If there are any questions about this data set and its use, refer to the HRS Restricted Data page (https://hrs.isr.umich.edu/data-products/restricted-data) or contact the HRS Help Desk ([email protected]). This document may not be reproduced without the written consent of the staff of the Health and Retirement Study, The Institute for Social Research, The University of Michigan. Table of Contents 1. Overview and Acknowledgments ............................................................................................... 3 2. Obtaining the Data ........................................................................................................................... 3 2c. Publications Based on Restricted Data ............................................................................................. 3 3. Cross-Year Benefit Data Set Content ......................................................................................... 4 3a. File Structure .............................................................................................................................................
    [Show full text]
  • Research Article N-Gram-Based Text Compression
    Hindawi Publishing Corporation Computational Intelligence and Neuroscience Volume 2016, Article ID 9483646, 11 pages http://dx.doi.org/10.1155/2016/9483646 Research Article n-Gram-Based Text Compression Vu H. Nguyen,1 Hien T. Nguyen,1 Hieu N. Duong,2 and Vaclav Snasel3 1 Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam 2Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam 3Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic Correspondence should be addressed to Hien T. Nguyen; [email protected] Received 21 May 2016; Revised 2 August 2016; Accepted 25 September 2016 Academic Editor: Geun S. Jo Copyright © 2016 Vu H. Nguyen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n- gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total.
    [Show full text]
  • Pentest-Report Chubaofs Pentest 08.-09.2020 Cure53, Dr.-Ing
    Dr.-Ing. Mario Heiderich, Cure53 Bielefelder Str. 14 D 10709 Berlin cure53.de · [email protected] Pentest-Report ChubaoFS Pentest 08.-09.2020 Cure53, Dr.-Ing. M. Heiderich, M. Wege, MSc. D. Weißer, MSc. F. Fäßler, MSc. R. Peraglie Index Introduction Scope Identified Vulnerabilities CFS-01-003 WP1: Insecure SHA1 password-hashing (Low) CFS-01-004 WP1: Linux file permissions ineffective for ACL (High) CFS-01-005 WP1: Missing HMAC leads to CBC padding oracle (Medium) CFS-01-007 WP1: No brute-force protection on time-unsafe comparisons (Low) CFS-01-008 WP1: Unencrypted raw TCP traffic to Meta- and DataNode (High) CFS-01-009 WP1: Unauthenticated raw TCP traffic to Meta- and DataNode (High) CFS-01-010 WP1: Lack of TCP traffic message replay protection (Medium) CFS-01-011 WP1: Rogue Meta- and DataNodes possible due to lack of ACL (High) CFS-01-015 WP1: API freely discloses all user-secrets (Critical) CFS-01-016 WP2: Default Docker deployment insecure on public hosts (High) CFS-01-022 WP1: HTTP clear-text ObjectNode REST API exposed (High) CFS-01-024 WP2: Bypassing Skip-Owner-Validation header authentication (Medium) Miscellaneous Issues CFS-01-001 WP1: Usage of math/rand within crypto-utils and utils (Info) CFS-01-002 WP1: TLS version not enforced for AuthNode HTTP server (Low) CFS-01-006 WP1: Password hashes can be used to authenticate (Low) CFS-01-012 WP1: HTTP parameter pollution in HTTP clients (Medium) CFS-01-013 WP1: Unsalted MD5 authKey-Computation in ObjectNode (Low) CFS-01-014 WP2: Lack of password complexity in MasterNode (Low) CFS-01-017 WP2: Docker deployment stores client.json as world-readable (Medium) CFS-01-018 WP1: Docker deployment logs credentials as world-readable (Medium) CFS-01-019 WP1: Folders can be moved into their own child folders (Low) CFS-01-020 WP1: Missing filename-validation allows folder corruption (Low) CFS-01-021 WP1: Debugging endpoint /debug/pprof exposed (Info) CFS-01-023 WP1: Build system lacks stack canaries, PIE and FORTIFY (Medium) Cure53, Berlin · 09/08/20 1/37 Dr.-Ing.
    [Show full text]