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Security in Cloud Computing a Security Assessment of Cloud Computing Providers for an Online Receipt Storage
Security in Cloud Computing A Security Assessment of Cloud Computing Providers for an Online Receipt Storage Mats Andreassen Kåre Marius Blakstad Master of Science in Computer Science Submission date: June 2010 Supervisor: Lillian Røstad, IDI Norwegian University of Science and Technology Department of Computer and Information Science Problem Description We will survey some current cloud computing vendors and compare them to find patterns in how their feature sets are evolving. The start-up firm dSafe intends to exploit the promises of cloud computing in order to launch their business idea with only marginal hardware and licensing costs. We must define the criteria for how dSafe's application can be sufficiently secure in the cloud as well as how dSafe can get there. Assignment given: 14. January 2010 Supervisor: Lillian Røstad, IDI Abstract Considerations with regards to security issues and demands must be addressed before migrating an application into a cloud computing environment. Different vendors, Microsoft Azure, Amazon Web Services and Google AppEngine, provide different capabilities and solutions to the individual areas of concern presented by each application. Through a case study of an online receipt storage application from the company dSafe, a basis is formed for the evaluation. The three cloud computing vendors are assessed with regards to a security assessment framework provided by the Cloud Security Alliance and the application of this on the case study. Finally, the study is concluded with a set of general recommendations and the recommendation of a cloud vendor. This is based on a number of security as- pects related to the case study’s existence in the cloud. -
Reliability and Security of Large Scale Data Storage in Cloud Computing C.W
This article is part of the Reliability Society 2010 Annual Technical Report Reliability and Security of Large Scale Data Storage in Cloud Computing C.W. Hsu ¹¹¹ C.W. Wang ²²² Shiuhpyng Shieh ³³³ Department of Computer Science Taiwan Information Security Center at National Chiao Tung University NCTU (TWISC@NCTU) Email: ¹[email protected] ³[email protected] ²[email protected] Abstract In this article, we will present new challenges to the large scale cloud computing, namely reliability and security. Recent progress in the research area will be briefly reviewed. It has been proved that it is impossible to satisfy consistency, availability, and partitioned-tolerance simultaneously. Tradeoff becomes crucial among these factors to choose a suitable data access model for a distributed storage system. In this article, new security issues will be addressed and potential solutions will be discussed. Introduction “Cloud Computing ”, a novel computing model for large-scale application, has attracted much attention from both academic and industry. Since 2006, Google Inc. Chief Executive Eric Schmidt introduced the term into industry, and related research had been carried out in recent years. Cloud computing provides scalable deployment and fine-grained management of services through efficient resource sharing mechanism (most of them are for hardware resources, such as VM). Convinced by the manner called “ pay-as-you-go ” [1][2], companies can lower the cost of equipment management including machine purchasing, human maintenance, data backup, etc. Many cloud services rapidly appear on the Internet, such as Amazon’s EC2, Microsoft’s Azure, Google’s Gmail, Facebook, and so on. However, the well-known definition of the term “Cloud Computing ” was first given by Prof. -
Amazon Dynamodb
Dynamo Amazon DynamoDB Nicolas Travers Inspiré de Advait Deo Vertigo N. Travers ESILV : Dynamo Amazon DynamoDB – What is it ? • Fully managed nosql database service on AWS • Data model in the form of tables • Data stored in the form of items (name – value attributes) • Automatic scaling ▫ Provisioned throughput ▫ Storage scaling ▫ Distributed architecture • Easy Administration • Monitoring of tables using CloudWatch • Integration with EMR (Elastic MapReduce) ▫ Analyze data and store in S3 Vertigo N. Travers ESILV : Dynamo Amazon DynamoDB – What is it ? key=value key=value key=value key=value Table Item (64KB max) Attributes • Primary key (mandatory for every table) ▫ Hash or Hash + Range • Data model in the form of tables • Data stored in the form of items (name – value attributes) • Secondary Indexes for improved performance ▫ Local secondary index ▫ Global secondary index • Scalar data type (number, string etc) or multi-valued data type (sets) Vertigo N. Travers ESILV : Dynamo DynamoDB Architecture • True distributed architecture • Data is spread across hundreds of servers called storage nodes • Hundreds of servers form a cluster in the form of a “ring” • Client application can connect using one of the two approaches ▫ Routing using a load balancer ▫ Client-library that reflects Dynamo’s partitioning scheme and can determine the storage host to connect • Advantage of load balancer – no need for dynamo specific code in client application • Advantage of client-library – saves 1 network hop to load balancer • Synchronous replication is not achievable for high availability and scalability requirement at amazon • DynamoDB is designed to be “always writable” storage solution • Allows multiple versions of data on multiple storage nodes • Conflict resolution happens while reads and NOT during writes ▫ Syntactic conflict resolution ▫ Symantec conflict resolution Vertigo N. -
Amazon's Antitrust Paradox
LINA M. KHAN Amazon’s Antitrust Paradox abstract. Amazon is the titan of twenty-first century commerce. In addition to being a re- tailer, it is now a marketing platform, a delivery and logistics network, a payment service, a credit lender, an auction house, a major book publisher, a producer of television and films, a fashion designer, a hardware manufacturer, and a leading host of cloud server space. Although Amazon has clocked staggering growth, it generates meager profits, choosing to price below-cost and ex- pand widely instead. Through this strategy, the company has positioned itself at the center of e- commerce and now serves as essential infrastructure for a host of other businesses that depend upon it. Elements of the firm’s structure and conduct pose anticompetitive concerns—yet it has escaped antitrust scrutiny. This Note argues that the current framework in antitrust—specifically its pegging competi- tion to “consumer welfare,” defined as short-term price effects—is unequipped to capture the ar- chitecture of market power in the modern economy. We cannot cognize the potential harms to competition posed by Amazon’s dominance if we measure competition primarily through price and output. Specifically, current doctrine underappreciates the risk of predatory pricing and how integration across distinct business lines may prove anticompetitive. These concerns are height- ened in the context of online platforms for two reasons. First, the economics of platform markets create incentives for a company to pursue growth over profits, a strategy that investors have re- warded. Under these conditions, predatory pricing becomes highly rational—even as existing doctrine treats it as irrational and therefore implausible. -
Performance at Scale with Amazon Elasticache
Performance at Scale with Amazon ElastiCache July 2019 Notices Customers are responsible for making their own independent assessment of the information in this document. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. © 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved. Contents Introduction .......................................................................................................................... 1 ElastiCache Overview ......................................................................................................... 2 Alternatives to ElastiCache ................................................................................................. 2 Memcached vs. Redis ......................................................................................................... 3 ElastiCache for Memcached ............................................................................................... 5 Architecture with ElastiCache for Memcached ............................................................... -
Defendant Apple Inc.'S Proposed Findings of Fact and Conclusions Of
Case 4:20-cv-05640-YGR Document 410 Filed 04/08/21 Page 1 of 325 1 THEODORE J. BOUTROUS JR., SBN 132099 MARK A. PERRY, SBN 212532 [email protected] [email protected] 2 RICHARD J. DOREN, SBN 124666 CYNTHIA E. RICHMAN (D.C. Bar No. [email protected] 492089; pro hac vice) 3 DANIEL G. SWANSON, SBN 116556 [email protected] [email protected] GIBSON, DUNN & CRUTCHER LLP 4 JAY P. SRINIVASAN, SBN 181471 1050 Connecticut Avenue, N.W. [email protected] Washington, DC 20036 5 GIBSON, DUNN & CRUTCHER LLP Telephone: 202.955.8500 333 South Grand Avenue Facsimile: 202.467.0539 6 Los Angeles, CA 90071 Telephone: 213.229.7000 ETHAN DETTMER, SBN 196046 7 Facsimile: 213.229.7520 [email protected] ELI M. LAZARUS, SBN 284082 8 VERONICA S. MOYÉ (Texas Bar No. [email protected] 24000092; pro hac vice) GIBSON, DUNN & CRUTCHER LLP 9 [email protected] 555 Mission Street GIBSON, DUNN & CRUTCHER LLP San Francisco, CA 94105 10 2100 McKinney Avenue, Suite 1100 Telephone: 415.393.8200 Dallas, TX 75201 Facsimile: 415.393.8306 11 Telephone: 214.698.3100 Facsimile: 214.571.2900 Attorneys for Defendant APPLE INC. 12 13 14 15 UNITED STATES DISTRICT COURT 16 FOR THE NORTHERN DISTRICT OF CALIFORNIA 17 OAKLAND DIVISION 18 19 EPIC GAMES, INC., Case No. 4:20-cv-05640-YGR 20 Plaintiff, Counter- DEFENDANT APPLE INC.’S PROPOSED defendant FINDINGS OF FACT AND CONCLUSIONS 21 OF LAW v. 22 APPLE INC., The Honorable Yvonne Gonzalez Rogers 23 Defendant, 24 Counterclaimant. Trial: May 3, 2021 25 26 27 28 Gibson, Dunn & Crutcher LLP DEFENDANT APPLE INC.’S PROPOSED FINDINGS OF FACT AND CONCLUSIONS OF LAW, 4:20-cv-05640- YGR Case 4:20-cv-05640-YGR Document 410 Filed 04/08/21 Page 2 of 325 1 Apple Inc. -
Rose Gardner Mysteries
JABberwocky Literary Agency, Inc. Est. 1994 RIGHTS CATALOG 2019 JABberwocky Literary Agency, Inc. 49 W. 45th St., 12th Floor, New York, NY 10036-4603 Phone: +1-917-388-3010 Fax: +1-917-388-2998 Joshua Bilmes, President [email protected] Adriana Funke Karen Bourne International Rights Director Foreign Rights Assistant [email protected] [email protected] Follow us on Twitter: @awfulagent @jabberworld For the latest news, reviews, and updated rights information, visit us at: www.awfulagent.com The information in this catalog is accurate as of [DATE]. Clients, titles, and availability should be confirmed. Table of Contents Table of Contents Author/Section Genre Page # Author/Section Genre Page # Tim Akers ....................... Fantasy..........................................................................22 Ellery Queen ................... Mystery.........................................................................64 Robert Asprin ................. Fantasy..........................................................................68 Brandon Sanderson ........ New York Times Bestseller.......................................51-60 Marie Brennan ............... Fantasy..........................................................................8-9 Jon Sprunk ..................... Fantasy..........................................................................36 Peter V. Brett .................. Fantasy.....................................................................16-17 Michael J. Sullivan ......... Fantasy.....................................................................26-27 -
Amazon Documentdb Deep Dive
DAT326 Amazon DocumentDB deep dive Joseph Idziorek Antra Grover Principal Product Manager Software Development Engineer Amazon Web Services Fulfillment By Amazon © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Agenda What is the purpose of a document database? What customer problems does Amazon DocumentDB (with MongoDB compatibility) solve and how? Customer use case and learnings: Fulfillment by Amazon What did we deliver for customers this year? What’s next? © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved. Purpose-built databases Relational Key value Document In-memory Graph Search Time series Ledger Why document databases? Denormalized data Normalized data model model { 'name': 'Bat City Gelato', 'price': '$', 'rating': 5.0, 'review_count': 46, 'categories': ['gelato', 'ice cream'], 'location': { 'address': '6301 W Parmer Ln', 'city': 'Austin', 'country': 'US', 'state': 'TX', 'zip_code': '78729'} } Why document databases? GET https://api.yelp.com/v3/businesses/{id} { 'name': 'Bat City Gelato', 'price': '$', 'rating': 5.0, 'review_count': 46, 'categories': ['gelato', 'ice cream'], 'location': { 'address': '6301 W Parmer Ln', 'city': 'Austin', 'country': 'US', 'state': 'TX', 'zip_code': '78729'} } Why document databases? response = yelp_api.search_query(term='ice cream', location='austin, tx', sort_by='rating', limit=5) Why document databases? for i in response['businesses']: col.insert_one(i) db.businesses.aggregate([ { $group: { _id: "$price", ratingAvg: { $avg: "$rating"}} } ]) db.businesses.find({ -
Descargar Catastro Prestadores De Servicios Digitales Formato
MARCA SERVICIOS FECHA FIN DE PROVEEDOR DESCRIPCIÓN REFERENCIA DOMICILIADO O EP REGISTRADO SRI FECHA DE REGISTRO COMISIÓN REGISTRO NETFLIX Contenidos audiovisuales por streaming 1 Netflix Contenidos audiovisuales por streaming 1 SPOTIFY Reproducción de música vía streaming 1 Spotify Reproducción de música vía streaming 1 APPLE COM BILL Software y servicios en línea 1 APPLE COM/BILL Software y servicios en línea 1 APPLE,COM BILL Software y servicios en línea 1 APPLE,COM/BILL Software y servicios en línea 1 APPLE.COM BILL Software y servicios en línea 1 APPLE.COM/BILL Software y servicios en línea 1 APPLE.COMBILL Software y servicios en línea 1 APPLECOM BILL Software y servicios en línea 1 APPLECOM/BILL Software y servicios en línea 1 APPLECOMBILL Software y servicios en línea 1 APPLESERVIC Servicio al Cliente en línea 1 GOOGLE Servicios relacionados con Internet y software 1 Google Servicios relacionados con Internet y software 1 Servicio de vídeos disponible en streaming y AMAZON PRIME 1 suscripción para envíos gratuitos AMAZON DIGIT Servicio de vídeos disponible en streaming 1 AMAZON MUSIC Plataforma de retransmisión de música 1 AMAZON VIDEO Servicio de vídeos disponible en streaming 1 AMAZON LUNA Servicio de videojuegos en línea 1 AMAZON MX DIGITAL Servicio de vídeos disponible en streaming 1 AMAZON KIDS Servicios Multimedia en línea para niños 1 AMAZON SELLER SERVICES Servicios para vendedores en línea 1 Amazon Prime Servicio de vídeos disponible en streaming 1 AmazonPrime Servicio de vídeos disponible en streaming 1 Amazon.ca Prime -
Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends
International Journal of Environmental Research and Public Health Review Exploring the Emerging Domain of Research on Video Game Live Streaming in Web of Science: State of the Art, Changes and Trends Luis Javier Cabeza-Ramírez * , Fernando J. Fuentes-García and Guzmán A. Muñoz-Fernandez Faculty of Law, Business and Economic Sciences, University of Córdoba, Puerta Nueva s/n, 14071 Córdoba, Spain; [email protected] (F.J.F.-G.); [email protected] (G.A.M.-F.) * Correspondence: [email protected]; Tel.: +34-957-212-688 Abstract: In recent years, interest in video game live streaming services has increased as a new communication instrument, social network, source of leisure, and entertainment platform for millions of users. The rise in this type of service has been accompanied by an increase in research on these platforms. As an emerging domain of research focused on this novel phenomenon takes shape, it is necessary to delve into its nature and antecedents. The main objective of this research is to provide a comprehensive reference that allows future analyses to be addressed with greater rigor and theoretical depth. In this work, we developed a meta-review of the literature supported by a bibliometric performance and network analysis (BPNA). We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol to obtain a representative sample of 111 published documents since 2012 and indexed in the Web of Science. Additionally, we exposed the Citation: Cabeza-Ramírez, L.J.; main research topics developed to date, which allowed us to detect future research challenges and Fuentes-García, F.J.; trends. -
Is Amazon the Next Google?
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Budzinski, Oliver; Köhler, Karoline Henrike Working Paper Is Amazon the next Google? Ilmenau Economics Discussion Papers, No. 97 Provided in Cooperation with: Ilmenau University of Technology, Institute of Economics Suggested Citation: Budzinski, Oliver; Köhler, Karoline Henrike (2015) : Is Amazon the next Google?, Ilmenau Economics Discussion Papers, No. 97, Technische Universität Ilmenau, Institut für Volkswirtschaftslehre, Ilmenau This Version is available at: http://hdl.handle.net/10419/142322 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially -
AWS Certified Developer – Associate (DVA-C01) Sample Exam Questions
AWS Certified Developer – Associate (DVA-C01) Sample Exam Questions 1) A company is migrating a legacy application to Amazon EC2. The application uses a user name and password stored in the source code to connect to a MySQL database. The database will be migrated to an Amazon RDS for MySQL DB instance. As part of the migration, the company wants to implement a secure way to store and automatically rotate the database credentials. Which approach meets these requirements? A) Store the database credentials in environment variables in an Amazon Machine Image (AMI). Rotate the credentials by replacing the AMI. B) Store the database credentials in AWS Systems Manager Parameter Store. Configure Parameter Store to automatically rotate the credentials. C) Store the database credentials in environment variables on the EC2 instances. Rotate the credentials by relaunching the EC2 instances. D) Store the database credentials in AWS Secrets Manager. Configure Secrets Manager to automatically rotate the credentials. 2) A Developer is designing a web application that allows the users to post comments and receive near- real-time feedback. Which architectures meet these requirements? (Select TWO.) A) Create an AWS AppSync schema and corresponding APIs. Use an Amazon DynamoDB table as the data store. B) Create a WebSocket API in Amazon API Gateway. Use an AWS Lambda function as the backend and an Amazon DynamoDB table as the data store. C) Create an AWS Elastic Beanstalk application backed by an Amazon RDS database. Configure the application to allow long-lived TCP/IP sockets. D) Create a GraphQL endpoint in Amazon API Gateway. Use an Amazon DynamoDB table as the data store.