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Efficient and scalable mapping of native mobile applications and of complex rich internet applications for automated security testing

Efficient and scalable mapping of native mobile applications and of complex rich internet applications for automated security testing
本机移动应用程序和复杂的富互联网应用程序的高效且可扩展的映射,用于自动化安全测试
批准号:
445678-2012
负责人:
Jourdan, GuyVincent
金额:
$4.95万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
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英文摘要
The ability to "crawl" Web sites and Web applications is at the core of the success of the Web. Crawling is necessary to index, and thus to search. It is also a necessary step to automate tasks such as testing and the assessment of security or usability. With the rise of "Rich Internet Applications" (RIA), where the client side communicates asynchronously with the server, and updates itself partially as needed, there is a tremendous gain in end-user experience. A RIA "feels" like a desktop application. But we have lost our ability to easily crawl Web sites, since it is not anymore simply a matter of following each hyperlink.
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Cyberattacks Countermeasures and Prevention
  • 批准号:
    539938-2019
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $14.42万
  • 财政年份:
    2021
  • 负责人:
    Jourdan, GuyVincent
  • 依托单位:
Creating and Using Models for Mobile and Rich Internet Applications
  • 批准号:
    RGPIN-2015-05744
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2021
  • 负责人:
    Jourdan, GuyVincent
  • 依托单位:
Cyberattacks Countermeasures and Prevention
  • 批准号:
    539938-2019
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $14.42万
  • 财政年份:
    2020
  • 负责人:
    Jourdan, GuyVincent
  • 依托单位:
Creating and Using Models for Mobile and Rich Internet Applications
  • 批准号:
    RGPIN-2015-05744
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.31万
  • 财政年份:
    2020
  • 负责人:
    Jourdan, GuyVincent
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis