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Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
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Dynamic Information Flow Tracking: Taxonomy, Challenges, and Opportunities.

Kejun Chen1, Xiaolong Guo2, Qingxu Deng1

  • 1School of Computer Science and Engineering, Northeastern University, Shenyang 110016, China.

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|August 27, 2021
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Summary

Dynamic Information Flow Tracking (DIFT) enhances security by monitoring data usage and preventing attacks. This study categorizes DIFT solutions and suggests future improvements for better system security.

Keywords:
control-flow integritydata-flow analysisdata-flow integritydynamic information flow tracking

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Software Engineering

Background:

  • Dynamic Information Flow Tracking (DIFT) is crucial for monitoring data usage and preventing runtime attacks.
  • Existing DIFT techniques are vital for analyzing program performance and enhancing security.
  • Recent advancements have led to the development of various DIFT solutions.

Purpose of the Study:

  • To summarize and analyze current Dynamic Information Flow Tracking (DIFT) solutions.
  • To identify the features and limitations of existing DIFT frameworks.
  • To propose potential enhancements and future directions for DIFT.

Main Methods:

  • Literature review and analysis of existing DIFT techniques.
  • Classification of DIFT solutions into software, hardware, and co-design categories.
  • System-level analysis of DIFT frameworks and their limitations.

Main Results:

  • Current DIFT solutions are categorized into software, hardware, and co-design approaches.
  • Analysis reveals specific features and limitations within each DIFT category.
  • Limitations in current DIFT frameworks are identified from a whole-system perspective.

Conclusions:

  • DIFT is an effective technique for enhancing system security and performance.
  • A clear classification of DIFT solutions aids in understanding their capabilities and drawbacks.
  • Future research should focus on enhancing DIFT frameworks to improve overall security levels.