CRJun 9, 2021

Information flow based defensive chain for data leakage detection and prevention: a survey

arXiv:2106.04951v1
Originality Synthesis-oriented
AI Analysis

It addresses data leakage threats for users of mobile and IoT applications, but is incremental as it synthesizes existing research into a survey.

This survey tackles the problem of data leakage in mobile and IoT applications by reviewing Information Flow Control techniques across the application lifecycle, proposing a new defensive chain framework for systematic understanding.

Mobile and IoT applications have greatly enriched our daily life by providing convenient and intelligent services. However, these smart applications have been a prime target of adversaries for stealing sensitive data. It poses a crucial threat to users' identity security, financial security, or even life security. Research communities and industries have proposed many Information Flow Control (IFC) techniques for data leakage detection and prevention, including secure modeling, type system, static analysis, dynamic analysis, \textit{etc}. According to the application's development life cycle, although most attacks are conducted during the application's execution phase, data leakage vulnerabilities have been introduced since the design phase. With a focus on lifecycle protection, this survey reviews the recent representative works adopted in different phases. We propose an information flow based defensive chain, which provides a new framework to systematically understand various IFC techniques for data leakage detection and prevention in Mobile and IoT applications. In line with the phases of the application life cycle, each reviewed work is comprehensively studied in terms of technique, performance, and limitation. Research challenges and future directions are also pointed out by consideration of the integrity of the defensive chain.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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