Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 15 of 15 for “"Android Malware"”.

  1. Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection

    An increasing variety of malware, including spyware, worms, and bots, threatens data confidentiality and system integrity on computing devices ranging from backend servers to mobile devices. To address these threats, exacerbated by dynamic network traffic patterns and growing volumes, network …

    vt Repository record for Discovery of Triggering Relations and Its Applications in Network Security and Android Malware Detection (opens in a new tab)

  2. Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)

    … Frequency (TF-IDF) as the main algorithm in Android malware detection. The TF-IDF algorithm is used to filter Android features filtered before detection process. However, IDF is unaware to the training class labels and gives incorrect weight value to some features. Therefore, the proposed …

    uthm Repository record for Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) (opens in a new tab)

  3. Developing a next-generation Mobile Security solution for Android

    The exponential growth of the Android platform in the recent years has made it a main target of cyber-criminals. As a result, the amount of malware for Android is constant and rapidly growing. This exponential growth of malware given, there is a need for new detection models designed to …

    reykjavik Repository record for Developing a next-generation Mobile Security solution for Android (opens in a new tab)

  4. Tapjacking Threats and Mitigation Techniques for Android Applications

    … type falls within the broader literature of malware, in particular for Android malware. In this direction, we propose a classification of Android malware. Then, we propose a novel technique based on Kullback-Leibler Divergence (KLD) to identify possible tapjacking behavior in applications. We …

    kennesaw Repository record for Tapjacking Threats and Mitigation Techniques for Android Applications (opens in a new tab)

  5. Efficient resolution of security-sensitive values in Android using abstract interpretation

    … calculates field values of security-relevant Android API class instances. The analysis is an important component of DroidSafe, an Android malware detection system designed to prove important properties of sensitive program behaviors before the programs appear in an application marketplace. The …

    mit Repository record for Efficient resolution of security-sensitive values in Android using abstract interpretation (opens in a new tab)

  6. Transparent and Precise Malware Analysis Using Virtualization: From Theory to Practice

    … analysis is an important technique used in malware analysis and is complementary to static analysis. Thus far, virtualization has been widely adopted for building fine-grained dynamic analysis tools and this trend is expected to continue. Unlike User/Kernel space malware analysis platforms …

    syracuse-diss Repository record for Transparent and Precise Malware Analysis Using Virtualization: From Theory to Practice (opens in a new tab)

  7. Design and implementation of robust systems for secure malware detection

    Malicious software (malware) have significantly increased in terms of number and effectiveness during the past years. Until 2006, such software were mostly used to disrupt network infrastructures or to show coders’ skills. Nowadays, malware constitute a very important source of economical profit, …

    cagliari Repository record for Design and implementation of robust systems for secure malware detection (opens in a new tab)

  8. Android behind the scenes: revealing hidden malware with AndroMEDA

    … including malicious applications such as malware and trojans. To better understand mobile malware, we introduce the concept of the User-App Agreement (UAA) — a concep- tual framework for a user consenting to and trusting specific actions an app may perform. Using UAA we examine the Android

    uiuc Repository record for Android behind the scenes: revealing hidden malware with AndroMEDA (opens in a new tab)

  9. Usable Post-Classification Visualizations for Android Collusion Detection and Inspection

    Android malware collusion is a new threat model that occurs when multiple Android apps communicate in order to execute an attack. This threat model threatens all Android users' private information and system resource security. Although recent research has made advances in collusion detection and …

    vt Repository record for Usable Post-Classification Visualizations for Android Collusion Detection and Inspection (opens in a new tab)

  10. On several problems regarding the application of opportunistic proximate links in smartphone networks

    … the distribution of unwanted content (mobile malware) over opportunistic proximate links and the supplementary problem of detecting mobile malware. Chapter 5 considers a probabilistic behavioral malware detection framework for delay-tolerant smartphone networks that are connected by …

    purdue-thes Repository record for On several problems regarding the application of opportunistic proximate links in smartphone networks (opens in a new tab)

  11. On Several Problems Regarding the Application of Opportunistic Proximate Links in Smartphone Networks

    … the distribution of unwanted content (mobile malware) over opportunistic proximate links and the supplementary problem of detecting mobile malware. Chapter 5 considers a probabilistic behavioral malware detection framework for delay-tolerant smartphone networks that are connected by …

    iupui Repository record for On Several Problems Regarding the Application of Opportunistic Proximate Links in Smartphone Networks (opens in a new tab)

  12. An Assessment of Static and Dynamic malware analysis techniques for the android platform

    … has fostered an increasing number of mobile malware attacks. The purpose of the research was to answer the following research questions: 1. What are the existing methods for analysing mobile malware? 2. How can methods for analysing mobile malware be evaluated? 3. What would comprise a …

    edithcowan Repository record for An Assessment of Static and Dynamic malware analysis techniques for the android platform (opens in a new tab)

  13. Identification of Privacy Risks for Android Users and Effective Protection Mechanisms

    … world’s most popular mobile Operating System is Android, consequently Android devices are at the center of much research which discuss their points of strengths and weaknesses. An important tool of Android smartphones is Application Programming Interface (API); it is a combination of benefits, …

    catania Repository record for Identification of Privacy Risks for Android Users and Effective Protection Mechanisms (opens in a new tab)

  14. User-Intention Based Program Analysis for Android Security

    … In this thesis, we address the problem of Android security by presenting a new quantitative program analysis framework for security vetting of Android apps. We first introduce a highly accurate proactive detection solution for detecting individual malicious apps. Our approach enforces …

    vt Repository record for User-Intention Based Program Analysis for Android Security (opens in a new tab)

  15. Artificial Intelligence for Android Stealth-Attack Detection: A Digital Forensics Approach

    Android is the most popular Operating System (OS) for mobile devices worldwide due to its low cost and open-source platform. Various apps for different services have been developed, but the incorrect management of specific data structures and code sections can lead to vulnerabilities, allowing …

    cagliari Repository record for Artificial Intelligence for Android Stealth-Attack Detection: A Digital Forensics Approach (opens in a new tab)