Search Results - (( copy detection ((a algorithm) OR (new algorithm)) ) OR ( botnet detection based algorithm ))

Refine Results
  1. 1
  2. 2
  3. 3
  4. 4

    Systematic Analysis on Mobile Botnet Detection Techniques Using Genetic Algorithm by Rahman, MZA, Madihah Mohd Saudi

    Published 2024
    “…A case study was carried out to reverse engineering the mobile botnet codes. Based on the findings, this mobile botnet has successfully posed itself as a fake anti-virus and has the capability to steal important data such as username and password from the Android-based devices. …”
    Proceedings Paper
  5. 5

    ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

    Published 2017
    “…Due to the fast modifications in the technologies used by malicious application (app) developers, there is an urgent need for more advanced techniques for Android botnet detection. In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
    Get full text
    Get full text
    Article
  6. 6
  7. 7

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…This new classification can be used as the input for mobile botnet detection for future work, especially for financial matters.…”
    Proceedings Paper
  8. 8
  9. 9
  10. 10

    An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

    Published 2019
    “…In order to detect botnet attacks which causes immense chaos and problems to smartphones, first the Android botnet need to be analysed. …”
    Get full text
    Get full text
    Thesis
  11. 11
  12. 12
  13. 13
  14. 14

    Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

    Published 2019
    “…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani by Seyed Asadollah, Abdiesfandani

    Published 2016
    “…We then develop a new algorithm to address the summarizing strategies identification problem. …”
    Get full text
    Get full text
    Thesis
  17. 17

    A keypoint based copy-move forgery detection and localization in digital images / Somayeh Sadeghi by Somayeh, Sadeghi

    Published 2015
    “…A copy-move forgery detector should be able to detect forgery in a reasonable amount of time. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Region duplication forgery detection technique based on keypoint matching / Diaa Mohammed Hassan Uliyan by Diaa , Mohammed Hassan Uliyan

    Published 2016
    “…The proposed method have adopted statistical region merging (SRM) algorithm to detect small regions, and then Harris interest points are localized in angular radial partition (ARP) of a circular region which are invariant to rotation and scale transformations. …”
    Get full text
    Get full text
    Thesis
  19. 19

    A framework of enhanced authentication for PDF textual documents using Zigzag-LSB embedding algorithm by Nur Alya Afikah, Usop

    Published 2024
    “…Similar processes are used in the generation and embedding phases of a watermark. The effectiveness of the algorithm has been established since it uses an image-based approach after conversion between document and images with a numbering pattern that is fragile to deletion, replacement, insertion, combine, and copy attack. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Designing a New Model for Trojan Horse Detection Using Sequential Minimal Optimization by Saudi, MM, Abuzaid, AM, Taib, BM, Abdullah, ZH

    Published 2024
    “…Based on the experiment conducted, the Sequential Minimal Optimization (SMO) algorithm has outperformed other machine learning algorithms with 98.2 % of true positive rate and with 1.7 % of false positive rate.…”
    Proceedings Paper