Log in
Language:

MERAL Myanmar Education Research and Learning Portal

  • Top
  • Universities
  • Ranking


Index Link

Index Tree

  • RootNode
    • Co-operative College, Mandalay
    • Cooperative College, Phaunggyi
    • Co-operative University, Sagaing
    • Co-operative University, Thanlyin
    • Dagon University
    • Kyaukse University
    • Laquarware Technological college
    • Mandalay Technological University
    • Mandalay University of Distance Education
    • Mandalay University of Foreign Languages
    • Maubin University
    • Mawlamyine University
    • Meiktila University
    • Mohnyin University
    • Myanmar Institute of Information Technology
    • Myanmar Maritime University
    • National Management Degree College
    • Naypyitaw State Academy
    • Pathein University
    • Sagaing University
    • Sagaing University of Education
    • Taunggyi University
    • Technological University, Hmawbi
    • Technological University (Kyaukse)
    • Technological University Mandalay
    • University of Computer Studies, Mandalay
    • University of Computer Studies Maubin
    • University of Computer Studies, Meikhtila
    • University of Computer Studies Pathein
    • University of Computer Studies, Taungoo
    • University of Computer Studies, Yangon
    • University of Dental Medicine Mandalay
    • University of Dental Medicine, Yangon
    • University of Information Technology
    • University of Mandalay
    • University of Medicine 1
    • University of Medicine 2
    • University of Medicine Mandalay
    • University of Myitkyina
    • University of Public Health, Yangon
    • University of Veterinary Science
    • University of Yangon
    • West Yangon University
    • Yadanabon University
    • Yangon Technological University
    • Yangon University of Distance Education
    • Yangon University of Economics
    • Yangon University of Education
    • Yangon University of Foreign Languages
    • Yezin Agricultural University
    • New Index

Please input email address.

WEKO

One fine body…

WEKO

One fine body…

Item

{"_buckets": {"deposit": "bb9913df-4d3d-4db2-a2c3-013f7967803f"}, "_deposit": {"id": "3459", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3459"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3459", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Analysis on Malware Detection with Multi Classifiers on M0Droid and DroidScreening Datasets", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "The number of applications for smart mobiledevices is steadily growing with the continuousincrease in the utilization of these devices. theInstallation of malicious applications on smartdevices often arises the security vulnerabilities suchas seizure of personal information or the use of smartdevices in accordance with different purposes bycyber criminals. Therefore, the number of studies inorder to identify malware for mobile platforms hasincreased in recent years. In this study, permissionbasedmodel is used to detect the maliciousapplications on Android which is one of the mostwidely used mobile operating system. M0Droid andDroidScreening data sets have been analyzed usingthe Android application package files andpermission-based features extracted from these files.In our work, permission-based model which appliedpreviously across different data sets investigated toM0Droid and DroidScreening datasets and theexperimental results has been expanded. Whileobtaining results, feature set analyzed using differentclassification techniques. The results show thatpermission-based model is successful on M0Droidand DroidScreening data sets and Random Forestsoutperforms another method. When compared toM0Droid system model, it is obtained much bet terconclusions depend on success rate. Our approachprovides a method for automated static code analysisand malware detection with high accuracy andreduces smartphone malware analysis time."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Mobile Malware Detection"}, {"interim": "Permission data"}, {"interim": "Classification techniques"}, {"interim": "M0Droid"}, {"interim": "DroidScreening"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-23"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ICCA 2019 Proceedings Book-pages-203-210.pdf", "filesize": [{"value": "185 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 185000.0, "url": {"url": "https://meral.edu.mm/record/3459/files/ICCA 2019 Proceedings Book-pages-203-210.pdf"}, "version_id": "0560a0d1-69ad-4fd9-8380-a3a457a2fe4a"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Seventeenth International Conference on Computer Applications(ICCA 2019)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Tun, Kyaw Naing"}, {"subitem_authors_fullname": "Aye, Zin May"}, {"subitem_authors_fullname": "Khaing, Kyaw Thet"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-02-27"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1207"}, "item_title": "Analysis on Malware Detection with Multi Classifiers on M0Droid and DroidScreening Datasets", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003459", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-23"}, "publish_date": "2019-07-23", "publish_status": "0", "recid": "3459", "relation": {}, "relation_version_is_last": true, "title": ["Analysis on Malware Detection with Multi Classifiers on M0Droid and DroidScreening Datasets"], "weko_shared_id": -1}
  1. University of Computer Studies, Yangon
  2. Conferences

Analysis on Malware Detection with Multi Classifiers on M0Droid and DroidScreening Datasets

http://hdl.handle.net/20.500.12678/0000003459
http://hdl.handle.net/20.500.12678/0000003459
e92fef5b-666c-45e5-ad10-6e17ac629551
bb9913df-4d3d-4db2-a2c3-013f7967803f
None
Preview
Name / File License Actions
ICCA ICCA 2019 Proceedings Book-pages-203-210.pdf (185 Kb)
Publication type
Article
Upload type
Publication
Title
Title Analysis on Malware Detection with Multi Classifiers on M0Droid and DroidScreening Datasets
Language en
Publication date 2019-02-27
Authors
Tun, Kyaw Naing
Aye, Zin May
Khaing, Kyaw Thet
Description
The number of applications for smart mobiledevices is steadily growing with the continuousincrease in the utilization of these devices. theInstallation of malicious applications on smartdevices often arises the security vulnerabilities suchas seizure of personal information or the use of smartdevices in accordance with different purposes bycyber criminals. Therefore, the number of studies inorder to identify malware for mobile platforms hasincreased in recent years. In this study, permissionbasedmodel is used to detect the maliciousapplications on Android which is one of the mostwidely used mobile operating system. M0Droid andDroidScreening data sets have been analyzed usingthe Android application package files andpermission-based features extracted from these files.In our work, permission-based model which appliedpreviously across different data sets investigated toM0Droid and DroidScreening datasets and theexperimental results has been expanded. Whileobtaining results, feature set analyzed using differentclassification techniques. The results show thatpermission-based model is successful on M0Droidand DroidScreening data sets and Random Forestsoutperforms another method. When compared toM0Droid system model, it is obtained much bet terconclusions depend on success rate. Our approachprovides a method for automated static code analysisand malware detection with high accuracy andreduces smartphone malware analysis time.
Keywords
Mobile Malware Detection, Permission data, Classification techniques, M0Droid, DroidScreening
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1207
Journal articles
Seventeenth International Conference on Computer Applications(ICCA 2019)
Conference papers
Books/reports/chapters
Thesis/dissertations
Back
0
0
views
downloads
See details
Views Downloads

Versions

Ver.1 2020-09-01 12:58:46.341605
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats
  • JSON

Confirm


Back to MERAL


Back to MERAL