FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2947534985> ?p ?o ?g. }

• W2947534985 endingPage "218" @default.
• W2947534985 startingPage "209" @default.
• W2947534985 abstract "Android-based smartphones are gaining popularity, due to its cost efficiency and various applications. These smartphones provide the full experience of a computing device to its user, and usually ends up being used as a personal computer. Since the Android operating system is open-source software, many contributors are adding to its development to make the interface more attractive and tweaking the performance. In order to gain more popularity, many refined versions are being offered to customers, whose feedback will enable it to be made even more powerful and user-friendly. However, this has attracted many malicious code-writers to gain anonymous access to the user’s private data. Moreover, the malware causes an increase of resource consumption. To prevent this, various techniques are currently being used that include static analysis-based detection and dynamic analysis-based detection. But, due to the enhancement in Android malware code-writing techniques, some of these techniques are getting overwhelmed. Therefore, there is a need for an effective Android malware detection approach for which experimental studies were conducted in the present work using the static features of the Android applications such as Standard Permissions with Application Programming Interface (API) calls, Non-standard Permissions with API-calls, API-calls with Standard and Nonstandard Permissions. To select the prominent features, Feature Selection Techniques (FSTs) such as the BI-Normal Separation (BNS), Mutual Information (MI), Relevancy Score (RS), and the Kullback-Leibler (KL) were employed and their effectiveness was measured using the Linear-Support Vector Machine (L-SVM) classifier. It was observed that this classifier achieved Android malware detection accuracy of 99.6% for the combined features as recommended by the BI-Normal Separation FST." @default.
• W2947534985 created "2019-06-07" @default.
• W2947534985 creator A5002860418 @default.
• W2947534985 creator A5054016512 @default.
• W2947534985 creator A5056898148 @default.
• W2947534985 date "2019-05-30" @default.
• W2947534985 modified "2023-09-23" @default.
• W2947534985 title "Experimental analysis of Android malware detection based on combinations of permissions and API-calls" @default.
• W2947534985 cites W130607548 @default.
• W2947534985 cites W1616720564 @default.
• W2947534985 cites W2002278076 @default.
• W2947534985 cites W2002478203 @default.
• W2947534985 cites W2008056655 @default.
• W2947534985 cites W2016871980 @default.
• W2947534985 cites W2060579268 @default.
• W2947534985 cites W2074402628 @default.
• W2947534985 cites W2085301524 @default.
• W2947534985 cites W2149772057 @default.
• W2947534985 cites W2167003418 @default.
• W2947534985 cites W2397550134 @default.
• W2947534985 cites W2507113366 @default.
• W2947534985 cites W2508108853 @default.
• W2947534985 cites W2519507103 @default.
• W2947534985 cites W2535790507 @default.
• W2947534985 cites W2536311873 @default.
• W2947534985 cites W2551095084 @default.
• W2947534985 cites W2591102410 @default.
• W2947534985 cites W2772660489 @default.
• W2947534985 cites W2792736988 @default.
• W2947534985 doi "https://doi.org/10.1007/s11416-019-00332-z" @default.
• W2947534985 hasPublicationYear "2019" @default.
• W2947534985 type Work @default.
• W2947534985 sameAs 2947534985 @default.
• W2947534985 citedByCount "22" @default.
• W2947534985 countsByYear W29475349852020 @default.
• W2947534985 countsByYear W29475349852021 @default.
• W2947534985 countsByYear W29475349852022 @default.
• W2947534985 crossrefType "journal-article" @default.
• W2947534985 hasAuthorship W2947534985A5002860418 @default.
• W2947534985 hasAuthorship W2947534985A5054016512 @default.
• W2947534985 hasAuthorship W2947534985A5056898148 @default.
• W2947534985 hasConcept C111919701 @default.
• W2947534985 hasConcept C186967261 @default.
• W2947534985 hasConcept C199360897 @default.
• W2947534985 hasConcept C2779818221 @default.
• W2947534985 hasConcept C2989133298 @default.
• W2947534985 hasConcept C41008148 @default.
• W2947534985 hasConcept C541664917 @default.
• W2947534985 hasConcept C548217200 @default.
• W2947534985 hasConcept C557433098 @default.
• W2947534985 hasConcept C97686452 @default.
• W2947534985 hasConcept C99613125 @default.
• W2947534985 hasConceptScore W2947534985C111919701 @default.
• W2947534985 hasConceptScore W2947534985C186967261 @default.
• W2947534985 hasConceptScore W2947534985C199360897 @default.
• W2947534985 hasConceptScore W2947534985C2779818221 @default.
• W2947534985 hasConceptScore W2947534985C2989133298 @default.
• W2947534985 hasConceptScore W2947534985C41008148 @default.
• W2947534985 hasConceptScore W2947534985C541664917 @default.
• W2947534985 hasConceptScore W2947534985C548217200 @default.
• W2947534985 hasConceptScore W2947534985C557433098 @default.
• W2947534985 hasConceptScore W2947534985C97686452 @default.
• W2947534985 hasConceptScore W2947534985C99613125 @default.
• W2947534985 hasIssue "3" @default.
• W2947534985 hasLocation W29475349851 @default.
• W2947534985 hasOpenAccess W2947534985 @default.
• W2947534985 hasPrimaryLocation W29475349851 @default.
• W2947534985 hasRelatedWork W2286416179 @default.
• W2947534985 hasRelatedWork W2559797975 @default.
• W2947534985 hasRelatedWork W2587046957 @default.
• W2947534985 hasRelatedWork W2947534985 @default.
• W2947534985 hasRelatedWork W2955731880 @default.
• W2947534985 hasRelatedWork W2964899650 @default.
• W2947534985 hasRelatedWork W3022728237 @default.
• W2947534985 hasRelatedWork W3049758233 @default.
• W2947534985 hasRelatedWork W4213452160 @default.
• W2947534985 hasRelatedWork W4385749679 @default.
• W2947534985 hasVolume "15" @default.
• W2947534985 isParatext "false" @default.
• W2947534985 isRetracted "false" @default.
• W2947534985 magId "2947534985" @default.
• W2947534985 workType "article" @default.