{"id":8,"date":"2019-12-27T11:05:57","date_gmt":"2019-12-27T11:05:57","guid":{"rendered":"https:\/\/arms10.org\/android\/?p=8"},"modified":"2020-01-27T06:45:58","modified_gmt":"2020-01-27T06:45:58","slug":"android-applications-categorization","status":"publish","type":"post","link":"https:\/\/arms10.org\/android\/android-applications-categorization\/","title":{"rendered":"Android Applications Categorization"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\"><a href=\"https:\/\/codeshoppy.com\/android-projects-titles-ieee.html\">Android Applications Categorization<\/a><\/h2>\n\n\n\n<h2 class=\"wp-block-heading\"><a href=\"https:\/\/codeshoppy.com\/android-projects-titles-ieee.html\">android projects titles topics ideas<\/a><\/h2>\n\n\n\n<p> With  the  development  of  Mobile  Internet,  the  global  mobile devices market has exploded in the past several years. Meanwhile,  Android  is  the  most  popular  mobile  platform,  holding nearly 82.8% of the global smartphone market share [1].   Mobile   Internet   brings   convenience   to   our   life.   Nevertheless,  it  brings  a  lot  of  negative  impacts  to  our  life.  The  number  of  malicious  software  on  mobile  devices  is  growing  and  Android  is  the  most  affected  mobile  platform.  According  to  2015  MOBILE  THREAT  REPORT,  97%  of  malware  application  target  to  Android.  In  order  to  mitigate  the  threats  on  Android  mobile  devices,  machine  learning  techniques  have  been  widely  used.   <a href=\"https:\/\/codeshoppy.com\/android-projects-titles-ieee.html\">https:\/\/codeshoppy.com\/android-projects-titles-ieee.html<\/a>  According  to  whether  to  run   the   application   during   the   detection   process,   the   detection methods are divided into two kinds: static detection [2],  [3],  [4]  and  dynamic  detection  [5],  [6].  Experiments  show  that  when  applying  machine  leaning  technology  to  detect  malicious  software,  adding  the  application  category  feature   can   significantly   improve   the   performance   and   accuracy  of  the  detection  [7].  <\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/codeshoppy.com\/android-projects-titles-ieee.html\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"536\" src=\"https:\/\/arms10.org\/android\/wp-content\/uploads\/2019\/12\/Untitled-design1-1024x536.png\" alt=\"android projects titles topics ideas\" class=\"wp-image-9\" srcset=\"https:\/\/arms10.org\/android\/wp-content\/uploads\/2019\/12\/Untitled-design1-1024x536.png 1024w, https:\/\/arms10.org\/android\/wp-content\/uploads\/2019\/12\/Untitled-design1-300x157.png 300w, https:\/\/arms10.org\/android\/wp-content\/uploads\/2019\/12\/Untitled-design1-768x402.png 768w, https:\/\/arms10.org\/android\/wp-content\/uploads\/2019\/12\/Untitled-design1.png 1200w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<p>Thus,  application  category  is  important for android malware detection. However,      when      application      publishers      publish      application  to  the  Android  application  market,  they  need  to  manually  select  the  category  and  they  are  more  inclined  to  choose the category in the front row where you can see (e.g., if  tools  is  in  font  of  weather  on  the  website,  the  publisher  may  choose  tools  even  though  the  application  is  belong  to  weather).  Besides,  it\u2019s  difficult  for  application  publishers  to  distinguish  the  difference  between  different  categories  for  choosing  the  most  appropriate  category.  More  importantly,  the  malware  application  publisher  may  randomly  choose  application category to evade the detection of the application market.  <a href=\"https:\/\/codeshoppy.com\/android-projects-titles-ieee.html\">android projects titles topics ideas<\/a> Therefore,   an   approach   that   can   automatically   categorize  different  types  of  applications  can  be  helpful  for  both organizing the Android Market and detecting malicious applications.      In  [9]  Shabtai  Asaf  et  al.  firstly  used  the  data  mining  method  to  categorize  Android  applications.  They  extracted  over  2200  features  from  Java  byte-code  and  XML-files  of  Android apk, and they selected features using three selection methods:  Information  Gain,  Fisher  Score  and  Chi-Square.  They  obtained  89%  of  accuracy  for  classifying  applications  into only 2 categories: tools or games. Their limitation is that they  just  simply  collected  all  the  static  features  from  the  application  but  failed  to  conduct  in-depth  analysis  to  those  features. Besides, the dataset they used is very limited &#8212; only contains 2 categories applications.   In  [10]  Borja  Sanz  et  al.  proposed  a  new  method  to  classify  Android  applications  into  several  categories.  They  extracted   features   both   from   Android   Market   and   the   application itself. Their main contribution is to apply the data collected  from  Android  Market  into  Android  classification.  However,    they    use    the    permissions    declared    in    the    manifest.xml  rather  than  the  permissions  actual  used  in  the  application. Most applications have the phenomenon of over-claim  of  permissions  [12]  &#8211;  the  permissions  declared  in  the  manifest.xml  file  are  not  actually  used  in  code.  Therefore,  the  permissions  declared  in  manifest.xml  can\u2019t  completely  reflect the real characteristics of the application. Given  this  background,  we  present  a  new  methodbased  on  Bayesian  classification,  which  utilizes  several  features  extracted from Android Market and the application itself for classifying Android applications into several categories. The features we used include permissions, strings and description of  the  application  in  Android  Market.  Different  from  earlier  works on Android categorization that rely on the permissions declared  in  Android  manifest.xml  [10],  our  approach  uses  the  actual  used  permissions  which  are  extracted  by  static  analyzing  APIs  called  by  the  application.  Compared  with  previous   work   [9],   [10],   we   take   the   category   of   an   application  into  consideration  which  is  determined  by  the  app\u2019s  functions.  Thus,  we  made  an  in-depth  analysis  of  the  string  contained  in  application,  and  then  extract  the  strings   that  can  reflect  its  function  as  the  string  features,  removing  irrelevant  string  features,  improving  the  accuracy  of  the  classification. In   summary,   the   main   contributions   of   this   paper   different  from  existing  related  works  in  the  literature  are  as  follows: \u2022Through    analyzing    the    APIs    called    by    the    application,    we    extracted    the    actually    used    permissions,   avoiding   the   error   caused   by   the   traditional use of the declared permissions. \u2022Through    analyzing    and    observing    the    usage    characteristics  of  the  strings  in  the  applications,  we  extracted the string which can reflect the application functions as the strings feature target-oriented. \u2022To build the model, we collected 13005 applications, which have been classified into 18 categories. As far as   we   know,   compared   with   previous   Android   categorization  experiments,  ours  has  the  greatest  number  and  the  most  comprehensive  categories  of  the datasets. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Android Applications Categorization android projects titles topics ideas With the development of Mobile Internet, the global mobile devices market has exploded in the past several years. Meanwhile, Android is the most popular mobile platform, holding nearly 82.8% of the global smartphone market share [1]. Mobile Internet brings convenience to our life. Nevertheless, it brings a&hellip; <a class=\"more-link\" href=\"https:\/\/arms10.org\/android\/android-applications-categorization\/\">Continue reading <span class=\"screen-reader-text\">Android Applications Categorization<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_joinchat":[]},"categories":[220,71,128,140,306],"tags":[202,316,296,303,304,311,319],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Android App Ideas - Android Applications Categorization - Arms10 - Android<\/title>\n<meta name=\"description\" content=\"Android App Ideas - Android Applications Categorization - Download abstract and Buy source code sonline for android PHP Project ideas 2020 - Arms10 - Android\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/arms10.org\/android\/android-applications-categorization\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Android App Ideas - 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