[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121814-en":3,"doc-seo-121814-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121814,1649267921044,"Ava Thompson","https://us-avatar.wpscdn.com/avatar/1800007509477c92dfb?_k=1782875107921204101",8,"Research & Report","OSN-Tagging Scheme and Its Steganalysis Realizing Using Machine Learning Model","Steganography hides information in digital objects, while steganalysis aims to detect such hidden content despite visual and statistical analyses. This work presents a machine learning approach for steganalysis using an SVM (Support Vector Machine) classifier. The evaluation is performed on an OSN (Online Social Network)-Tagging scheme, using Facebook as the selected OSN. The study measures classification accuracy of steganographic algorithms in percentage using the proposed model.","OSN-Tagging Scheme and Its Steganalysis Realizing Using Machine  \nLearning Model  \nLekshmi R.Nair  \nComputer Science and Engineering, College of Engineering Cherthala, INDIA  \nCorresponding Author: [lekshmi.r.nair@cectl.ac.in](lekshmi.r.nair@cectl.ac.in)  \nReceived: 15-03-2023 Revised: 27-03-2023 Accepted: 29-04-2023  \nABSTRACT  \nSteganography is a type of art and steganalysis is that art fining.In this work we propose a machine learning model for steganaysis. An SVM(Support Vector Machine)– Classification model. Testing the model with the help of OSN(Online Social Network)-Tagging scheme. Facebook was selected from all amoung the OSN for OSN-Tagging. Machine classify the steg-algorithm’s accuracy in percentage.  \nKeywords— OSN-Tagging, Steganalysis, SVM, AES, Bit Pattern, Useability, Peek Threshold Value  \nI. INTRODUCTION  \nOnline social networks are dedicated websites that enable users to communicate with each other by posting information, comments, messages, images, etc.  \n[11] . The popularity of OSNs such as Facebook, Twitter, Google+,[etc.is](etc.is) continuously growing, with Facebook the most popular OSN based on the number of active users (active users are users who have logged in to Facebook in the last 30 days) [12] . In the third quarter of 2012, the number of active Facebook users surpassed 1 billion, while as of the third quarter of 2016 the number of active Facebook users have grown to 1.79 billion [13] .  \nSteganography is the practice or art of hiding information in digital object [14], with image being the most popular choice of cover object [15] . Steganography’s main objectives are undetectavility (resistance against both visual as well as statistical analysis) [16] . Although all three these objectives are desirable, most applications can only focus on one or two of these objectives and a tradeoff is usually necessary. The main focus of the OSNTagging scheme that is on robustness, specifically against the types of image modifications that are performed by OSNs, and resist from statistical analysis (like entropy) that are analyzed by this machine learning methodology.  \nFigure 1: Classification of information hiding  \nFig 1 represents the classification of information hiding. It can be mainly four type which are convert channel, steganography, anonymity and copyright marking. Watermarking is under copyright marking.  \nII. LITRATURE REVIEW  \nA. Advanced Encryption Standard(AES)  \nIt is a symmetric block cipher. A number of AES parameters depend on the key length. The AES standard states that the algorithm can only accept a block size of 128 bits and a choice of three keys-128,192,256 bits. At present the most common key size likely to be used is the 128-bit key then the number of round is 10.  \nB. Support Vector Machine(SVM)  \nSupport Vector Machine (SVM) is one of the most popular Machine Learning Classifier. It falls under the category of Supervised learning algorithms and uses the concept of Margin to classify between classes. It gives better accuracy than K-Nearest Niebour(KNN), Decision Trees and Naive Bayes Classifier and hence is quite useful.  \n 182  This work is licensed under Creative Commons Attribution 4.0 International License.  \nIII. RELATED WORK  \nFigure 2: Classification of steganography  \nA. Mp3stego Steganalysis  \nMp3stego is an open source data hiding algorithm that is built on top of 8 Hz encoder [6] . It means that files embedded with mp3stego will shares some characteristics with 8 Hz encoder. The algorithm embeds bits of message as the parity of part2_3_length field of SI. Embedding algorithm works directly on uncompressed samples of cover and embeds the message during the compression process. To that end, the algorithm adds a second criterion to inner loop of mp3 compression algorithm. Such that, not only the existing bit budget should be enough for encoding the granule, but also parity of its part2_3_length should match with bit of the message. Therefore, if parity of part2_3_length ","cbCaiuzkyVJCslGe","https://ap.wps.com/l/cbCaiuzkyVJCslGe","pdf",663532,1,6,"English","en",105,"# Introduction\n## Online social networks and information hiding\n## Objectives and OSN-Tagging scheme focus\n# Literature Review\n## AES\n## SVM\n# Related Work\n## Mp3stego Steganalysis\n## Caronni’s Tagging\n# Proposed Work\n## Dataset\n## Metrics\n## Libraries Used","[{\"question\":\"What machine learning method is used for steganalysis in the proposed work?\",\"answer\":\"The proposed work uses an SVM (Support Vector Machine) classification model to perform steganalysis.\"},{\"question\":\"How is the evaluation tied to the OSN-Tagging scheme?\",\"answer\":\"Testing uses an OSN-Tagging scheme, with Facebook selected as the OSN, to classify steganographic algorithms’ accuracy.\"},{\"question\":\"What dataset is used for training and testing?\",\"answer\":\"The work uses 50 plane images and 50 corresponding stego-images, including 50 different image types of varying sizes.\"}]","OSN-Tagging Scheme and Its Steganalysis Realizing Using Machine Learning Model | PDF",1785806998,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"osn-tagging-scheme-and-its-steganalysis-realizing-using-machine-learning-model","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/osn-tagging-scheme-and-its-steganalysis-realizing-using-machine-learning-model/121814/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What machine learning method is used for steganalysis in the proposed work?","Question",{"text":75,"@type":76},"The proposed work uses an SVM (Support Vector Machine) classification model to perform steganalysis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the evaluation tied to the OSN-Tagging scheme?",{"text":80,"@type":76},"Testing uses an OSN-Tagging scheme, with Facebook selected as the OSN, to classify steganographic algorithms’ accuracy.",{"name":82,"@type":73,"acceptedAnswer":83},"What dataset is used for training and testing?",{"text":84,"@type":76},"The work uses 50 plane images and 50 corresponding stego-images, including 50 different image types of varying sizes.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]