LSB steganalysis using support vector regression
We describe a method of detecting the existence of messages, which are randomly scattered in the least significant bits (LSB) of both 24-bit RGB color and 8-bit grayscale images. The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image...
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| creator | Lin, E. Woertz, E. Kam, M. |
| description | We describe a method of detecting the existence of messages, which are randomly scattered in the least significant bits (LSB) of both 24-bit RGB color and 8-bit grayscale images. The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image, whose similarities and correlations change with different ratios of LSB embedding. The proposed detection scheme is based on support vector regression (SVR). It is shown that the measurement of a selected set of features forms a multidimensional feature space which allows estimation of the length of hidden messages embedded in the LSB of cover-images with high precision. |
| doi_str_mv | 10.1109/IAW.2004.1437803 |
| format | Conference Proceeding |
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The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image, whose similarities and correlations change with different ratios of LSB embedding. The proposed detection scheme is based on support vector regression (SVR). It is shown that the measurement of a selected set of features forms a multidimensional feature space which allows estimation of the length of hidden messages embedded in the LSB of cover-images with high precision.</description><identifier>ISBN: 9780780385726</identifier><identifier>ISBN: 0780385721</identifier><identifier>DOI: 10.1109/IAW.2004.1437803</identifier><language>eng</language><publisher>IEEE</publisher><subject>Cryptography ; Extraterrestrial measurements ; Gray-scale ; Histograms ; Length measurement ; Multidimensional systems ; Pixel ; Scattering ; Steganography ; Support vector machines</subject><ispartof>Proceedings from the Fifth Annual IEEE SMC Information Assurance Workshop, 2004, 2004, p.95-100</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1437803$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1437803$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lin, E.</creatorcontrib><creatorcontrib>Woertz, E.</creatorcontrib><creatorcontrib>Kam, M.</creatorcontrib><title>LSB steganalysis using support vector regression</title><title>Proceedings from the Fifth Annual IEEE SMC Information Assurance Workshop, 2004</title><addtitle>IAW</addtitle><description>We describe a method of detecting the existence of messages, which are randomly scattered in the least significant bits (LSB) of both 24-bit RGB color and 8-bit grayscale images. The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image, whose similarities and correlations change with different ratios of LSB embedding. The proposed detection scheme is based on support vector regression (SVR). It is shown that the measurement of a selected set of features forms a multidimensional feature space which allows estimation of the length of hidden messages embedded in the LSB of cover-images with high precision.</description><subject>Cryptography</subject><subject>Extraterrestrial measurements</subject><subject>Gray-scale</subject><subject>Histograms</subject><subject>Length measurement</subject><subject>Multidimensional systems</subject><subject>Pixel</subject><subject>Scattering</subject><subject>Steganography</subject><subject>Support vector machines</subject><isbn>9780780385726</isbn><isbn>0780385721</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj0tLxDAURgMiKGP3gpv8gdbcPJpmOQ4-BgouVFwOaXJbImNbcjvC_HtHnLM5Z_XBx9gtiApAuPvt-rOSQugKtLKNUBescCf_ZWOsrK9YQfQlTihnwJhrJtq3B04LDn70-yMl4gdK48DpMM9TXvgPhmXKPOOQkShN4w277P2esDh7xT6eHt83L2X7-rzdrNsygTVLKTsZGuNq6cHqqKLB0ENQug7CBUDd9bKzHTQaAVSUIgZjRIyyVxZri06t2N3_bkLE3ZzTt8_H3fmX-gVkA0Kt</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Lin, E.</creator><creator>Woertz, E.</creator><creator>Kam, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2004</creationdate><title>LSB steganalysis using support vector regression</title><author>Lin, E. ; Woertz, E. ; Kam, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-2b2c85962a174d3d5ecf1c346c09c1e4bf2b7b184e113d20dc550dd2f37e67e93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Cryptography</topic><topic>Extraterrestrial measurements</topic><topic>Gray-scale</topic><topic>Histograms</topic><topic>Length measurement</topic><topic>Multidimensional systems</topic><topic>Pixel</topic><topic>Scattering</topic><topic>Steganography</topic><topic>Support vector machines</topic><toplevel>online_resources</toplevel><creatorcontrib>Lin, E.</creatorcontrib><creatorcontrib>Woertz, E.</creatorcontrib><creatorcontrib>Kam, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lin, E.</au><au>Woertz, E.</au><au>Kam, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>LSB steganalysis using support vector regression</atitle><btitle>Proceedings from the Fifth Annual IEEE SMC Information Assurance Workshop, 2004</btitle><stitle>IAW</stitle><date>2004</date><risdate>2004</risdate><spage>95</spage><epage>100</epage><pages>95-100</pages><isbn>9780780385726</isbn><isbn>0780385721</isbn><abstract>We describe a method of detecting the existence of messages, which are randomly scattered in the least significant bits (LSB) of both 24-bit RGB color and 8-bit grayscale images. The method is based on gathering and inspecting a set of image relevant features from the pixel groups of the stego-image, whose similarities and correlations change with different ratios of LSB embedding. The proposed detection scheme is based on support vector regression (SVR). It is shown that the measurement of a selected set of features forms a multidimensional feature space which allows estimation of the length of hidden messages embedded in the LSB of cover-images with high precision.</abstract><pub>IEEE</pub><doi>10.1109/IAW.2004.1437803</doi><tpages>6</tpages></addata></record> |
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| ispartof | Proceedings from the Fifth Annual IEEE SMC Information Assurance Workshop, 2004, 2004, p.95-100 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cryptography Extraterrestrial measurements Gray-scale Histograms Length measurement Multidimensional systems Pixel Scattering Steganography Support vector machines |
| title | LSB steganalysis using support vector regression |
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