Differential Privacy Principal Component Analysis for Support Vector Machines

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Algorithm</td><td class="align_center">Noise scale</td><td class="align_center">Privacy level</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">AG</td><td class="align_center"><span style="width: 53.0384ptpx;"><svg height="14.4435pt" id="M221" style="vertical-align:-2.2681pt" version="1.1" viewbox="-0.0498162 -12.1754 53.0384 14.4435" width="53.0384pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M699 369C699 549 575 666 407 666C186 666 23 488 23 278C23 101 145 -16 312 -16C535 -16 699 153 699 369ZM600 373C600 210 500 19 321 19C186 19 120 129 120 272C120 450 232 631 399 631C541 631 600 522 600 373Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.387,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 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270Z"></path></g></svg></span></td></tr><tr><td class="align_left">MOD-SuLQ</td><td class="align_center"><span style="width: 83.6508ptpx;"><svg height="15.184pt" id="M223" style="vertical-align:-3.5795pt" version="1.1" viewbox="-0.0498162 -11.6045 83.6508 15.184" width="83.6508pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M699 369C699 549 575 666 407 666C186 666 23 488 23 278C23 101 145 -16 312 -16C535 -16 699 153 699 369ZM600 373C600 210 500 19 321 19C186 19 120 129 120 272C120 450 232 631 399 631C541 631 600 522 600 373Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.387,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,13.885,0)"><path d="M530 686C535 705 530 712 521 712C504 712 448 684 359 674L358 648H393C437 648 439 646 429 593L400 435C372 447 345 448 332 448C286 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604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg></span></td></tr><tr><td class="align_left">DPPCA</td><td class="align_center"><span style="width: 43.0691ptpx;"><svg height="11.5564pt" id="M225" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 43.0691 11.5564" width="43.0691pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M699 369C699 549 575 666 407 666C186 666 23 488 23 278C23 101 145 -16 312 -16C535 -16 699 153 699 369ZM600 373C600 210 500 19 321 19C186 19 120 129 120 272C120 450 232 631 399 631C541 631 600 522 600 373Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.387,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,13.885,0)"><path d="M530 686C535 705 530 712 521 712C504 712 448 684 359 674L358 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<div>Display of the noise scale and privacy level.</div>

Security and Communication Networks

tab2

Table 2

Table 2: Differential Privacy Principal Component Analysis for Support Vector Machines 