{"id":1634,"date":"2016-12-22T01:26:17","date_gmt":"2016-12-22T01:26:17","guid":{"rendered":"https:\/\/www.inforsec.org\/wp\/?p=1634"},"modified":"2017-01-03T01:46:36","modified_gmt":"2017-01-03T01:46:36","slug":"%e7%bd%91%e5%ae%89%e5%9b%bd%e9%99%85%e8%ae%ba%e5%9d%9binforsec2016%e5%b9%b4%e5%b9%b4%e4%bc%9a%e8%ae%ae%e7%a8%8b","status":"publish","type":"post","link":"http:\/\/202.112.238.40\/wp\/?p=1634","title":{"rendered":"\u7f51\u5b89\u56fd\u9645\u8bba\u575bInForSec2016\u5e74\u5e74\u4f1a\u8bae\u7a0b"},"content":{"rendered":"

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\u65f6\u95f4\uff1a2016\u5e7412\u670830\u65e5\uff08\u5468\u4e94\uff0913:30-18:30<\/strong><\/p>\n

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\u6f14\u8bb2<\/b><\/strong>\u5609\u5bbe\u53ca\u5185\u5bb9\u6458\u8981<\/b><\/strong><\/p>\n

1\u3001\u62a5\u544a\u9898\u76ee\uff1a<\/b><\/strong>\u7f51\u7edc\u5b89\u5168\u653b\u9632\uff1a\u4eba\u5de5\u667a\u80fd\u4f1a\u662f\u4e0b\u4e00\u4e2a\u7ec8\u7ed3\u8005\uff1f<\/b><\/strong>
\nTopic:\u00a0 The Hype and Reality of AI in Cyber Security<\/strong><\/p>\n

\u6f14\u8bb2<\/b><\/strong>\u4eba<\/b><\/strong>\uff1a\u674e\u5eb7\u00a0\u7f8e\u56fd\u4e54\u6cbb\u4e9a\u5927\u5b66\u6559\u6388<\/p>\n

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\u5185\u5bb9<\/b><\/strong>\u6458\u8981<\/b><\/strong>\uff1a<\/b><\/strong><\/p>\n

The recent CTF competitions (Cyber Grand Challenge and DEFCON CTF) among machines and between humans and machines have brought a hype of applying artificial intelligence in cyber security.\u00a0 As a CGC finalist, the presenter has been asked numerous time about his team\u2019s approach of applying artificial intelligence in analyzing binaries and vulnerability discovery.\u00a0 In this talk, he will reveal the related automation techniques used in binary analysis as a response to those questions.\u00a0 To his knowledge, most of CGC finalist adopted a similar approach with a combination of smart fuzzing and symbolic execution.\u00a0 The presenter will describe the challenged faced by different vulnerability discovery techniques, with emphases on coverage based fuzzing (AFL) and dynamic symbolic analysis (S2E).\u00a0 He will also cover his recent effort of using binary transformation techniques to improve fuzzing and binary analysis efficiency.<\/p>\n

\u6f14\u8bb2<\/b><\/strong>\u4eba\u7b80\u4ecb<\/b><\/strong>\uff1a<\/b><\/strong><\/p>\n

Kang Li is currently a Professor of Computer Science at the University of Georgia, where he leads the Cyber Security research cluster. Dr. Li received his B.S. degree in computer science from Tsinghua University, and he graduated with his Ph.D in computer science and engineering from Oregon Graduate Institute at Portland, Oregon. He worked as a research scientist at the College of Computing of Georgia Tech before joining University of Georgia. His research interests are in the areas of computer security and operating systems. His current research topics include virtualization security and bootloader firmware security. Dr. Kang Li has also founded multiple CTF security teams, including Disekt, and SecDawg, which play various CTF competitions around the world.<\/p>\n

2\u3001\u62a5\u544a\u9898\u76ee\uff1a<\/b><\/strong> \u7f51\u5740\u5b89\u5168\u4e0e\u6df1\u5ea6\u5b66\u4e60<\/b><\/strong><\/p>\n

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\n\u5185\u5bb9\u6458\u8981\uff1a<\/p>\n

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6\u3001\u62a5\u544a\u9898\u76ee\uff1a<\/b><\/strong>\u5982\u4f55<\/b><\/strong>\u66f4\u597d\u5730\u5171\u5efa<\/b><\/strong>I<\/b><\/strong>nForSec<\/b><\/strong>\u793e<\/b><\/strong>\u533a<\/b><\/strong><\/p>\n

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