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<h1 class="post-title">
<span class="font-weight-bold">Duy Phuc</span> Pham
</h1>
<p class="desc">Threat analyst and malware researcher, PhD.</p>
</header>
<article>
<div class="profile float-right">
<img class="img-fluid z-depth-1 rounded" src="/assets/img/prof_pic.jpg">
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<div class="clearfix">
<p>My main interests: malware reverse-engineering, intelligence threats hunting, side-channel information with deep learning analysis.</p>
<ul>
<li>Malware researcher at Advanced Research Center (ARC) - <a href="https://www.trellix.com/" target="_blank">Trellix</a>
</li>
<li>PhD graduate at <a href="https://www.irisa.fr/emsec/" target="_blank">EMSEC team</a>, <a href="https://irisa.fr" target="_blank">IRISA</a> & <a href="https://inria.fr" target="_blank">INRIA</a> under supervision of <a href="http://www.annelieheuser.com/" target="_blank">Annelie Heuser</a>, <a href="https://members.loria.fr/OZendra/" target="_blank">Olivier Zendra</a>, <a href="https://www.di.ens.fr/~fouque/" target="_blank">Pierre-Alain Fouque</a>, and <a href="http://p.lanet.free.fr/pmwiki-2.2.81/" target="_blank">Jean-Louis Lanet</a>.</li>
<li>MSc of cyber-security at <a href="https://www.utwente.nl/" target="_blank">University of Twente</a> and <a href="https://www.unitn.it/" target="_blank">University of Trento</a>
</li>
<li>BA of Business Administration at <a href="https://www.hust.edu.vn/" target="_blank">Hanoi University of Science and Technology</a>
</li>
<li>Engineering degree of Mechatronics at <a href="https://www.hust.edu.vn/" target="_blank">Institut polytechnique de Hanoï</a>
</li>
<li>Founder of CTF team <a href="https://babyphd.net" target="_blank">BabyPhD</a>
</li>
</ul>
<hr>
<h2 id="awards">Awards</h2>
<ul>
<li>1st winner of Airbus security challenge, CYBER IN Toulouse 2021.</li>
<li>1st prize award of SILM Security of Software & Hardware Interfaces CTF 2019</li>
<li>Mandiant’s Fire Eye- Advanced Reverse Engineering 1,2,3,5,6,9,10 : Winning award. 2023, 2022, 2019, 2018, 2016, 2015, 2014</li>
<li>Batterii: Web penetration testing - Bug Bounty award. Oct. 2016</li>
<li>BlackHat Europe Conference: Student Scholarship. Aug. 2016</li>
<li>KTH Royal Institute of Technology, Sweden: EIT Digital’s summer school Future Cloud. Jul. 2016</li>
<li>EIT ICT School: Excellent nomination scholarship of €30.000 in Security&Privacy. Apr. 2015</li>
<li>BKAV’s Whitehat contest 08: 1st prize award on behalf of BabyPhD team. Feb. 2015</li>
<li>Hanoi University of Science and Technology Young Scientific Research : 1st prize award. Jul. 2013</li>
</ul>
<h2 id="i-amwas-a-member-of-the-following">I am/was a member of the following:</h2>
<ul>
<li>USENIX Security 2022 Artifact Evaluation Committee <a href="https://www.usenix.org/conference/usenixsecurity22/call-for-artifacts" target="_blank">2022</a>
</li>
<li>CHES Artifact Evaluation PC <a href="https://ches.iacr.org/2021/artifacts.php" target="_blank">2021</a>
</li>
<li>International Symposium on Information and Communication Technology PC <a href="https://soict.org/" target="_blank">2022</a>
</li>
<li>Quarterly security livestreaming roundtable of BabyTalk from 2020- <a href="https://www.youtube.com/watch?v=DDxRn3CNdeQ" target="_blank">3</a> <a href="https://www.youtube.com/watch?v=7gE_9P0CDUk" target="_blank">2</a> <a href="https://www.youtube.com/watch?v=rMevp_WBY88" target="_blank">1</a>
</li>
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<div class="news">
<h2>news</h2>
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<table class="table table-sm table-borderless">
<tr>
<th scope="row">Nov 12, 2023</th>
<td>
My talk record: <a href="https://youtu.be/u1LSjpD5yYw"><em>The Wolf in Sheep’s Clothing: How Cybercriminals Leverage OneNote for Stealthy Malware Delivery</em></a> at code.talks Hamburg 2023 has been published.
</td>
</tr>
<tr>
<th scope="row">Jun 23, 2022</th>
<td>
Our paper “ULTRA: Ultimate Rootkit Detection over the Air” has been accepted in <a href="https://raid2022.cs.ucy.ac.cy/index.html">RAID 2022</a> <img class="emoji" title=":sparkles:" alt=":sparkles:" src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png" height="20" width="20"> <img class="emoji" title=":smile:" alt=":smile:" src="https://github.githubassets.com/images/icons/emoji/unicode/1f604.png" height="20" width="20">.
</td>
</tr>
<tr>
<th scope="row">Aug 28, 2021</th>
<td>
Our paper “Obfuscation Revealed: Leveraging Electromagnetic Signals for Obfuscated Malware Classification” has been accepted in <a href="https://www.acsac.org/">ACSAC 2021</a>.
</td>
</tr>
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<div class="publications">
<h2>selected publications</h2>
<ol class="bibliography">
<li>
<div class="row">
<div class="col-sm-2 abbr">
</div>
<div id="10.1145/3545948.3545962" class="col-sm-8">
<div class="title">ULTRA: Ultimate Rootkit Detection over the Air</div>
<div class="author">
<em>Pham, Duy-Phuc</em>,
Marion, Damien,
and Heuser, Annelie
</div>
<div class="periodical">
<em>In 25th International Symposium on Research in Attacks, Intrusions and Defenses</em>
2022
</div>
<div class="links">
<a class="abstract btn btn-sm z-depth-0" role="button">Abs</a>
<a href="https://hal.archives-ouvertes.fr/hal-03713584/document" class="btn btn-sm z-depth-0" role="button" target="_blank">PDF</a>
<a href="https://gitlab.com/ultra-RK/ultra" class="btn btn-sm z-depth-0" role="button" target="_blank">Code</a>
</div>
<!-- Hidden abstract block -->
<div class="abstract hidden">
<p>Rootkits are the most challenging malware threats against server and desktop systems. They are created by highly skilled actors and are deployed in advanced persistent threat attacks. Lately and even in the future, rootkits will become a real threat to billions of IoT devices. Existing malware detection techniques based on static or dynamic analysis face major shortcomings, which become more apparent when it is necessary to detect threats on IoT devices. In this paper, we propose the ULTRA framework, which can detect rootkits effectively and efficiently by operating outside of the “box” (literary device) with no resource requirement on the target device. ULTRA baits the rootkit to provoke activity, measures electromagnetic emanation with a software-defined radio, preprocesses signals, then detects and classifies rootkit behavior using machine/deep learning techniques. As use cases, we target two IoT devices with MIPS and ARM architectures. The proposed approach achieved promising results with high accuracy for detecting both known and unknown rootkits during the offline learning phase. Our experimental study involves classification of rootkit families and distinct variants, obfuscated rootkits, probe dislocation, benign noise (kernel) activities, and comparison with software-based solutions.</p>
</div>
</div>
</div>
</li>
<li>
<div class="row">
<div class="col-sm-2 abbr">
</div>
<div id="pham:hal-03374399" class="col-sm-8">
<div class="title">Obfuscation Revealed: Leveraging Electromagnetic Signals for Obfuscated Malware Classification</div>
<div class="author">
<em>Pham, Duy-Phuc</em>,
Marion, Damien,
Mastio, Mathieu,
and Heuser, Annelie
</div>
<div class="periodical">
<em>In Annual Computer Security Applications Conference</em>
2021
</div>
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<a href="https://dl.acm.org/doi/10.1145/3485832.3485894" class="btn btn-sm z-depth-0" role="button" target="_blank">HTML</a>
<a href="https://hal.archives-ouvertes.fr/hal-03374399/file/ACSAC21_camera_ready.pdf" class="btn btn-sm z-depth-0" role="button" target="_blank">PDF</a>
<a href="https://github.com/ahma-hub" class="btn btn-sm z-depth-0" role="button" target="_blank">Code</a>
</div>
<!-- Hidden abstract block -->
</div>
</div>
</li>
<li>
<div class="row">
<div class="col-sm-2 abbr">
</div>
<div id="PhamVM19" class="col-sm-8">
<div class="title">Mac-A-Mal: macOS malware analysis framework resistant to anti evasion techniques</div>
<div class="author">
<em>Pham, Duy-Phuc</em>,
Vu, Duc Ly,
and Massacci, Fabio
</div>
<div class="periodical">
<em>J. Comput. Virol. Hacking Tech.</em>
2019
</div>
<div class="links">
<a href="https://doi.org/10.1007/s11416-019-00335-w" class="btn btn-sm z-depth-0" role="button" target="_blank">HTML</a>
<a href="https://github.com/phdphuc/mac-a-mal" class="btn btn-sm z-depth-0" role="button" target="_blank">Code</a>
</div>
<!-- Hidden abstract block -->
</div>
</div>
</li>
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