SW

Dr. Sarah Wijaya, Ph.D.

Lead Security Researcher • Android Security Expert
Ph.D. Stanford CISSP CEH OSCP GMOB ISO 27001 Lead Auditor

Lead Security Researcher di gacor77 dengan Ph.D. in Computer Science dari Stanford University. Spesialisasi dalam Android security, malware detection using machine learning, dan mobile threat analysis. 12+ tahun pengalaman di Google Android Security Team, kontributor AOSP, dan published researcher di konferensi internasional (BlackHat, DEF CON, OWASP AppSec).

12+ Tahun Pengalaman
25+ Publikasi Research
500+ CVE Discoveries
50+ Conference Talks

🎓 Pendidikan

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Pendaftaran Pengguna Masuk

💼 Pengalaman Profesional

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📚 Publikasi & Research

Conference Paper
S. Wijaya, A. Pratama, L. Kusuma | BlackHat Asia 2023 | Singapore

Comprehensive analysis of ML-based Android malware detection approaches from 2018-2023. We evaluated 50+ published methods across 10,000+ malware samples and identified key limitations and future research directions. Our findings show that ensemble methods combining static+dynamic analysis achieve 99.2% detection rate with 0.3% false positive rate.

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Journal Article
S. Wijaya, et al. | IEEE Transactions on Mobile Computing | 2022 | Impact Factor: 6.075

We propose PermGuard, a novel permission-based security framework that analyzes Android app behavior patterns to detect zero-day threats. Evaluated on 50,000+ apps, PermGuard achieved 97.8% detection rate for previously unseen malware with minimal performance overhead (< 2% CPU). The framework has been deployed in production by 3 major Android OEMs.

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Conference Talk
S. Wijaya | DEF CON 29 | Las Vegas, USA | 2021

Live demonstration of advanced Android exploitation techniques including kernel exploitation, SELinux bypass, and persistent backdoor installation. Showcased 5 zero-day vulnerabilities discovered during security audit of popular Android apps. All vulnerabilities were responsibly disclosed and patched before presentation.

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Research Paper
S. Wijaya, R. Firmansyah | OWASP AppSec Global 2020 | Virtual

Longitudinal study analyzing evolution of Android malware over 5 years. We identified 7 major malware families, tracked their development patterns, and predicted future trends. Dataset of 100,000+ malware samples made public for research community. Study cited 150+ times in security research papers.

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🎓 View All Publications (25+) on Google Scholar
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🏆 Sertifikasi Profesional

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