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Location： Caoguangbiao-201
Time: 18:00-20:00 Welcome to attend the seminar!
| Date | Speaker | Title | |
|---|---|---|---|
| 1 | 2018.1.5 | 施程辉 唐凯宇 |
DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation ADVERSARIAL EXAMPLES IN THE PHYSICAL WORLD |
| 2 | 2018.1.12 | 徐晓刚 王博 |
Adversarial Attacks on Neural Network Policies Meltdown & Spectre |
| 3 | 2018.1.19 | 刘沛宇 陈源 |
Broken Fingers: On the Usage of the Fingerprint API in Android Didn’t You Hear Me? — Towards More Successful Web Vulnerability Notifications |
| 4 | 2018.1.26 | 卢令令 李长江 |
BLOCKBENCH: A Framework for Analyzing Private Blockchains Feature Squeezing:Detecting Adversarial Examples in Deep Neural Networks |
| 5 | 2018.2.2 | 杜天宇 李进锋 |
Trojaning Attack on Neural Networks Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data |
| 6 | 2018.2.9 | Report | |
| 7 | 2018.2.24 | 李宇薇 刘倩君 |
Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection(CCS-17). |
| 8 | 2018.3.2 | 凌祥 李旭嵘 |
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong WHITENING BLACK-BOX NEURAL NETWORKS |
| 9 | 2018.3.9 | 伍一鸣 刘倩君 |
Game of Missuggestions: Semantic Analysis of Search-Autocomplete Manipulations When coding style survives compilation: de-anonymizing programmers from executable binaries. |
| 10 | 2018.3.16 | 翁海琴 贺思睿 |
Machine Learning Models that Remember Too Much |
| 11 | 2018.3.23 | 周骏丰 魏成坤 |
VulDeePecker: A Deep Learning-Based System for Vulnerability Detection IKP: Turning a PKI Around with Decentralized Automated Incentives |
| 12 | 2018.3.30 | 唐凯宇 吕晨阳 |
Knock Knock, Who’s There? Membership Inference on Aggregate Location Data |
| 13 | 2018.4.6 | 段辅正 陈源 |
How to Learn Klingon Without Dictionary: Detection and Measurement of Black Keywords Used by Underground Economy |
| 14 | 2018.4.13 | 肖特嗣 刘栩威 |
ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models Predicting the resilience of obfuscated code against symbolic execution attacks via machine learning |
| 15 | 2018.4.20 | 周安妮 付丽嫆 |
PlatPal: Detecting Malicious Documents with Platform Diversity BinSim: Trace-based Semantic Binary Diffing via System Call Sliced Segment Equivalence Checking |
| 16 | 2018.4.27 | 冯依南 刘丁豪 |
RELIABLE ATTACKS AGAINST BLACK-BOX MACHINE LEARNING MODEL Town Crier: An Authenticated Data Feed for Smart Contracts |
| 17 | 2018.5.4 | 施程辉 李长江 |
Spatially Transformed Adversarial Example |
| 18 | 2018.5.11 | No Group meeting | |
| 19 | 2018.5.18 | 刘沛宇 | Prudent Practices for Designing Malware Experiments: Status Quo and Outlook |
| 20 | 2018.5.25 | 李宇薇 | Angora: Efficient Fuzzing by Principled Search |
| 21 | 2018.6.1 | 刘倩君 魏成坤 |
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| 22 | 2018.6.8 | 陈源 吕晨阳 |
CCS 2017： Directed Greybox Fuzzing |
| 23 | 2018.6.15 | 王博 唐凯宇 |
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| 24 | 2018.6.22 | 杜天宇 李进峰 |
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| 25 | 2018.6.29 | 施程辉 贺思睿 |
A Machine Learning Approach To Prevent Mailcious Calls Over Telephoney Networks |
| 26 | 2018.7.6 | 王琴应 宋宇 |
Spying on the Smart Home Privacy Attacks and Defenses on Encrypted IoT Traffic |
| 27 | 2018.7.13 | 黄诤杰 付丽嫆 |
SMARTPOOL: Practical Decentralized Pooled Mining |
| 28 | 2018.7.20 | 吴含露 董剑辉 |
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning |
| 29 | 2018.7.27 | 伍一鸣 卢令令 |
CertChain Public and Efficient Certificate Audit Based on Blockchain for TLS Connections |
| 30 | 2018.8.3 | 刘沛宇 魏成坤 |
Dark Hazard: Learning-based, Large-Scale Discovery of Hidden Sensitive Operations in Android Apps |
| 31 | 2018.8.10 | 李长江 李宇薇 |
SemFuzz: Semantics-based Automatic Generation of Proof-of-Concept Exploits (CCS-2017) |
| 32 | 2018.8.17 | 翁海琴 王博 |
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| 33 | 2018.8.24 | 施程辉 唐凯宇 |
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| 34 | 2018.8.31 | 吕晨阳 陈源 |
Who Is Answering My Queries: Understanding and Characterizing Interception of the DNS Resolution Path |
| 35 | 2018.9.7 | 王琴应 宋宇 |
Analysis of Privacy Protections in Fitness Tracking Social Networks |
| 36 | 2018.9.14 | 李旭嵘 付丽嫆 |
Detecting Adversarial Examples through Image Transformation |
| 37 | 2018.9.21 | 董剑辉 陈安莹 |
Learning Universal Adversarial Perturbations with Generative Models MineSweeper: An In-depth Look into Drive-by Cryptocurrency Mining and Its Defense |
| 38 | 2018.9.28 | 凌祥 黄诤杰 |
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| 39 | 2018.10.5 | 杜天宇 李进峰 |
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| 40 | 2018.10.12 | 贺思睿 段辅正 |
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| 41 | 2018.10.19 | 刘沛宇 魏成坤 |
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| 42 | 2018.10.26 | 吴含露 翁海琴 |
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| 43 | 2018.11.2 | 卢令令 伍一鸣 |
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| 44 | 2018.11.9 | 李长江 李宇薇 |
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| 45 | 2018.11.16 | 刘倩君 王博 |
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| 46 | 2018.11.23 | 施程辉 唐凯宇 |
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| 47 | 2018.11.30 | 吕晨阳 陈源 |
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| 48 | 2018.12.7 | 王琴应 宋宇 |
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| 49 | 2018.12.14 | 黄诤杰 吴含露 |
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| 50 | 2018.12.21 | 董剑辉 陈安莹 |
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