Wireless Networks Security and Privacy

Semester: 2020 Autumn
Time: 13:15-16:40 (6.7.8.9)
Location: Yuquan Campus, #4 Teaching Building 426
TA : Juchuan Zhang, juchuanzhang@zju.edu.cn

Schedule

Group:each group has 2 students. Send your group information to TA according to the following format:

Format: the order you wish to present + group members + paper name, e.g.,
“1 + Alice, Bob + Beauty and the Burst: Remote Identification of Encrypted Video Streams”

Student presentation:
1. 2 students as a group
2. chooses paper from the list I provide or from others relevant conferences/ journals
3. Presentations lasts for 20 mins + Q&A + Discussion
4. Submit a summary paper for the paper you present
5. Make slides yourself

Paper source:
1. Big 4: USENIXS Security/ NDSS/ ACM CCS/ IEEE Oakland (S&P)
2. Other leading conferences: ACM Mobicom, ACM sigcomm, IEEE Infocom, CHI, Ubicomp, NSDI
3. CCF ranked conferences and journals:
security: http://history.ccf.org.cn/sites/ccf/biaodan.jsp?contentId=2903940690850
networks: http://history.ccf.org.cn/sites/ccf/biaodan.jsp?contentId=2903028135856

Course materials:
- 课件(浙大云盘)

课程project参考:
1. 图像对抗 (CNN)
- https://github.com/bethgelab/foolbox
- https://github.com/BorealisAI/advertorch

2. 语音对抗 (Speech-to-Text)
- https://github.com/carlini/audio_adversarial_examples
- https://github.com/tensorflow/cleverhans/tree/master/examples/adversarial_asr
- https://github.com/rub-ksv/adversarialattacks

3. 文本对抗
- https://github.com/airbnb/artificial-adversary

4. 对抗样本文章合集
- https://nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html
- https://nicholas.carlini.com/writing/2018/adversarial-machine-learning-reading-list.html

Candidate papers from me:
1. Gesture Authentication for Smartphones: Evaluation of Gesture Password Selection Policies
2. This PIN Can Be Easily Guessed: Analyzing the Security of Smartphone Unlock PINs
3. Automatically Detecting Bystanders in Photos to Reduce Privacy Risks
4. TRRespass: Exploiting the Many Sides of Target Row Refresh
5. An Analysis of Pre-installed Android Software
6. Automatic Uncovering of Hidden Behaviors from Input Validation in Mobile Apps
7. Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning
8. I Know Where You Parked Last Summer : Automated Reverse Engineering and Privacy Analysis of Modern Cars
9. Breaking Secure Pairing of Bluetooth Low Energy Using Downgrade Attacks
10. You Are What You Broadcast: Identification of Mobile and IoT Devices from (Public) WiFi
11. Chaperone: Real-time Locking and Loss Prevention for Smartphones
12. Who's Calling? Characterizing Robocalls through Audio and Metadata Analysis
13. Hall Spoofing: A Non-Invasive DoS Attack on Grid-Tied Solar Inverter
14. COUNTERFOIL: Verifying Provenance of Integrated Circuits using Intrinsic Package Fingerprints and Inexpensive Cameras
15. Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries
16. Adversarial Preprocessing: Understanding and Preventing Image-Scaling Attacks in Machine Learning
17. DeepHammer: Depleting the Intelligence of Deep Neural Networks through Targeted Chain of Bit Flips
18. Human Distinguishable Visual Key Fingerprints
19. Preech: A System for Privacy-Preserving Speech Transcription
20. Are You Going to Answer That? Measuring User Responses to Anti-Robocall Application Indicators
21. FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic
22. CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples
23. On the Resilience of Biometric Authentication Systems against Random Inputs
24. Detecting Fake Accounts in Online Social Networks at the Time of Registrations
25. DeepIntent: Deep Icon-Behavior Learning for Detecting Intention-Behavior Discrepancy in Mobile Apps
26. Seeing isn't Believing: Towards More Robust Adversarial Attack Against Real World Object Detectors
27. Trick or Heat?: Manipulating Critical Temperature-Based Control Systems Using Rectification Attacks
28. When the Differences in Frequency Domain are Compensated: Understanding and Defeating Modulated Replay Attacks on Automatic Speech Recognition