Reading Group for Dependable Computing Systems Lab – Fall 2021
For Fall 2021, we will be meeting on Thursdays 5:00-6:30. We will start off virtually and then hopefully, with the case numbers coming down, we will move to in-person.
| Dates | Topic | Suggested papers | Presenters | Recording |
|---|---|---|---|---|
| Sep 6 | Introductions, Fun quiz, Paper writing tips | Saurabh | ||
| Sep 16 | Own work: Ensemble security for ML | Ruqi | ||
| Sep 23, 30 | Reliability of zero/one shot learning | A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts (CVPR, 2018) | Ashraf | Recording (protected) Slide deck |
| Oct 7 | Model extraction attacks and defenses | Tramèr, Florian, Fan Zhang, Ari Juels, Michael K. Reiter, and Thomas Ristenpart. "Stealing machine learning models via prediction apis." In 25th {USENIX} Security Symposium ({USENIX} Security 16), pp. 601-618. 2016. | Ahaan, Atul | Recording (protected) Slide deck |
| Oct 14 | October break | |||
| Oct 21, 28 | Security of distributed learning | Liu, Lumin, Jun Zhang, S. H. Song, and Khaled B. Letaief. "Client-edge-cloud hierarchical federated learning." In ICC 2020-2020 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE, 2020. Wang, Xiaoding, Sahil Garg, Hui Lin, Jia Hu, Georges Kaddoum, Md Jalil Piran, and M. Shamim Hossain. "Towards accurate anomaly detection in industrial internet-of-things using hierarchical federated learning." IEEE Internet of Things Journal (2021). | Edgardo, Josh Z | Slide deck |
| Nov 4 | Own work | Akhil | Video (Password protected) |
|
| Nov 11 | Large streaming models on tiny devices | "Flexible High-resolution Object Detection on Edge Devices with Tunable Latency" MSRA, USTC, Tsinghua, Mobicom 2021. "MoViNets: Mobile Video Networks for Efficient Video Recognition" Google Research, CVPR 2021. | Pengcheng, Preeti | Pengcheng: Mobicom 2021 Preeti: CVPR 2021 |
| Nov 18 | Own work: Approximate streaming models on embedded devices | Akash, Sarthak | ||
| Nov 25 | Thanksgiving break | |||
| Dec 2 | Own work | Mustafa | ||
| Dec 9 | Adversarial reinforcement learning | Pinto, Lerrel, James Davidson, Rahul Sukthankar, and Abhinav Gupta. "Robust adversarial reinforcement learning." In International Conference on Machine Learning, pp. 2817-2826. PMLR, 2017. Gleave, Adam, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, and Stuart Russell. "Adversarial policies: Attacking deep reinforcement learning." ICLR 2020. | Dipesh | Slide Video (protected) |
Reading Group for Dependable Computing Systems Lab – Spring 2021
For Spring 2021, we will be meeting on Tuesdays 11.30-1.00.
The papers are samples and the discussion will go beyond them or may use other papers altogether.
| Date | Topic | Presenters |
|---|---|---|
| Jan 26, Feb 2 | How to write a strong evaluation section | Saurabh |
| Feb 9 | Lightning talks from all group members | All |
| Feb 16 | Own work: Security of Android devices | Josh |
| Feb 23, Mar 2 | Reliability and security of serverless computing Sreekanti et al. "A Fault-Tolerance Shim for Serverless Computing" Eurosys 2020. Datta et al. "Valve: Securing Function Workflows on Serverless Computing Platforms" WWW 2020. | Karthick, Ashraf |
| Mar 9 | Own work: IoT deployments | Pengcheng, Edgardo |
| Mar 16, 23 | Reliable computing with heterogeneous embedded devices and drones | Ran, Jay |
| Mar 30 | Own work: Security in distributed ML | Atul |
| Apr 6, 20 (Apr 13 is reading day and off for students) | Distributed ML on lightweight devices | Pranjal, Tanushree |
| Apr 27 | Own work: Security in ML | Ruqi |
| May 4 | Lessons learned | Saurabh |
Reading Group for Dependable Computing Systems Lab – Fall 2020
We will be meeting on Zoom on Tuesdays 11:30 AM – 1:00 PM.
URL: https://purdue-edu.zoom.us/j/93810013621?pwd=MWRPTUpjSUZsUG1BbzZURU5lRi80Zz09
Meeting ID: 938 1001 3621
Passcode: 878001
| Dates | Topic | Suggested papers | Presenters | Recording |
|---|---|---|---|---|
| Sep 8 | Intro, Paper writing techniques | Saurabh | Link | |
| Sep 15 | Own work: Byzantine-robust federated learning | Atul | ||
| Sep 22 | Own work: Approximate streaming analytics for the edge | Ran | ||
| Sep 29, Oct 6 | Binary analysis of embedded software | Vulnerability Detection in IoT Firmware: A Survey - ICPADS, 2017. A broad overview of IoT firmware vulnerability detection coupled with a novel static analysis technique to detect authentication bypass flaws. FirmUp: Precise Static Detection of Common Vulnerabilities in Firmware - ASPLOS 2018. A new static analysis technique for finding CVEs in stripped firmware binaries. | Austin, Abe | |
| Oct 13 | Own work: Behavioral Decision-Making in Security of interdependent systems | Mustafa | ||
| Oct 20, 27 | Reliability of autonomous systems | - Pei, Kexin, Yinzhi Cao, Junfeng Yang, and Suman Jana. "Deepxplore: Automated whitebox testing of deep learning systems." In proceedings of the 26th Symposium on Operating Systems Principles (SOSP), pp. 1-18. 2017. - Mishra, N., Imes, C., Lafferty, J.D. and Hoffmann, H., “CALOREE: Learning control for predictable latency and low energy.” ASPLOS, pp.184-198, 2018. | Ashraf, Pengcheng | |
| Nov 3 | Reliability of edge computing systems | “Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping” Ali J. Ben Ali, Zakieh Sadat Hashemifar, Karthik Dantu University of Buffalo, Mobisys 2020. | Heng | Link |
| Nov 10, 17 | Performance predictability of ML processing | Edgardo, Josh | ||
| Nov 24 | How to write good evaluation section | Saurabh | ||
| Dec 1 | Adversarial ML | Ruqi | ||
| Dec 8 | Embedded testbed setup | Shristi, Jay |
Reading Group for Dependable Computing Systems Lab – Spring 2020
We will be meeting in EE 118 on Wednesdays 12:30 – 2:00 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Feb 12 | Paper writing analysis & Own work | Heng Zhang, Michael A. Roth, Rajesh K. Panta, He Wang, Saurabh Bagchi. CrowdBind: Fairness Enhanced Late Binding Task Scheduling in Mobile Crowdsensing, EWSN '20, Best Paper Finalist | Saurabh, Heng | |
| Feb 19, 26 | Distributed Machine Learning under Attacks | Reza Shokri and Vitaly Shmatikov. 2015. Privacy-Preserving Deep Learning. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security ( CCS ’15). Association for Computing Machinery, New York, NY, USA, 1310–1321. Bhagoji, Arjun Nitin, Supriyo Chakraborty, P. Mittal, and S. Calo. "Model Poisoning Attacks in Federated Learning." In In Workshop on Security in Machine Learning (SecML), collocated with the 32nd Conference on Neural Information Processing Systems (NeurIPS’18). 2018. | Atul, Manish | Atul Slides |
| Mar 4 | Own work | Approximate ML for embedded systems with reliability and performance guarantees | Ran | |
| Mar 11 | Symbolic execution for verification of systems | Nelson L, Bornholt J, Gu R, Baumann A, Torlak E, Wang X. Scaling symbolic evaluation for automated verification of systems code with Serval. InProceedings of the 27th ACM Symposium on Operating Systems Principles 2019 Oct 27 (SOSP '19) (pp. 225-242). KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs, Cristian Cadar, Daniel Dunbar, and Dawson Engler (Stanford University) (OSDI '08) | Austin | |
| Mar 25 | Own work | Serverless computing: reliability and performance guarantees | Ashraf | |
| Apr 1 | Attacks and Defenses against Cyber Physical Systems | Choi, Hongjun, Wen-Chuan Lee, Yousra Aafer, Fan Fei, Zhan Tu, Xiangyu Zhang, Dongyan Xu, and Xinyan Deng. "Detecting attacks against robotic vehicles: A control invariant approach." In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS '18), pp. 801-816. 2018. Sun, Pengfei, Luis Garcia, and Saman Zonouz. "Tell Me More Than Just Assembly! Reversing Cyber-Physical Execution Semantics of Embedded IoT Controller Software Binaries." In 2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN '19), pp. 349-361. IEEE, 2019. | ||
| Apr 8 | Own work | "Anomaly detection through sensing data with missing data values" | Sean | |
| Apr 15 | Big-Data Programming Models & Frameworks | Fang, Minghong, Xiaoyu Cao, Jinyuan Jia, and Neil Zhenqiang Gong. "Local model poisoning attacks to Byzantine-robust federated learning." pp. 1--18, Usenix Security 2020. J. E. Gonzalez, Y. Low, H. Gu, D. Bickson, and C. Guestrin. PowerGraph: Distributed graph-parallel computation on natural graphs. In (OSDI '12), pages 17–30, 2012. | Atul | Atul Slides |
| Apr 22 | Own work | Privacy preserving inferencing from distributed sensor data in a battlefield environment | Shams | |
| Apr 29 | Approximation for ML Algorithms | Belabbas, M.A. and Wolfe, P.J., 2009. Spectral methods in machine learning and new strategies for very large datasets. Proceedings of the National Academy of Sciences, 106(2), pp.369-374. | Pengcheng |
Reading Group for Dependable Computing Systems Lab – Fall 2019
We will be meeting in EE 118 on Thursdays 5:00 – 6:30 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Aug 22 | Paper writing analysis | Saurabh | ||
| Aug 29, Sep 5 | Testing ML programs | Pei, Kexin, Yinzhi Cao, Junfeng Yang, and Suman Jana. "Deepxplore: Automated whitebox testing of deep learning systems." In Proceedings of the 26th Symposium on Operating Systems Principles (SOSP), pp. 1-18. ACM, 2017. Sun, Youcheng, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, and Daniel Kroening. "Concolic testing for deep neural networks." In Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE), pp. 109-119. ACM, 2018. | ||
| Sep 12 | Own work | |||
| Sep 19, 26 | ML at the edge | Jiang, Junchen, Ganesh Ananthanarayanan, Peter Bodik, Siddhartha Sen, and Ion Stoica. "Chameleon: scalable adaptation of video analytics." SIGCOMM 2018. Luyang Liu, Hongyu Li, Marco Gruteser "Edge Assisted Real-time Object Detection for Mobile Augmented Reality." 25th Annual International Conference on Mobile Computing and Networking (Mobicom), 2019. | ||
| Oct 3 | Own work | |||
| Oct 10, 17 | Security of autonomous embedded platforms | Choi, H., Lee, W.C., Aafer, Y., Fei, F., Tu, Z., Zhang, X., Xu, D. and Xinyan, X., 2018, October. Detecting attacks against robotic vehicles: A control invariant approach. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS) (pp. 801-816). ACM. He, Zhijian, Yao Chen, Enyan Huang, Qixin Wang, Yu Pei, and Haidong Yuan. "A system identification based Oracle for control-CPS software fault localization." In Proceedings of the 41st International Conference on Software Engineering (ICSE), pp. 116-127. IEEE Press, 2019. | ||
| Oct 24 | Own work | |||
| Oct 31, Nov 7 | Distributed systems for accelerating ML | Cui, Henggang, Hao Zhang, Gregory R. Ganger, Phillip B. Gibbons, and Eric P. Xing. "Geeps: Scalable deep learning on distributed gpus with a gpu-specialized parameter server." In Proceedings of the Eleventh European Conference on Computer Systems (Eurosys), p. 4. ACM, 2016. Hsieh, Kevin, Aaron Harlap, Nandita Vijaykumar, Dimitris Konomis, Gregory R. Ganger, Phillip B. Gibbons, and Onur Mutlu. "Gaia: Geo-Distributed Machine Learning Approaching {LAN} Speeds." In 14th {USENIX} Symposium on Networked Systems Design and Implementation (NSDI), pp. 629-647. 2017. | ||
| Nov 14 | Own work | |||
| Nov 21, 28 | Adversarial example detection for ML models | Song, Yang, Taesup Kim, Sebastian Nowozin, Stefano Ermon, and Nate Kushman. "Pixeldefend: Leveraging generative models to understand and defend against adversarial examples." International Conference on Learning Representations (ICLR), 2017. Xu, Weilin, David Evans, and Yanjun Qi. "Feature squeezing: Detecting adversarial examples in deep neural networks." Network and Distributed System Security Symposium (NDSS), 2017. |
Reading Group for Dependable Computing Systems Lab – Fall 2018
We will be meeting in EE 118 on Wednesdays 5:00 – 6:30 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Aug 29 | Paper writing analysis | Saurabh | ||
| Sep 5 | Paper writing analysis | Saurabh | ||
| Sep 12 | Own work | Heng | ||
| Sep 19, 26 | Debugging ML stacks | "Why Should I Trust You?": Explaining the Predictions of Any Classifier - Ribeiro, Singh, Guestrin. KDD 16. "Interpretable Convolutional Neural Networks," Zhang, Wu, Zhu, CVPR 2018. | Jinkyu, Chandan | Jinkyu PDF Chandan PDF |
| Oct 3 | Own work | Mustafa | ||
| Oct 10, 17 | Debugging distributed systems | D3S: Debugging Deployed Distributed Systems, Kaashoek et al. NSDI-08. Debugging Distributed Systems, Ernst et al. ACM Queue-16. | Ran, Shikhar | |
| Oct 24 | Own work | Charitha | ||
| Oct 31, Nov 7 | Attacks against online learning, transfer learning | With Great Training Comes Great Vulnerability: Practical Attacks against Transfer Learning, Ben Zhao et al. Usenix Security-18. The space of transferable adversarial examples, McDaniel et al. Arxiv-17. | Ashraf, Rakesh | |
| Nov 14 | Own work | Edgardo | ||
| Nov 21 | Own work | Chris W |
Reading Group for Dependable Computing Systems Lab – Spring 2018
We will be meeting in EE 118 on Thursdays 5.30 – 7:00 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Feb 22 | Own work | Charitha | ||
| Feb 15, Mar 1 | Configuration management in distributed systems | "Borg, Omega, and Kubernetes" IEEE Queue, Mar 2016; Unikernels, ASPLOS 2013. | Ashraf, Rakesh | |
| Mar 8 | Own work | Subramaniyam | ||
| Mar 22, 29 | Security implications and debugging in ML | SOSP 17 paper from Columbia; Papernot et al. AsiaCCS 17 | Jinkyu, Paul | |
| Apr 5 | Own work | Naif | ||
| Apr 12, 19 | Wearable devices | Mobicom 17 paper from U Buffalo; Mobisys 16 paper from Felix | Edgardo, Heng | |
| Apr 26 | Own work | Ran, Peter |
Reading Group for Dependable Computing Systems Lab – Fall 2017
We will be meeting in EE 118 on Thursdays 5.30 – 7:00 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Aug 31 | Introduction Logistics Paper writing tips | Saurabh | ||
| Sep 14, 21 | Vulnerability discovery through static analysis or dynamic analysis | Charitha, Jinkyu | ||
| Sep 28 | Own work | Heng | ||
| Oct 5, 12 | Programming accelerators (GPU, DSP, FPGA, neuromorphic chips) | Paul, Saurabh | ||
| Oct 19 | Own work | Naif | ||
| Oct 26, Nov 2 | Smart contracts and smart money | Abe, Aniket's student | ||
| Nov 9 | Own work | Ashraf | ||
| Nov 16 | Own work | Chris W | ||
| Nov 30, Dec 7 | Reliability challenges in new wireless technologies: UWB, 5G, cognitive radio | Mustafa, Heng |
Reading Group for Dependable Computing Systems Lab – Fall 2016
We will be meeting in MSEE 239 on Thursdays 6.00 – 7:30 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Sep 1 | Own work | Tara | ||
| Sep 8, 15 | Debugging distributed systems | Scott-NSDI16, Kasikci-SOSP15 | Subrata, Charitha | |
| Sep 22 | Own work | Chris G, Tom | ||
| Sep 29, Oct 6 | Infrastructure for large-scale machine learning | Google-OSDI16, Google-NIPS12 | Ashraf, Jinkyu | |
| Oct 13 | Own work | Nawanol | ||
| Oct 20, 27 | Security bug finding through static analysis | Livshits-UsenixSec05, Costin-UsenixSec14 | Chris W, Abe | |
| Nov 3 | Own work | Ayush | ||
| Nov 10, 17 | Distributed processing using accelerators | Kaleem-PACT14, Kim-OSDI14 | Paul, Ranvijay | |
| Dec 1 | Own work | Ashraf | ||
| Dec 8, 15 | Security in crowdsourced systems | Wang-Mobisys16, Tran-NSDI09 | Ayush, Heng |
Reading Group for Dependable Computing Systems Lab – Spring 2016
We will be meeting in EE 118 on Thursdays 6.00 – 7:30 PM.
| Dates | Topic | Papers | Presenter(s) | Presentation |
|---|---|---|---|---|
| Feb 18 | DoS in Control Systems | Paul | ||
| Feb 25 | Own Work | Chris | ||
| Mar 03 Mar 10 | Network Function Virtualization Reliability | Saurabh, Ayush | Powerpoint (Saurabh) Powerpoint (Ayush) |
|
| Mar 24 | Own Work | Kanak | ||
| Mar 31 Apr 07 | Streaming Data analytics in IoT | Subrata, Akshay | ||
| Apr 14 | Own Work | Chris W | ||
| Apr 21 Apr 28 | Randomization for Security for Embedded devices | Ravi, Abe | ||
| May 05 | Own work | Tara |
History of DCSL Reading group
2022, 2015, 2014, 2013, 2012, 2010, 2009, 2008, 2007, 2006, 2005, 2004, 2003, 2002