NIT

Summer 2020

Instructor: Prof. Bharat Bhargava. email: bbshail AT purdue.edu

Description

NIT

Tentative Lecture Plan (Subject to Change)

No. Topic
01 Introduction to Trust
02 Introduction to Privacy
03 Introduction to Security
04 Trading Privacy for Trust
05 Towards Measuring Security and Privacy via Serv Mech, Lilien
06 Secure Data Warehouse
07 Attacks in Networks
08 Detecting Service Violations and Intruders
09 Coordinated Attacks on MANETs [CERIAS]
10 Collaborative Attacks and REACT, Wang
11 Collaborative Attacks, Wang
12 Collaborative Attacks
13 Peer to Peer Trusted Communication
14 Privacy Preserving Data Dissemination
15 Data Dissemination and Evaporation
16 Data Dissemination in UAV
17 Explanations of IAS
17 Blockhub, Ulybyshev
18 Secure Resilient Systems and Provenance
19 IAS, JPL, Bhargava
20 IAS Intelligent Autonomous Secure Systems
21 Switzerland Conference, IAS, Bhargava
22 NGC Data Leakage and Moving Target Defense
23 Mitigating Poisoning Attacks on Machine Learning Models A Data Provenance Based Approach
23 Vienna Cognitive Autonomy Report
24 Nathalie Baracaldo Attacks AI ML
25 Nathalie Baracaldo ICIOT IBM
26 Adversarial Machine Learning
27 Adversarial Machine Learning IARPA
28 DARPA Meeting Learning Machines. Sept 10 - Short Version
29 STC Schedule
30 NSF Self Healing Proposal
31 CERT Attacks Models
32 CERT, Shanon, CMU
33 Mitigating Learning Attacks, Canada, Clement
34 Privacy and Identity Management in Cloud
35 Security and Privacy in Cloud
36 Privacy in Off Loading in Cloud
37 Measuring Attack Path Complexity
38 End to End Security in Service Oriented Architecture
39 Privacy Preservation in Cloud
40 Moving Target Defense, IEEE Cloud, 2017
41 Defending Against Collaborative Attacks in MANET
42 NGC Meeting
43 NGC Meeting
44 SOA Security
45 Extending Attacks Graph
46 Lecture on Privacy and Trust
47 Adaptable Service Composition, NGC Report
48 Adaptable Defense Collaborative Attacks in SOA

Extra Slides

No. Topic
49 Bhargava, Singh, Kumar, Stonebraker, Purdue University, 2020.
50 Palacios and Solaiman et al., VLDB Workshop, 2019.
51 Surveillance Video Querying, HILDA, 2020.
52 Surveillance Video Querying - [VIDEO], HILDA, 2020.
53 Situational Knowledge On Demand (SKOD) [Presentation Slides] Bhargava, NGC Tech Fest, 2019.
54 Situational Knowledge On Demand [REALM] Bhargava, Purdue University, 2019.
55 Situational Knowledge on Demand: Information Extraction from Multimodal Data for Knowledge Graph Construction [Abstract] Nesen, Purdue University, 2020.
56 Adversarial Machine Learning: Big Data Meets Cyber Security [Video], Bowei, National Academy, 2020.
57 ConFoc: Content-Focus Protection Against Trojan Attacks on Neural Networks, NDSS, 2020.
58 Hunting for Insider Threats Using LSTM-based Anomaly Detection, TDSC, 2020.
59 Anomaly Detection and Security Deep Learning Methods Under Adversarial Situation, Villarreal-Vasquez, Thesis, 2020.
60 Anomaly Detection and Security Deep Learning Methods Under Adversarial Situation [Final Exam Video]
61 ISI Final Slides
62 Vishnu-Kagal-MIT-Explainable-AI
63 Developing Attack Defense Ideas for Ad Hoc Wireless Networks
64 Adversarial Machine Learning
65 Adversarial Machine Learning, Baracaldo
66 A Survey on Bias and Fairness in Machine Learning
67 CERIAS Seminar Videos

Credit
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