Difference between revisions of "Cybersecurity"
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| − | <b> | + | <b>AI and Security |
| − | </b><br> | + | </b><br>In the future, every company will be using AI, which means that every company will need a secure infrastructure that addresses AI security concerns. At the same time, the domain of computer security has been revolutionized by AI techniques, including machine learning, planning, and automatic reasoning. What are the opportunities for researchers in both fields—security infrastructure and AI—to learn from each other and continue this fruitful collaboration? This session will cover two main topics. In the first half, we will discuss how AI techniques have changed security, using a case study of the DARPA Cyber Grand Challenge, where teams built systems that can reason about security in real time. In the second half, we will talk about security issues inherent in AI. How can we ensure the integrity of decisions from the AI that drives a business? How can we defend against adversarial control of training data? Together, we will identify common problems for future research. |
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| − | <b> | + | <b>EP 03: Inside DARPA’s Cyber Grand Challenge |
| − | </b><br> | + | </b><br>DARPA’s Cyber Grand Challenge in 2016 showed the world what's coming -- autonomous adversaries -- and raised serious questions. How can organizations react to something that makes decisions in milliseconds? How can you still have humans in the loop when reaction time is key? And how can organizations defend or stop something that increases its own cyber capabilities autonomously? In this episode we go behind the scenes for the first and only completely autonomous capture the flag competition at DEF CON 24 with Team ForAllSecure. Twitter: @Th3H4ck3rm1nd thehackermind.com |
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Revision as of 19:15, 5 October 2020
Youtube search... ...Google search
- Case Studies
- Capabilities
- Cybersecurity References
- Offense - Adversarial Threats/Attacks
- Cybersecurity Frameworks, Architectures & Roadmaps
- Cybersecurity Companies/Products
- Cybersecurity: National Institute of Standards and Technology (NIST) & U.S. Department of Homeland Security (DHS)
- Defense: Cybersecurity and Acquisition Lifecycle Integration Tool (CALIT)
- Cybersecurity: Evaluating & Selling
- (Artificial) Immune System
- 5G Security
- Useful Models ...find outliers:
- Detecting Malicious Requests with Keras & TensorFlow | Adam Kusey - Medium
- Best security software: How 12 cutting-edge tools tackle today's threats | CSO
- graphistry.com
- Intelligence Advanced Research Projects Activity (IARPA)Is Trying Keep Adversaries From Corrupting AI Tools ... Could cyber adversaries be training the government’s artificial intelligence tools to fail? | Jack Corrigan - Nextgov
- TrojAI - Office of the Director of National Intelligence Office: Intelligence Advanced Research Projects Activity FedBizOpps.gov predict whether AI systems have been corrupted through so-called “Trojan attacks.”
- Adversarial Attacks on Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
- Breaking Down the Tencent 2018 Cybersecurity Report
- Chronicle combines all the best parts of Google and X culture
- Fraud and Anomaly Detection | Chris Nicholson - A.I. Wiki pathmind
- The Cyber Security Evaluation Tool (CSET®) | National Cybersecurity and Communications Integration Center ...provides a systematic, disciplined, and repeatable approach for evaluating an organization’s security posture
- Watch me Build a Cybersecurity Startup | Siraj Raval
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Fraud Detection
- Introduction to Fraud Detection Systems | Miguel Gonzalez-Fierro, Microsoft
- AI for Health Insurance Fraud Detection – Current Applications | Niccolo Mejia
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Data Center Security
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