
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 1ch | Duration: 4H 58M | 10.70 GB
Genre: eLearning | Language: English
Fraud and abuse aimed at organizations big and small is becoming more and more sophisticated. In this unique O'Reilly video collection-taken from live sessions at Strata + Hadoop World 2015 in San Jose, California-you'll learn about security tools and techniques for dealing with this growing and ever-present threat.
This video collection includes:
Data Science vs. The Bad Guys: Using data to defend LinkedIn against fraud and abuse
David Freeman (LinkedIn)
Explore the barrage of fraudulent and abusive activity aimed at LinkedIn, such as fake accounts, account takeover, and scraping-and learn some solutions the company has built to defend against them.
Secure Machine Learning
Bahman Bahmani (Stanford University)
Learn the interplay between attack and defense in the design of secure machine learning algorithms, including solutions to exploratory attacks, causative attacks, and reverse engineering.
Data Security in Hadoop for large enterprises
Ajit Gaddam (VISA)
How do you ensure that big data in Hadoop doesn't become a big target? This session reveals what Visa discovered, reinvented, polished, and developed to support data security, compliance, cryptographic protection, and effective risk management.
The Future of Apache Hadoop Security
Joey Echeverria (Rocana)
Examine the state of Hadoop security today and where it's headed. You'll visit new projects such as Apache Sentry and Apache Knox, as well as initiatives such as Project Rhino.
Real-Time Cyber Threat Detection with Sqrrl and Spark
Adam Fuchs (Sqrrl)
Learn how to build a real-time anomaly detection system for cybersecurity that focuses on Advanced Persistent Threat (APT) and malicious insider scenarios, using Sqrrl Enterprise and the GraphX library included in Apache Spark.
Getting Started with Data Governance: Paths Converge from Multiple Starting Points
Paula Wiles Sigmon (IBM)
Explore several reasons for getting started with information governance-including starting points that have been tried, results that have been achieved, and lessons learned-for organizations across several industries.
Data Governance for Regulated Industries
Amir Halfon (ScalingData)
Examine best practices around the use of big data technologies as part of a regulated environment, including retention, provenance, privacy, and security for banking, healthcare, and other organizations.
Why Should Anyone Care at All about Privacy, Privacy Engineering, or Data?
Michelle Dennedy (McAfee, an Intel Company)
Learn how to design systems and functional interfaces that enhance data privacy with sustainability that invites transparency and further innovation. Those who create those systems with elegance, efficiency, and measurable components will profit and proliferate.
A Framework of Purpose and Consent for Data Security and Consumer Privacy
Aurélie Pols (Mind Your Group)
Borrowing from Spanish information security best practices-in the light of increasing data breach regulations-this presentation examines how data flows should be defined and secured in order to assure accountability through an entire data lifecycle.
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