Sep 23–26, 2019

Schedule: Privacy and Security sessions

Recent regulations in Europe (GDPR) and California (Consumer Privacy Act) have placed concepts like “user control” and “privacy-by-design” at the forefront for companies wanting to deploy ML. The good news is that there are new privacy-preserving tools and techniques – including differential privacy – that are becoming available for both business intelligence and ML applications.

  • Data security and privacy: A recent white paper from the Hoover Institution observed that we are beginning to see the convergence of data privacy and security. This is an age when companies are guarding against the misuse of data, either by adversaries or by parties they presently trust but may not longer do so in the future: “Anyone, from a privacy perspective, can become an adversary, given enough time.”
  • The use of data, analytics, and machine learning in security and cybersecurity.
  • Secure and robust analytics, including secure machine learning and aspects of machine deception (such as machines deceiving machines, or people deceiving machines).
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9:00am12:30pm Tuesday, September 24, 2019
Location: 1E 15/16
Mark Donsky (Okera)
New regulations such as CCPA and GDPR are driving new compliance, governance, and security challenges for big data. Infosec and security groups must ensure a consistently secured and governed environment across multiple workloads that span on-prem, private cloud, multi-cloud, and hybrid cloud. We will share hands-on best practices for meeting these challenges, with special attention to CCPA. Read more.
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1:30pm5:00pm Tuesday, September 24, 2019
Location: 1E 15/16
Carolyn Duby (Hortonworks)
Bring your laptop, roll up your sleeves, and get ready to crunch some cyber security events with Apache Metron, an open source big data cyber security platform. Learn how Metron finds actionable events in real time. Read more.
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11:20am12:00pm Wednesday, September 25, 2019
Location: 1E 09
Steven Touw (Immuta)
Anti-patterns are behaviors that take bad problems and lead to even worse solutions. In the world of data security and privacy, they’re everywhere. Over the past 4 years we’ve seen data security and privacy anti-patterns consistently emerge across 100s of customers and industry verticals - there has been an obvious trend. We’ll cover 5 anti-patterns and more importantly, the solutions for them. Read more.
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1:15pm1:55pm Wednesday, September 25, 2019
Location: 1E 09
The Apache Parquet community is working on a column encryption mechanism that protects the sensitive data and enables access control for table columns. Many companies are involved, the mechanism specification has recently been signed off by the community management committee. I will present the basics of Parquet encryption technology, its usage model and a number of use cases. Read more.
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1:15pm1:55pm Wednesday, September 25, 2019
Location: 1E 14
Andrew Burt (Immuta), Brenda Leong (Future of Privacy Forum)
Machine learning techniques are being deployed across almost every industry and sector. But this adoption comes with real, and oftentimes underestimated, privacy and security risks. In this session, Immuta and the Future of Privacy Forum will convene leading industry representatives and experts to talk about real life examples of when ML goes wrong, and the lessons they learned. Read more.
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2:05pm2:45pm Wednesday, September 25, 2019
Location: 1E 09
Tomer Shiran (Dremio), Jacques Nadeau (Dremio)
With cheap and infinitely scalable storage services such as S3 and ADLS, it has never been easier to dump data into a cloud data lake. But how do you secure that data and make sure it doesn't leak? In this talk we explore numerous capabilities for securing a cloud data lake, including authentication, access control, encryption (in motion and at rest) and auditing, as well as network protections. Read more.
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2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 12/14
Mikio Braun (Zalando SE)
With ML becoming more and more mainstream, the side effects of using machine learning and AI on our lives become more and more visible. One has to take extra measures to make machine learning models fair and unbiased In addition, awareness for preserving the privacy in ML models is rapidly growing. Read more.
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2:05pm2:45pm Wednesday, September 25, 2019
Location: 1E 14
Andrew Burt (Immuta), Brenda Leong (Future of Privacy Forum)
From the EU to California and China, more and more of the world is regulating how data can be used. In this session, Immuta and the Future of Privacy Forum will convene leading experts on law and data science for a deep dive into ways to regulate the use of AI and advanced analytics. Come learn why these laws are being proposed, how they’ll impact data, and what the future has in store. Read more.
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2:55pm3:35pm Wednesday, September 25, 2019
Location: 1E 09
Justin Fier (Darktrace)
Cyber security must find what it doesn’t know to look for. AI technologies have led to the emergence of self-learning, self-defending networks that achieve this – detecting and autonomously responding to in-progress attacks in real time. These cyber immune systems enable the security team to focus on high-value tasks, can counter even machine-speed threats, and work in all environments. Read more.
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2:55pm3:35pm Wednesday, September 25, 2019
Location: 1E 14
Mark Hinely (KirkpatrickPrice)
The fear that comes along with new compliance requirements is overwhelming. Organizations don’t know where to start, what to fix, or what an auditor expects to see. In this session, learn what an auditor’s perspective is on the newest security and privacy regulations, how your business can prepare for compliance, and what the audit looks like from their perspective. Read more.
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4:35pm5:15pm Wednesday, September 25, 2019
Location: 1E 09
Jeff Zemerick (Mountain Fog)
This talk describes how open source technologies can be used to identify and remove PHI from streaming text in an enterprise healthcare environment. Read more.
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5:25pm6:05pm Wednesday, September 25, 2019
Location: 1E 09
Matt Carothers (Cox Communications), Jignesh Patel (Cox Communications)
Organizations often work with sensitive information such as social security number, and Credit card information. Although this data is stored in encrypted form, most analytical operations ranging from data analysis to advanced machine learning algorithms require data decryption for computation. This creates unwanted exposures to theft or unauthorized read by undesirables. Read more.
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5:25pm6:05pm Wednesday, September 25, 2019
Location: 1E 10/11
Alasdair Allan (Babilim Light Industries)
A arrival of new generation of smart embedded hardware may cause the demise of large scale data harvesting. In its place smart devices will allow us process data at the edge, allowing us to extract insights from the data without storing potentially privacy and GDPR infringing data. The current age where privacy is no longer "a social norm" may not long survive the coming of the Internet of Things. Read more.
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3:45pm4:25pm Thursday, September 26, 2019
Location: 1E 09
Owen O'Malley (Cloudera)
Fine-grained data protection at a column level in data lake environments has become a mandatory requirement to demonstrate compliance with multiple local and international regulations across many industries today. This talk describes how column encryption in ORC files enables both fine grain protection and audits of who accessed the private data. Read more.
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4:35pm5:15pm Thursday, September 26, 2019
Location: 1E 14
Mark Donsky (Okera)
California is following the EU's GDPR with the California Consumer Protection Act (CCPA) in 2020. Penalties for non-compliance, but many companies aren't prepared for this strict regulation. This session will explore the capabilities your data environment needs in order to simplify CCPA and GDPR compliance, as well as other regulations. Read more.

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