33C3 notes & keywords part 6
Post date: Apr 16, 2017 4:53:08 AM
- Corporate surveillance, digital tracking, big data & privacy - About: Surveillance, big data, corporate surveillance, big data, digital tracking, data broker. user privacy, private personal data. Analyzing and utilizing valuable data without consent. Corporate malpractices, what could possibly go wrong? Marketing bullsh*t terms. Hahah! Google, Facebook, Instagram and Twitter spying users. Ad networks, analytic services, social network sites, etc. Smartphone = Person Tracker. Collecting and selling personal information. Addthis, Bluekai, data collection services from Oracle. BlueKai, Datalogix, AddThis. Behavioral Data, Social Data, Purchase Data. Used for targeting, personalization and measuring. - That's one of the reasons why I personally prefer using addthis in a way, hit doesn't leak your data, unless of course you use the share feature. But by default, it's not being shared. Creating Efficient and accurate One Addressable Consumer Profile. Using Cloud Data Directory. Sources like: Acxiom, Infogroup, Neustar, Experian TransUnion, IXI / Quifax, Lotame, VisualDNA. Also Visa and MasterCard leak your purchase data. Not of course forgetting Google, Facebook, etc. Building Rich User Profiles. Allows excluding ethnic groups etc. How do they know and is it accurate? As example people are easy to target by: Ethnicity, Gender, Sexual Orientation, Political Views, Religion, Nicotine Usage, Alcohol Usage, Relationship, Drug Usage and if their Parents are Divorced. It's just data, it's not discrimination. Can we price your car insurance based on what you've liked on Facebook? Facebook credit score? WhatsApp shares data with Facebook. VisualDNA automatic Psychological Profiling on-line. (Personal note: Ouch, I wonder what they're saying about me. Hahah. Honesty, I really don't care.) Is it bad if line between marketing and risk analysis is being crossed? Interlinked databases form Networks of Corporate Surveillance. Spying data gets collected covertly, so users don't even know it's being collected. Types of data being collected: financial, contact, socio-demographic, transaction, contractual, locational, behavioral, technical, communications, social relationships. Especially collecting location data is very popular. Different data collection levels on mobile providers: Application level real time location. Interval based location snapshots.. Emergency Services Location. Granular network-based. Coarse cell-level network based. And of course high resolution indoor information based on beacons, WiFi, etc. Real-world behavior of mobile users surveillance based on observation graph. Matching users with Points of Interest. - Obvious question how interested intelligence services and law enforcement are about this? - Highly accurate audience profiles. - Also Stasi would have loved this kind of technology. - Separating between first-party data and third-part data. Marketing Segmentation. Credit Scoring. FICO Score (ficoscore). TransUnion Trustev. ID check, Address, Email, Telephone, Financial History, Behavioral, Location, Device, Mobile, Machine learning, Identity, Digital Data, Fraud Scoring. Typical Patterns, Past Reputation, Cross Merchant History, Network deep location. OS, Browser, VM, etc. White, gray , black lists for the identity. - Afaik, that's all pretty obvious. I'm doing all thet with some projects, yet using pretty simple algorithms. But the source data is there. - Four weeks of your call history, is enough to tell your credit history (?), pretty interesting claim. Predicting user character traits from smartphone metadata. Is user neuroticism, extraversion, openness, conscientiousness, agreeableness. Etc. With of course varying prediction accuracy. Data Mining, Mathematics, Statistics, Machine Learning. Zest Finance uses thousands of data elements to calculate credit scores. They co-operate with Baidu. More data is always better. All data is also credit data. Infobase-X. Basic data like: Credit History, Driving History, Criminal History, Residential History, Employment History, Education History. Income History, Credit Cards, Properly Data, Vehicle Daa. Purchase Behavior, Life Events, Voter Party, Health Information, Personal Interests. Name, Address, Phone, Email, Birth date, Gender, Ethnic Code, Martial Status, Childer. - Yep, sounds like pretty public basic data, ahem. - LexisNexis Risk Solutions. Healh care solutions where Social Network Analytics Reveal Hidden Relationships. Delinquent prediction. Plantir. PayPal Fraud Detection. SCL Group. Targeting and data-driven communication. Defence/Intelligence: Information Operations. Elections: Microtargeting for political campaigns. Classifying users on political views like: Pro-Life, Environment, Gun Rights, National Security, Immigration. Marketing Technology Landscape. Mobile Marketing, Digital Asset Management, Display Ad Management, E-Commerce, Loyalty management, Marketing Automation, CRM, Email Marketing, Social Media, Data Analytics, Business Intelligence (BI), Multi-channel marketing. Agile project management. TellApart - Predictive Marketing Platform. Customer Value Score. Allowing Dynamic Promotions. Right person at the right time. Personalized Pricing. Price Discrimination. "Rich see a different Internet than the poor" - Michael Fertik . Filter Bubbles. Anonymous identifiers derived from email addresses, phone numbers and credit card numbers. Pseudonym != Anonymous. Google Advertising ID, Apple IFA / DFA, Microsoft ID, Orcale Identity Graph, Acxio AbiliTec Link, Verzon Precision ID, Experian AdTruth ID. Data Management Platform (DMP) = real-time online data marketplace. Providing a central hub for data aggregation, integration, management and employment and disparaging different sources of data. Collecting enw data using tags and web bugs. Analyzing and categorizing people in different segments and audiences. Grouping people to lookalikes. DMS providers: Liveramp, BlueKai, eXelate, Krux, Lotame, Adobe Audience Manager, Rocket Fuel, Turn DMP, etc. What should we do about all this? DataDealer.com - link - An online game that explores the personal data ecosystem on the Internet. Networks of Control is a report on corporate surveillance, digital tracing, big data & privacy. Tracking the trackers about health, discrimination, data brokers, tracking ,algorithmic decisions, apps, employment, profiling, IoT, privacy, big data, personal data, surveillance, wearables, smartphone, credit scoring, analytics and regulation. Data collection and analytics should be transparent. There should be strong regulation to protect privacy. Support of decentralized, privacy-aware technology. Privacy-aware open source components & business models. (Nuff said!) - This was awesome talk. And provider so much information. Which of course wasn't anything new to me. But it's good to know that 'predictions' are ell coming reality.