Two Recent LE Use Cases Case Study I Have A Bomb On This Plane (Miami Airport) In January 2012, an airline passenger tweeted she had a bomb on a Jet Blue commercial aircraft at the Miami International Airport. Within 3 minutes of detecting the Tweeted threat, a suspect was identified. TSA and FBI were immediately notified and the passenger was detained before the plane departed the gate. No bomb was found but the suspect did get her hashtag wish: #tostayinmiamialittlewhilelonger. Case Study 2012 SUPERBOWL Threat Just days before the 2012 Superbowl, "RulingElite" Tweeted he would carry out a biological attack designed to kill thousands of fans in the stadium. Out of one billion Tweets, our technology and tradecraft detected and reported this threat to authorities in real-time.
(Combining Social Monitoring with Social Analytics) Predictive Policing / Counter Terrorism Ingesting unrelated big data and finding the relationships!
Another Recent LE Use Case Asia Pacific Economic Cooperation (APEC)
Combining Social Monitoring and Analytics with Real-Time Dissemination (Professional Social Networking for the Public Safety Enterprise) Share new insights and knowledge across the Criminal Justice & Public Safety Enterprise
Looking Ahead We have an App For That! New Concepts - Public Safety App Store
Fire Department & Incident Command ebicard App Building Intelligence Mobile App to Upload Building Data Mobile Access to Retrieve Building Intelligence Real Time Updates Standardized Look & Feel Click On Map to Retrieve Building Data 2012 NFPA 1620 Standards 2015 IFC Emergency Preparedness Standards
The Competitive Advantage As the world continues to become more and more social competitive advantage will come to those who understand what s happening better than their peers and can directly connect it to their business outcomes and other useful pursuits. * The newly announced Big Data Research and Development Initiative. promises to help accelerate the pace of discovery in science and engineering, strengthen our national security, and transform teaching and learning by improving our ability to extract knowledge and insights from large and complex collections of digital data. *Source: How social media and big data will unleash what we know by Dion Hinchcliffe
What is Big Data? Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data effectively. Big data sizes currently range from a few dozen terabytes to many petabytes of data in a single data set.
How Big is BIG? Kilobytes (10 3 ) Megabytes (10 6 ) Gigabytes (10 9 ) Terabytes (10 12 ) Petabytes (10 15 ) Exabytes (10 18 ) Zettabytes (10 21 ) = 1,000,000,000,000,000,000,000 bytes = 1000 7 bytes = 10 21 bytes A zettabyte is equal to 1 billion terabytes. A zettabyte is equal to 1 million petabytes.
How Big is BIG? All the printed material in the world = less than 20 petabytes Currently Google processes about 24 petabytes of data per day. The estimated size of the digital universe in 2011 was 1.8 zettabytes. It is predicted that between now and 2020, this will grow 44 fold (or 35 zettabytes per year!
Data: Big and Small Circa 1975 Transaction Data Circa 2010 Cloud Data 2,000 users = Huge 2,000 users = Tiny Smaller Data Sets (bytes) Highly Structured and Homogenous Data -- Relatively small tables Absolute consistency required Big Data (petabytes) Unstructured, complex blobs (images, voice, video, logs) does not constrain to tables, columns and rows Application responsiveness & scale trumps consistency
The 3V Factor Model of Big Data Volume -- amount of data Velocity -- speed of data in/out Variety -- range of data types, sources Volume Variety Velocity
Big Data Analytics Scalability (the problem) Which are all of the relevant data sources? What are the characteristics of the different data sources? Where these data sources reside? What is the capacity of host platforms? What is the reliability of host platforms? How interoperability between host platforms is defined?
Big Data Analytics Scalability (the emerging solution) If it is particionable, it is hadoopable.
The Blurring of Public, External and Internal Big Data (the problem)
The Blurring of Public, External and Internal Big Data (the emerging solution) Data Marking and Classification will ultimately allow: Distinguishing between the level of fidelity of public, external and internal data in the context of a complex big data analytical model. Defining the nature of the analytical results and identifying the boundary between facts and intelligence Identifying the boundary between public data use, external data stewardship and internal data ownership.
Big Data Equals Big Security Threats (the problem) Just like this data is potentially valuable to you, also it is valuable to an attacker. Some 1,271 government organizations and 1,931 private companies work on programs related to counterterrorism, homeland security and intelligence in about 10,000 locations across the United States publishing at least 50,000 reports each year. Approximately 854,000 people hold top-secret security clearances ( nearly 1.5 times as many people as live in Washington, D.C. ). Source: Big data: Information security downsides (and upsides too!) Source: Washington Post
Security and Big Data (the emerging solution) Start Defining the Security Model Now Security should be the first concern and not the last one Discovery and Classification Bringing security closer to the data is critical to its protection Consistent Security Controls Centralizing the data leads to consistent security controls Auditing and Monitoring Watching users behavior is key to finding security bridges and data misuse trends Reduce Toxic Data Disposing of unneeded information and killing data reduces risk
Privacy Concerns (the problem) Much of this will look like Big Brother vacuuming up every scrap of people s behavior and knowledge and using in ways that were never intended.* It is about Technology, Policy, Legislature *Source: How social media and big data will unleash what we know by Dion Hinchcliffe
Privacy Concerns (the solution) Privacy policies and legislature specifically developed to target the problems introduced by big data Privacy policy automation to meet the requirement for large scale distributed application of policies
The Big Data Gap IT professionals estimate that they have less than half of the storage, computing, and personnel resources necessary to leverage big data for efficiency gains, better decision making.* Source: The Big Data Gap study sponsored by NetApp and performed by MeriTalk
The Demand for Social Media and Big Data A community driven capability Combines public safety and social media data Disseminates relevant, timely, hyper-local information First test case in Orlando, FL
Big Data and Social Media Collecting and combining data from Law enforcement regional information sharing programs License plate readers Cell phone data Other data sources
Types of Data in LE Systems
Big Data and Social Media Analyzing data in conjunction with social media Use of analytical tools to connect the dots Verify the data just as you would verify the LE data Trust but Verify
Taking It To the Next Level Example: East Coast Rapist Task Force Putting the information out to the public Websites, Billboards, Other possibilities Combining and Analyzing the Data