Big Data for Public Safety: 4 use cases for intelligence and law enforcement agencies to leverage Big Data for crime prevention.

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1 Big Data for Public Safety: 4 use cases for intelligence and law enforcement agencies to leverage Big Data for crime prevention.

2 I m not going to get more money. I m not going to get more cops. I have to be better at using what I have, and that s what predictive policing is about If this old street cop can change the way that he thinks about this stuff, then I know that my [officers] can do the same. Charlie Beck Los Angeles Police Chief Share this ebook: 2

3 1 Social Network Analysis In spite of more recent changes in the way that we communicate, the intelligence community has always employed of intelligence operation required many operatives recording the movements of individuals and their communications. Today this information trail is digital. From telephone records to Facebook posts, to s, the actions of a criminal enterprise or terrorist network are being recorded as strings of structured and unstructured text. Not only does law enforcement need to adjust to the digital paper trail by developing digital analysis tools, but the entire structure of police and intelligence work must change the way that personnel think about criminal and terrorist communications. These technologies have already begun to trickle down from larger federal agencies down to City and State intelligence and law enforcement agencies. Major cities have implemented social data suspects. New techniques are emerging that will help investigators get to an answer faster, identifying and ranking information the investigators 3

4 Some social media monitoring companies do a great job of measuring volume of opinions and sentiment, but none of them allow you to get to key influencers. For intelligence, it is critical that we identify and isolate individuals and networks in the social graph that will cause unrest. That s the distinction. Anonymous Emcien Intelligence Partner Share this ebook: 4

5 2 Connecting Seemingly Unrelated Case Files There was a time when seemingly disparate cases were connected only through the reasoning skills of investigators. Today, case management software and analysis technologies allow zones, structured data system, allowing investigators to search that content for connections between crimes, locations, and individuals. With this search ability, investigators can come up with, and verify, their suspicions more quickly than ever. type of crime or an individual suspect can be accessed almost cases they are working on with cases that have not one attribute in common, but that match two, three, or more relevant attributes. These advances lead to a greater degree of accuracy related and ranked based on their content, telling users not only that the documents are related, but to present them in a list ranked by how closely they are related. departments, these documents are automatically connected by the key words and phrases they contain. 5

6 3 Some Crime Prediction Modeling of the most exciting advances in law enforcement have come from the combination of various data sources to create a model for predicting criminal behavior. Given enough data, these models can make reasonable predictions of when and where crime spikes will occur. Proactive agencies can then use these predictions to divert enforcement resources to the locations and times that are likely to see increased crime, in essence preventing crimes before they happen. but today digital records can be reviewed, queried, and modeled to more easily extract valuable information. Today, departments can explore the trends and relationships that exist between the surrounding circumstances and the criminal act itself. With the ability to understand the nature of crimes across time, location, and many other factors, law enforcement and government representatives can begin to address the root causes of crime spikes rather than being reactive to crimes. 6

7 New technologies keep the leadership up to speed on what s happening where, if not in real-time, than at least in a very recent time frame. It allows management to analyze, organize and respond in an efficient manner. Ralph Taylor Temple University criminal justice professor and crime researcher Share this ebook: 7

8 4 Network Oversight and Cyber Security There are no easy parallels for the rapid scaling of data that governments, businesses, and agencies must protect. As physical paper files have been replaced with digital, these records are available almost anywhere around the world, sacrificing security for the sake of convenience. Governments that do keep pace with advances in modern technology are collecting and storing all kinds of sensitive data. Personal data, financial data, and even intellectual property must be distributed across local networks and between corporate partners. Widespread access leaves this sensitive information open to threats from foreign governments, hackers and hacktivists, and private companies looking for competitive advantage. Botnets, backdoors, rootkits, trojans, and worms are the tools used by these bad-actors to infiltrate the sensitive data collected by governments. Addressing these intrusions has become an ongoing game of chase, with intruders adapting new methods as companies and law enforcement catch on to their schemes. For each advancement in fighting cyber crime the criminals adapt with new ways to cover their tracks or extract information without being detected. 8

9 Mitigating Threats to Safety by Leveraging Data The modern trail of breadcrumbs is no longer entirely a physical one investigators must now be scouring both the physical and the digital realms to keep pace with today s bad actors. The Emcien technology suite helps law enforcement and intelligence agencies by automatically mapping connections in data, revealing the connections between documents, people, recurring events and the circumstances that lead to events that threaten security, safety, and property. EmcienScout offers automatic pattern detection for unstructured machine data and human generated text data. Emcien s pattern detection enables: Anomaly detection in machine data to reveal suspicious network traffic Automatically map the connections between documents to link case files and evidence documents Identify the factors that lead to spiking criminal activity Analyze social data and correspondence to create a network of bad actors, identifying the most influential individuals and their followers Automated fraud identification and investigation tools Request a Live Demo Share this ebook: 9