It’s Time to Incorporate OSINT into Crime Analysis

Date Posted: May 23rd, 2023
Technology

August 22, 2023

By Johnmichael O’Hare, Director of Business Development, PenLink

Crime analysts need a variety of tools and data to support tactical, strategic, and investigative initiatives in law enforcement agencies.

The International Association of Crime Analysts (IACA) has identified several types of crime analysis that are performed by law enforcement as part of their profession: Tactical, Strategic, Administrative, and Investigative. Crime analysts retrieve and analyze data from record management systems (RMS), computer-aided dispatch (CAD) systems, inmate management systems, and case management systems, integrating that data with data sets from public and government records to provide executives, officers, and detectives with actionable insights to protect and keep communities safe.

Open-source intelligence (OSINT) data is an important component of this ecosystem that can enrich investigations and help generate the insights law enforcement executives and officers need to keep communities safe and to solve crimes. Too often crime analysts think that OSINT is just about conducting manual searches to find someone’s online presence. They do not realize that OSINT can open many more intelligence-rich doors, tapping into a wealth of information about the people, places, and events being investigated.

Crime analysts who solely rely on internal law enforcement databases are missing the full picture when analyzing a crime, person, or location. Even if they couple that data with manual online searching when performing any of the four types of crime analysis, vital information is often missed. Moreover, there is no context in the police report or CAD records because it is a singular snapshot of an event or person. Interviews by detectives after the fact can provide additional context. However, in this interconnected world where so much information is publicly accessible online, as well as in forums in the deep and dark web, digital footprints can add context investigators’ need to solve cases. This is where OSINT can have a real impact on investigations and aid in the response or deployment of officers.

OSINT Provides Valuable Context for Crime Analysis

But how do crime analysts incorporate data derived from OSINT solutions into their workflow to support crimefighting measures and investigations? An automated OSINT tool can not only provide that additional context but can automate the process and dig deeper beyond the publicly accessible online platforms, finding information in areas many analysts do not consider searching as part of their analytical efforts.

An artificial intelligence (AI)-powered, automated OSINT solution helps provide context to these three areas of a criminal investigation: person information, location data, criminal data.

Person Information: OSINT can assist law enforcement by providing insight into a victim or suspect’s personality or pattern of life before, during, or after a critical event. For example, their digital footprint can help analysts understand more about their interests, friends, colleagues, and family, potentially tying them to specific activity, connections to a victim, or an alibi. Analysts cannot obtain this type of unique background information from an internal document or database.  Investigators may also never collect this information from interviews or canvassing at a scene.

Location Data: Location information can be gathered from digital media to give analysts additional information about ‘who and what’ is at a specific location or what is being said from or about a location. For instance, if a protest is happening at a location in a certain city, an analyst can scour the web for timely information shared online in forums or in chats regarding protest activity.   The intelligence gathered from these online sources would likely never be found in official police records. Analysts can use OSINT in a proactive way to find out who is talking about a location or event online. By taking all available data – geospatial, RMS, public records, OSINT – law enforcement is better equipped to mitigate and respond to incidents with comprehensive analysis and intelligence from all these sources.

Criminal Data: Crime analysts can go beyond RMS data and case management notes with OSINT. They can find information about stolen goods online, as well as chatter about criminal activity and threats to commit a crime. Organized retail crime can be analyzed by supplementing incident reports with data from online marketplaces, virtual garage sales, or illegal storefronts operated by “fences.”  This provides additional data related to the organized retail theft supply chain that does not exist in an RMS. By supplementing the RMS data analysis about a series of crimes or patterns with OSINT, analysts can provide detectives with meaningful information to help recover losses and close the case.

The Bottom Line – Marrying Crime Analysis and OSINT

In today’s interconnected world, it doesn’t make sense to focus on manual searching and analysis without automation and integration of data and tools. OSINT paired with crime analysis provides valuable data about people, places, and groups, adding more context to data collected in disparate criminal justice management systems and databases. An AI-powered, automated OSINT solution ties data from all levels of the surface, deep, and dark web, allowing analysts to integrate that intelligence with law enforcement data in a cohesive manner to solve crimes and better protect our communities.

Johnmichael O’Hare, Director, Business Developtment, PenLink

Lieutenant Johnmichael O’Hare retired from the Hartford Police (CT) in 2018. His career elevated investigative units that specifically attacked narcotics and firearms violence. In 2013, he was tasked with creating a Real-Time Intelligence Center that could support critical functions & provide analytical and forensic back support. He currently serves as a Director of Business Development at PenLink with a focus on Threat Network Identification & Interdiction in the Web Intelligence Realm.

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