Online Surveillance - Modern Day Policing

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Online Surveillance: Modern Day Policing:

Online Surveillance: Modern Day Policing Oton Ukaj PAD 747 John Jay College of Criminal Justice

Types of Intelligence:

Types of Intelligence Open Source Information that is readily available to the public without having to resort to covert means of accessing it (hacking, wiretapping, etc.) Most of the online surveillance material is considered open source Social Media user-generated content is one of the most valuable open source categories Most of the content becomes quite accessible to a surveillance operator Closed Source Material Enhanced security measures Not intended for public exposure Phone texts, email, etc.

Open Source vs Closed Source:

Open Source vs Closed Source PROS CONS OPEN SOURCE Few legal barriers – less intrusive Not targeted requiring much investigative review Openness allows for more accountability Great in volume CLOSED SOURCE More valuable per unit Requires court proceedings for access Allows for potential access to secretive info Much more intrusive – hence the probable cause requirement

Lateral Surveillance:

Lateral Surveillance The concept that a government uses citizens to do the surveillance legwork and gather information on each other Historically, this was done by recruiting government spies and informants to spread their information net In modern society, the Internet is the ultimate LS engine, because people can ultimately participate without their knowledge Examples: See Something, Say Something, Vancouver Hockey Riots

Intel flow:

Intel flow Intelligence can flow top-down or start from the bottom Task Forces Large national databases with data provided to other agencies (Rissgang, Terrorist Identities Datamart Environment) Gang intelligence is heavily reliant on local officials Lateral intelligence sharing is also common CalGang – California’s statewide gang database with numerous participating agencies at all levels

Social Media Role in Investigations (2014):

Social Media Role in Investigations (2014) Note: Adapted from "Survey of Law Enforcement Personnel and Their Use of Social Media” by LexisNexis Risk Solutions, 2015, https://www.lexisnexis.com/risk/downloads/whitepaper/2014-social-media-use-in-law-enforcement.pdf

Internet Activities Surveilled:

Internet Activities Surveilled Much of the OS intel material is derived from people communicating on the net for a joint purpose (groups) Terrorism The growth of terror groups, such as ISIS, is partially attributed to online recruiting and propaganda In 2009, Army Major Hasan killed 13 people in attack, after communicating online with Islamic clerics

Internet Activities Surveilled (cont’d):

Internet Activities Surveilled (cont’d) Organized Groups (gangs, hate groups) Use the internet at 25% more than general population ( Pyrooz et. al, 2015) Rely on the internet to communicate with fellow members or rivals Spread their message Enhance their image Recruit Initiate/maintain disputes with rivals Upload videos

Surveillance Methods:

Surveillance Methods Human Intelligence Primary collector is an investigator or analyst The targeted approach provides for better quality information Forums include social media and chat rooms Used in conjunction with patrol duties and field surveillance

Social Media and Internet Surfing:

Social Media and Internet Surfing No standardization for investigative procedures Intelligence often begins with one person of interest From there activity (pictures, comments, hashtags) associated with subject leads to other intel interests A social network is established for analysis Case study (Patton et. al, 2016) shows that gang members can be very specific and descriptive at times with their online threats Cyber undercover operations

Data Mining and Bulk Collection:

Data Mining and Bulk Collection Data Mining Analysis of data to discover patterns Bulk data collection based on keywords and associations Less subjective targeting Capability to analyze a broader spectrum of targets Difficult in translating data into workable analysis, given complex nature of human networks and communication A combination of both is beneficial Data mining protocols to alert officials of emerging trend activity, but allow a human data processor to evaluate info and interpret meaning

Conclusion:

Conclusion Decentralization Provides for more tailored investigations Localized experience and expertise is key Qualitative analysis instead of focus on numbers Activity driven pattern analysis, instead of mere association Updated information about on the ground conditions A combination of data mining with human intelligence capability

Thank You !:

Thank You !

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