Law Enforcement Intelligence

LAW ENFORCEMENT INTELLIGENCE 1

LawEnforcement Intelligence

UniversityAffiliation

ActionableIntelligence

Actionable intelligence refers to information that is crucial inmaking decisions (Can`t we all just get along?, 2007). Lawenforcement agencies gather plenty of data from virtually unlimitedsources. Information is derived from sensors, alarms, video cameras,social media, and smartphones. Public safety agencies have aheightened ability to acquire data from various sources (Reducingcrime through intelligence-led policing, 2012). However, it isdifficult to operationalize data to obtain actionable intelligence.

As a patrol commander in a high-crime district, it is essential togather information on criminal activities. In this regard, viabledata is obtained from 9-1-1 calls, multimedia messages, radio trafficand video feeds (Reducing crime through intelligence-led policing,2012). Police departments need to adopt innovative ways of capturing,correlating, and sharing such information. Subsequently, it will bepossible to derive actionable and usable intelligence. Real-timetechnology plays a fundamental role in analyzing bulk amounts of data(Can`t we all just get along?, 2007). Previously, disjointeddatabases and paper reports made it quite strenuous to accessrequired information. Nonetheless, advanced forms of technology havemade it easier to develop actionable intelligence.

Local crime databases, arrest records, incident and criminalcomplaints and video inputs can be meshed to provide a real-timeoperational view (Reducing crime through intelligence-ledpolicing, 2012). Actionable intelligence can be used byanticipating crowd formations within the city. Advanced sensors andvideo analytics can also detect gunshots in the neighborhood.Consequently, patrol teams will benefit from an additional layer ofactionable intelligence. In this regard, a badged officer canintegrate multiple streams of data into one unified view. Firstresponders in the field are also provided with information on theprogress of particular incidents (Reducing crime throughintelligence-led policing, 2012). In this manner, a patrolofficer can contribute to the successful handling of volatilesituations.

Actionable intelligence can also be applied to ensure that largersections of the city are covered using the same resources. Wirelessvideo networks and other applications deliver high-speed access todata and images (Reducing crime through intelligence-led policing,2012). Public and private security cameras can also be coordinated toprovide real-time insight into criminal incidents. Surveillance canbe deployed in high-risk areas, dangerous intersections, commercialdistricts, municipal buildings, and crowded public events (Reducingcrime through intelligence-led policing, 2012). Consequently,officers can be dispatched immediately whenever a problem isdetected. Notably, reducing the response time maximizes crime-solvingand ensures optimal use of resources.

Besides, a patrol officer can use actionable intelligence to liaisewith detectives and other members of law enforcement. Integratedinformation is made available to all agents as investigative support.Such comprehensive details are provided to identify crime patternsand eliminate time-wasting steps. Up-to-date information also helpsto reduce the resources spent on police investigations. Actionableintelligence can also be applied to increase conviction rates. Inmany instances, criminals are released due to the lack of conclusiveevidence (Can`t we all just get along?, 2007). Hence, suchpeople are highly likely to perpetrate additional crimes.Nevertheless, actionable intelligence acts as substantive proof incourts. In particular, security cameras provide irrefutable videoevidence to establish an assailant’s guilt beyond a reasonabledoubt.

Actionable intelligence can also be used to increase closure rates.Some cases are impossible to solve due to the lack of proper evidence(Reducing crime through intelligence-led policing, 2012).Other criminals are also difficult to track since they move acrossdifferent regions. However, actionable intelligence integrates aperson’s sightings in various places to establish trends andpredict future movements (Reducing crime through intelligence-ledpolicing, 2012). In this manner, the chief’s expectations willbe fulfilled.

OperationalSecurity Program

An effective operational security program plays a crucial role in alaw enforcement narcotics strike unit. For example, it helps in thecoordination of efforts among police officers. In particular, agentsin the narcotics strike unit have to complement each other while theytrack the movement of drugs (Gibbs, McGarrell, &amp Sullivan, 2015).In many instances, the success of drug enforcement officers isdependent on their discretion. Notably, surprise raids lead to thecapture of many peddlers and other users. On the other hand,criminals with advance information can avoid detection by policeofficers.

The presence ofan ineffective operational security program would cause variousproblems. For example, it would create inefficiencies in howinformation was gathered and shared among the relevant stakeholders(Gibbs et al., 2015). Furthermore, it would become difficult toproduce actionable information from diverse sources. Drug gangs areusually secretive and procedural such that law enforcement agentsstruggle to obtain viable details (Gibbs et al., 2015). Hence, manyofficers opt to infiltrate such networks through undercoveroperations. The lack of an effective security program endangers thesafety of such agents. It is vital to coordinate background checksand criminal profiles to appear authentic (Gibbs et al., 2015).Furthermore, confidential informants can be exposed when theoperational security program is ineffective.

Additionally, it limits the understanding of the links andrelationships between items and entities. Electronic documents,reports, and statements are used to capture secret communicationamong different drug barons. Distribution networks are alsomaintained along with human trafficking operations. Many drugpeddlers use illegal immigrants to conduct their business since suchpeople experience terrible circumstances (Gibbs et al., 2015). Inthis regard, the lack of an effective operational security programundermines the unit’s capacity to establish connections amongvarious criminal groups (Gibbs et al., 2015). It also impedes trendanalysis and crime analysis whenever predictive forecasting isrequired to provide actionable information.

Notwithstanding, some operational security measures can be undertakento reduce the impact of these challenges. For instance, it is properto establish skillful planning as the first priority. The narcoticsunit can utilize existing technology to enact intelligence-ledpolicies. Law enforcement agents are also required to assess anddevelop sufficient technology solutions (Gibbs et al., 2015).Critical shareholders must be consulted to provide input into theprograms of the narcotics unit. Police officers also need adequatetraining to act stealthily without alerting criminal gangs ofimminent raids and other swoops (Gibbs et al., 2015). Drug peddlerscould discard or destroy their merchandise if they were aware ofimpending checks. Therefore, it is important to develop systems whereundercover operations are coordinated and protected.

Furthermore, it can help to make plans of how to integrate thefunctions of both new and existing technology. Intelligence-ledsafety solutions would endeavor to safeguard civilians from thedangers of drug possession (Gibbs et al., 2015). Recovering addictscan be used to show the endless possibilities open to people whochoose to overlook intoxicating substances. Educational campaignscould also be held to inform the public of the appropriate methods ofcollecting and analyzing data (Gibbs et al., 2015). Consequently, anefficient operational security program would have major effects in alaw enforcement strike force unit.

Sharingof Intelligence

The 9/11 attacks exposed weaknesses in the U.S. intelligence network.Despite the unlimited resources, surveillance and other responsemechanisms had failed to prevent a hijacked plane from crashing intothe World Trade Center. The massive civilian casualties from theseattacks forced intelligence agencies to share information pertinentto the case at hand. Stringent measures were also enacted to preventfuture occurrences.

Since the 9/11 terrorist attacks, there have been severalhigh-profile incidents where law enforcement agents collaborated toensure a successful joint operation. In September 2016, someexplosives were discovered in particular areas within New York Cityand New Jersey (Perez et al., 2016). In fact, a pipe bomb explodedalong the route of a charity can in Seaside Park. A few hours later,a homemade pressure cooker bomb detonated near the Chelseaneighborhood in Manhattan. Other explosive devices were discovered atthe Elizabeth train station. Although there were no fatalities,several people were injured in the attacks (Perez et al., 2016).Unsurprisingly, panic spread among New York and New Jersey residentsespecially given the infamous 9/11 catastrophe.

Several intelligence agencies cooperated to mitigate the threat posedby the bombs. Some of these organizations include the Federal Bureauof Investigation (FBI), Homeland Security, Joint Terrorism Task Force(JTTF), and the Bureau of Alcohol, Tobacco, Firearms and Explosives(ATF). The New York Police Department and the New York City FireDepartment (FDNY) also participated in the investigation (Perez etal., 2016). Admittedly, the Manhattan and Seaside Park bombings wereinitially viewed as separate incidents. Nevertheless, frequentsharing of information revealed similarities in the findings fromboth investigations. Hence, the FBI determined that the attacks wereperpetrated by the same assailant. Hours later, various agenciesissued a statement to claim that the explosions were intentional(Perez et al., 2016). Subsequently, links to natural gas, arson, andvandalism were explored and discredited.

Further investigations revealed that both Manhattan bombs had thesame structural design. The NYPD received a 9-1-1 call reporting thepresence of a suspicious package. Next, the FBI extractedfingerprints from the pressure cooker bomb on West 27thStreet. Pictures on the mobile phone were matched to Ahmad KhanRahimi (Perez et al., 2016). Notably, the traced prints also belongedto the same person. The man’s online behavior was examined toreveal patterns of dubious conduct. In particular, Ahmad hadpurchased several bomb ingredients from eBay in the preceding months.Ahmad’s YouTube account also showed that he had been radicalized byjihadist groups to perpetrate the lone-wolf attacks (Perez et al.,2016). Surveillance videos also showed the suspect planting severalbombs on West 23rd and 27th streets.

Law enforcement agents released images of the suspect to variousmedia outlet while urging all residents to remain calm and keep intheir houses. An individual placed a call to the police who werequick to respond and hence confront the suspect. Ahmad was arrestedand charged with wounding some police officers during a shoot-out(Perez et al., 2016). This incident highlights the positive resultsthat are experienced when intelligence sharing led to a successfuljoint operation leading to arrest.

OpenSource Intelligence

Open source information refers to intelligence gathered from publiclyavailable sources including media and journals. Law enforcement unitsface several ethical dilemmas when contemplating the use of suchdata. Firstly, police officers contend with issues of intellectualproperty protection (Lomas, 2014). In particular, law enforcementagents wonder whether human knowledge is enhanced by the free andfull access to information. Open sources contribute to the easyavailability of data concerning persons of interest. Although policeofficers can acquire plenty of information, the lack of protectionfor intellectual property places doubts on authenticity (Lomas,2014). Therefore, law enforcement agents cannot differentiate betweenaccurate and falsified details.

Open source intelligence also contradicts the requirement to exercisepersonal rights without infringing those of others. Law enforcementagents struggle while considering whether to acknowledge thedevelopers of such information (Lomas, 2014). The data available fromopen source intelligence should be used responsibly. On the otherhand, such information is unrestricted and hence seems to allow forunlimited self-expression (Sampson, 2016). In this manner, lawenforcement agents have to examine whether they have the indisputableright to use open source intelligence.

In many instances, developers are expected to provide theirintellectual product without restrictions. Contrariwise, otherproducers and inventors would not be required to extend the samebenefits. In this regard, law enforcement agents grapple with issuesof fairness. Many police officers wonder whether it is proper tobenefit from something that was made publicly available (Lomas,2014). Consequently, some law enforcement agencies are inclined tomake financial contributions to software developers. Admittedly, thecreators of open source software incurred substantial expenses whiledeveloping their content (Lomas, 2014). Therefore, it would seem fairwhen intelligence units cater for a portion of such costs.

The common good perspective requires the use of informationtechnology in a manner that manifests a resolute commitment tosolidarity. Additionally, the cyberspace is viewed as a source ofcomprehensive data without charge to all users (Sampson, 2016). It isassumed that the information contained in open sources was beyond thecontrol of the wealthy elite. However, it is likely thatmultinational corporations have also utilized the opportunity toextract useful information. In some circumstances, the available opensource intelligence would not guarantee common good (Lomas, 2014).Hence, law enforcement units must weigh all the factors involvedbefore making a decision whether to utilize such information.

Additional ethical issues arise in the sharing of information amongpolice officers. Data concerning a particular event or person maycontain sensitive aspects. Moreover, sharing personal details isparamount to consenting to its theft. Open source intelligence occursdue to ingenuity and effort (Sampson, 2016). Therefore, lawenforcement agencies contemplate whether they would share informationacquired from publicly available platforms. Moreover, open sourceintelligence lacks intrinsic value. The easy availability ofinformation over the internet creates loopholes whereby actionableintelligence is impossible to obtain. For example, law enforcementunits may need to plan on how to handle certain matters of publicimportance. Secrecy is essential to safeguard the government’sprocedures and policies (Sampson, 2016). On the other hand, materialthat is used to make fundamental decisions comes from publicwebsites. Consequently, law enforcement personnel encounter plenty ofdilemmas while using open source intelligence.

References

Can`t we all just get along? Improving the LawEnforcement-Intelligence Community Relationship. (2007).Washington, DC. Retrieved fromhttp://ni-u.edu/ni_press/pdf/Improving_the_Law_Enforcement_Intelligence_Community.pdf

Gibbs, C., McGarrell, E., &amp Sullivan, B. (2015). Intelligence-ledpolicing and transnational environmental crime: A process evaluation.European Journal of Criminology, 12(2), 242-259.http://dx.doi.org/10.1177/1477370815571947

Lomas, D. (2014). Open source intelligence in a networked world.Journal of Intelligence History, 14(1), 76-77.http://dx.doi.org/10.1080/16161262.2014.941524

Perez, E., Prokupecz, S., Wills, A., Grinberg, E. &ampYan, H. (2016,September 21). Suspect wrote `bombs will be heard in the streets,`authorities say. CNN. Retrieved fromhttp://edition.cnn.com/2016/09/20/us/new-york-explosion-investigation/

Reducing crime through intelligence-led policing. (2012).[Washington, D.C.]. Retrieved fromhttps://www.bja.gov/publications/reducingcrimethroughilp.pdf

Sampson, F. (2016). Intelligent evidence: Using open sourceintelligence (OSINT) in criminal proceedings. The Police Journal.http://dx.doi.org/10.1177/0032258×16671031