Technology for Law and Enforcement Agencies

8/9/2019 Technology for Law and Enforcement Agencies

1/12

DI Technology for Law and Enforcement agencies

Mob. No. +91 9215019797 -- www.nimblespy.co.cc-- [email protected] Page 1

Whitepaper on DI Technology for Law and Enforcement agencies

By

Yogesh Vats & Deepak Rathore


2/12



Contents:

1. Introduction ...................................................................................

2. The Problem ...................................................................................

3. DI Technology ..................................................................................

3.1 Data Warehousing .........................................................................

3.2 Data Mining ...................................................................................

4. Architecture .....................................................................................

4.1 Hardware Architecture ..................................................................

5. Features ...........................................................................................

6. Advantages ......................................................................................

7. Case Study .......................................................................................


3/12



1. Introduction

The world is becoming digital by the day for good as well as bad

We live in an age where most of the information is raw digital data. The

information may consist of images from a satellite orbiting our planet, a credit

card transaction verification system or our criminal or interrogation reports.

However the problem with all kinds of raw data remains the same - What to do

with all this data?

The value of raw data is typically predicated on the ability to extract higher levelinformation: information useful for further investigations, decision support, for

better understanding of the crimes plaguing a state, for storage of all data in a

structured format.

Day by day more and more data is being piled up so what should we do with this

data? The answer lies with the problem itself. Since we have this data we can use

it to its own advantage by using data mining and extracting useful information it

The process ofData Mining To analyze data and find hidden patterns in it has

been in vogue since centuries. However, with the rapid increase in the inflow of

unstructured digital data, sophisticated statistical analysis and modeling

techniques are now used to generate patterns and relationships hidden in raw

data.

Today, multiple Law Enforcement agencies across the world are using statistical

analysis and pattern matching to catch suspects and criminals or just to draw

intelligence out of the humongous quantity of raw data available with us.


4/12



2. The ProblemCriminals leave their traces behind huge amount of data however manual

analysis of this data usually takes more time than it took to gather the data

As the focus on extracting intelligence from raw data has sharpened, Law

enforcement agencies need information that allows for quick action at all levels.

However, most of our agencies have fragmented systems and maintain

information in disparate systems, thereby making it difficult to find and access

the right piece of information quickly. Reports can take days or weeks to produce.

Answers to queries vary, based on which system is used.

The problems

Digitization of current data A typical law enforcement agency has manyoperational systems that capture and report crime-based information. The

challenge is to digitize this data, integrate data from fragmented systems

to provide a single view thereby increasing the ability to analyze crime

trends using data from all systems, accurately

Non-clustered Databases Most of the current records (for instance, FIR,Investigation Report, Missing people register, Auto thefts etc) have

separate databases of their own with multiple common and some unique

parameters. Multiple attempts at digitizing these fragmented databases

has lead to duplicity of data, redundancy, data integrity and non reliability

issues

Data Analysis The rapidly increasing inbound flow of raw data has createdthe need for automated extraction of useful knowledge from hugeamounts of data which not only helps in finding new information about the

criminals, their associates or modus operandi etc. but also helps in better

understanding of them and their activities


5/12



3. DI TechnologyUnlock your data

For any country the biggest problem with digital data is how to create it, how to

store it and how to analyze the data. The typical police department has many

operational systems that capture and report crime-based information. The

challenge is integrating data from fragmented systems to provide a single view ,

finding the ability to analyze crime trends using data from all systems,

accurately reporting crime statistics, and complying with state and federal

reporting requirements.

3.1Data Warehousing

DI Technology is designed and developed to maintain the details pertaining to all

the activities of the Police Stations relating to Crime and Criminals. The details are

stored in a cluster of databases so as to ensure

Flexibility The system has been designed keeping in mind therequirements of a state police department for the next ten years. Thesystem is flexible and new modules can easily be integrated or deleted

from the system without much ado.


6/12



No duplicity of data Using the self developed clustered databasestechnology, DI ensures that data once entered never needs to be

replicated. For instance, certain information such as names, address,

associates, modus operandi may be common to both FIR as well as

Investigation report. Now instead of entering these details in both the

databases, database cluster has been used to ensure that the data in

entered only once and automatically linked to other databases

Data integrity issues DI Technology integrates your existing data into anew repository of consistent, accurate information without modifying

your existing operational systems. Data entered is consistent in nature

with guaranteed data integrity and availability

Report Generation - Easy-to-generate reports greatly reduce the technicalskill and time needed to produce information that can be used to make

key decisions quickly. The DI Technology helps in digitizing the current dataand generates reports as per the user requirements. The reports may be

generated on the complete profile of a criminal, incidence of a certain

crime within an area, year to year crime trend, crime patterns and trends .

The system provides required information to the higher levels periodically

and as and when required. The system also generates various statutory

reports for the smooth functioning of the police station.


7/12



Quick and easy retrieval of information in multiple views DI Technologyenables the quick and easy retrieval of information permitting officers or

crime analysts to spend their time gaining insight rather than dealing with

complex data access issues. Structured to support analysis and decision

making throughout the organization, the solution integrates data into a

new repository of consistent, accurate information, which is then

presented in multiple business views, including offenses or incidents,

dispatch and arrests

Dynamically sort data by relevant dimensions location, date, signal,incident priority, relationship between offender and victim, relationship

between parties involved in domestic violence, and call-for-service holding

time Create and quickly distribute presentation-quality charts and graphs.

3.2Data Mining

The value of raw data is typically predicated on the ability to extract higher

level information which leads to the need for automated extraction of

useful knowledge from huge amounts of data. Knowledge discovery and

data mining are techniques to discover strategic information hidden in verylarge databases

Algorithms used

An user friendly search filter, customizable relationship layouts likeo Tree layouto Ring layout

Data mining algorithms usedo Statistical based

Regression Bayesian


8/12



o Distance Based Simple K nearest neighbors

o Neural Network Based Propagation NN supervised Learning

o Rule Based Generating rules from Decision tree Generating rules from Neural network

o Association Techniques Sampling

oPartition algorithms

Minimum spanning tree PAM algorithms

Database clustering using BIRCH, DBSCAN & CURE algorithms.Logical analysis is done using Data and Task parallelism algorithms The application

is programmed to perform investigative analysis on the data stored in data

warehouse. The application will be setup to automatically identify the data from

the input media and alert the administrator about the input option. The

application also maintains an index of each database and correlates the

information so that the search takes place faster and easier.


9/12




10/12


11/12



5. Features Software designed using state police departments requirements in

view Flexible thresholding User friendly GUI Interface High level of security (Multifactor Authentication) Possibility of connectivity between district, state and police station

databases

Reduces repetitive manual work System helps officers

o Draw Patterns and analyze a given situation graphicallyo Draw links and associations between multiple entitieso Link past crimes of an individualo Analyze the progress on a particular caseo Study and analyze crime trends in respective jurisdictions

6. AdvantagesThe main objective behind developing and completing this product was to

help our Law Enforcement agencies save their energy and the time which

goes into manual analysis of the humongous data which most of the time

does not lead to fruitful results. The product not only does the analysis but

helps in creating a database which serves the objective. The automated

tool leads to discovery, extraction and linkages of sparse evidence

contained in large amount of classified and unclassified data resources. It

has detection capabilities to extract relevant data and relationships aboutpeople, organizations, and activities from source data. It will link items

relating potential criminals, terrorist groups or scenarios, and learn


12/12



patterns of different groups or scenarios to identify new organizations or

emerging threats

7. Case StudyThe world is already using the best technology available to combat crime,

terrorism and other facilities to make their tasks easier. Why should we be left

behind?

Snapshot by agencies during the 9/11 investigation where similar tools were

used to discover the relationships between various terrorists

Technology for Law and Enforcement Agencies

Documents