Abstract:
Data Mining plays a key role in Crime Analysis.
There are many different algorithms mentioned in previous research papers,
among them are the virtual identifier, pruning strategy, support vector
machines, and apriori algorithms. VID is to find relation between record and
vid. The apriori algorithm helps the fuzzy association rules algorithm and it
takes around six hundred seconds to detect a mail bomb attack. In this research
paper, we identified Crime mapping analysis based on KNN (K - Nearest Neighbor)
and ANN (Artificial Neural Network) algorithms to simplify this process. Crime
Mapping is conducted and Funded by the Office of Community Oriented Policing
Services (COPS). Evidence based research helps in analyzing the crimes. We
calculate the crime rate based on the previous data using data mining
techniques. Crime Analysis uses quantitative and qualitative data in
combination with analytic techniques in resolving the cases. For public safety
purposes, the crime mapping is an essential research area to concentrate on. We
can identify the most frequently crime occurring zones with the help of data
mining techniques. In Crime Analysis Mapping, we follow the following steps in
order to reduce the crime rate: 1) Collect crime data 2) Group data 3)
Clustering 4) Forecasting the data. Crime Analysis with crime mapping helps in
understanding the concepts and practice of Crime Analysis in assisting police
and helps in reduction and prevention of crimes and crime disorders.
Introduction
Cybercrime involves a mixture of diverse typical crimes
with new illegal acts. Individual cybercrime incidents are occurrences of
particular criminal offences and, as multiple national crime statistics and
surveys demonstrate, are steadily increasing. According to the Federal Bureau
of Investigation, the Internet Complaint Center received 269 422 complaints of
Internet crime in 2014, which indicates a rise of 1600% in comparison to the 16
838 complains included in the initial report. In a worldwide study released by PricewaterhouseCoopers,
the number of reported information security incidents around the world rose 48%
in 2014, the equivalent of 117 339 attacks per day. Similarly, the German Crime
Statistics indicated a 23.6% increase in the number of cybercrime incident from
2007 to 2008. The various offences of cybercrime pose a serious threat to the
global economy, safety, and wellbeing of the society. In a
PricewaterhouseCoopers report, it is highlighted that cyber-security incidents are
not only increasing in number but they are also becoming progressively
destructive and target a broadening array of information and attack vectors.
Cybercrime continues to be on the rise and cybercriminals
are launching increasingly sophisticated cyber attacks aimed at disrupting businesses
through denial of service attacks and stealing personal information all with
serious economic consequences. Law and policy makers are under increasing
pressure to develop timely legislations to address cybercrime issues and provide
effective measures to prosecute cybercriminals. We present a comprehensive review
of the various laws that are currently available in the Unites States to
control cybercrime and support cyber security. We also discuss proposed bills
in light of how they address cyber security challenges in current legislations.
Finally, we briefly present recent regulations and proposed bills related to
cyber security in a few other countries which have set up various government
initiatives in this area.
Existing System:
Crime has been increasing day by day and everyone in
the world is trying to figure out how to manage the crime rate and to work on
certain cases, most of the people are trying to store the data for future
reference. Human errors can occur at any point of time. There are different
types of crimes law enforcement levels, such as traffic violations, sex crime,
theft, violent crime, arson, gang/drug offenses, cybercrime. There are many
different algorithms mentioned in previous research papers, among them are the
virtual identifier, pruning strategy, support vector machines, and apriori
algorithms. VID is to find relation between record and vid. The apriori
algorithm helps the fuzzy association rules algorithm and it takes
around six hundred seconds to detect a mail bomb attack.
Disadvantage:
· The main problem here is the central
problem, where all the data needs to be stored in a single place and required
to retrieve this large bulk amount of data would cost a lot.
· Crimes are one of the most predominant
problems that is happening in most of the urban areas in the world. There are a
lot of different types of crimes that happen, including robbery, theft of
vehicles, etc.
· It takes around six hundred seconds to detect a mail bomb attack.
Proposed System:
Crime Mapping helps in understanding the concepts
and practice of Crime Analysis in assisting police and helps in reduction and prevention
of crimes and crime disorders using data mining tools. We can use data mining
tools involved using ANN (Artificial Neural Networks) and KDD (Knowledge
Discovery in Databases). We collect the data from police department and try to
get each and every detail, like the person’s name, height, age, sex,
fingerprint details, and pattern identification number for similar types of
cases.
Once we get the information, we start to process the
data. We get a lot of unnecessary data along with the required data. But before
we start processing the data using data mining techniques and tools, we need to
identify unnecessary data and remove those kinds of data to reduce or to avoid
the confusion.
Advantage:
· We mainly collect the attributes information,
like eye color, fingerprint details, characteristics, dimensions, or other
features.
· The use of information mining methods helps
in resolving most complicated criminal cases.
· One of the best methods is crime
analysis with crime mapping. Crime analysis with crime mapping helps in
understanding the concepts and practices of crime analysis in assisting police
and helps in the reduction and prevention of crimes and crime disorders.
· It can identity the most frequently crime
occurring zones with the help of data mining techniques.
SYSTEM CONFIGURATION
HARDWARE CONFIGURATION
·
Hard
Disk : 80 GB.
·
Monitor : 15 VGA Colour.
·
Mouse : Logitech.
·
Ram : 2 GB.
·
Coding Language : JAVA/J2EE
·
IDE : Net beans
·
Database : MYSQL
MAIN MODULES
·
Crime analysis
·
Community oriented policing services
·
Distributed denial of service attack
·
Clustering technique
MODULE DESCRIPTIONS
Crime analysis
Crimes are one of the most predominant problems that
is happening in most of the urban areas in the world. There are a lot of
different types of crimes that happen, including robbery, theft of vehicles, etc.
As crime increases, the investigation process gets longer and more complicated.
The use of information mining methods helps in resolving most complicated
criminal cases. One of the best methods is crime analysis with crime mapping. Crime
analysis with crime mapping helps in understanding the concepts and practices
of crime analysis in assisting police and helps in the reduction and prevention
of crimes and crime disorders.
Community oriented policing services:
Crime mapping is conducted and funded by the Office
of Community Oriented Policing Services (COPS). Evidence based research helps
in analyzing the crimes. We calculate the crime rate based on the previous data
using data mining techniques. Crime analysis uses quantitative and qualitative
data and analytic techniques in resolving the cases. For public safety
purposes, the crime mapping is an essential research area to concentrate on. We
can identity the highest risk crime zones with the help of data mining
techniques.
Distributed denial of service attack:
Distributed denial of service attacks is one of the most
common attacks on internet sites. Intrusion detection helps in identifying the
network related activity and using this we can provide security against DOS
attacks. There are two types of intrusion detection methods available here:
misuse detection which is based on exact pattern match, and anomaly detection
which requires more training related to artificial intelligence. Fuzzy intrusion
recognition engine is an anomaly IDS which identifies malicious sites which are
not trustworthy using fuzzy systems. Here, 3-D packet count with a 15-minute
interval is used to find the regular network connections and try to indicate
the intrusions, if any, at that point of time.
Clustering technique:
In this, they used clustering techniques to identify
crime patterns. In a geographical area, the need to identify the crime at a
point in time is known as clustering. We can use a map to identify the plot. The
largest challenge is with free text fields. It is difficult to convert the free
text fields into data, but the K means technique is used for this purpose in this
paper. Operational data can be extracted and transformed to another form using
this technique. By doing this, it is much easier to find out the crime patterns
for the detectives to identify the frauds
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