Currently for detecting cybercrime by using data mining

Currently Existing System Proposed

Authors Ali, Mohammed Mahmood Rajamani,
Lakshmi explain more about suspicious words via social networking sites and
instant messenger, implemented framework based ontology concept and enhanced
for detecting cybercrime by using data mining and information extraction techniques.
The framework based on message communication between clients modules are
captured and stored in database from web application server. Ontology learning
process was used to recognise the domain of suspicious words where those word
belong in depending on content in predefine process using natural language processing
{Ali2013}.

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Implantation IM as Web Application

The module was a website implemented, in
which contained IM that can send and receive messages. This module was having
two part client module of SNS/IM applications and server Module of web
application. The client module is social network sites that are being used to
exchange messages between clients on real time system. Server module is stored
to serve information and retrieval information during user’s communication on
web application.

Data Collection

They used dataset from global terrorism
database GTD, it was open source database. This module, the data was collected
to perform measurements {Ali2013}.

Predefined of Data Using Ontology

Ontology was representing concept within
a domain and relationships among concepts. They used this approach in
identifying the hidden suspicious words from messages and domain such as murder,
kidnap, attack, drug supply, smuggling, robbery and other words similar are
found using ontology in SMD framework{Ali2013}. The suspicious word was extracted
from unstructured text information. Messages spell error checked by using
stinging matching algorithms once the error messages found were stored and
ignored in the words database. The limitation was difficult to identify
suspicious words accurately during word extraction from ODE ontology framework
{Wimalasuriya2010}.

Ontology based information extraction is
require to be implemented due to single word could confirm dissimilar synonyms
that help to builds the knowledge base agreeing topic align with a stem words
of same topic. After discovering the suspicious word the used, ontology and
tree alignment algorithm mapping suspicious word when IM messages were
communicated among the users it captured dynamically using ODE ontology {Ali2013}.

Security Module

This module encrypted messages sent by
clients need a difficult analysis with special algorithm standard to decryption
and encryption algorithm, it needs a public keys or private to decrypt the
encrypted messages that are shared via social networking sites. A researcher
based on text messages analysis, tested only general messages which are
communicated among users.

E -crime Monitoring System

Showing confirmation, extraction of
suspicious word and accurate track detection in IM and SNS when the users
exchange messages. Automatic generated report with details of words,
cyber-attacks types with details such as phone no, ISP details, IP address, and
area sending to the department. My SQL database used stored information of cyber-attacks,
find information completed from database which are sometime hard to get
accurate data, used RDF relational wrapper to get specific domain entities
attributes and relationships that exist in criminals.

SPD Algorithm

In this section researcher explained SPD
algorithm flow chart implemented from initial stages to capture messages that
are sent between sender and receiver, then stores them into database for
identifying suspicious messages, trace the culprit details for E-crime
department. However, it was successful to detect suspicious patterns attacks
from dynamic messages and find relationships among the people, locations chat
online. But could not apprehend simple English words like kill, murder etc in
most scenarios those words are in specific coding language for example: picnic
is used instead of “kill”.                                                                                                                                                                 
 Also detect short form such as word
bomb, “bom” or tomorrow is “m” doesn’t detect it. Messages communicated among
users in images hidden ones which are hard to detect. Other challenges
encryption and decryption messages are sending online web application.
E-department could not be able to block and blacklist the message not to be
views by users if it contains suspicious words {Ali2013}.

 

Suspicious Word Detection Framework

In this section, the discussion is more
about enhancement of Suspicious Pattern Detection SPD algorithm. SPD algorithm
is playing big role of capturing the social media messages sent between
clients/users and store them into database for categorizing suspicious messages
using ontology based information extraction (OBIE) and text mining approaches {Wimalasuriya2010}.

The system modules are divided into two
modules:

Step
1:  User register and login

Initially clients
need to register a username, password, email, phone number etc via social media
/ client’s application. Then after gotten verification email of username and
password, clients need to sign into clients application by putting username and
password, through association with different clients to perform such sending
messages utilizing such sending messages using user chat, send users request
and accept request