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 andinstant messenger, implemented framework based ontology concept and enhancedfor detecting cybercrime by using data mining and information extraction techniques.The framework based on message communication between clients modules arecaptured and stored in database from web application server. Ontology learningprocess was used to recognise the domain of suspicious words where those wordbelong in depending on content in predefine process using natural language processing{Ali2013}.Implantation IM as Web ApplicationThe module was a website implemented, inwhich contained IM that can send and receive messages.

This module was havingtwo part client module of SNS/IM applications and server Module of webapplication. The client module is social network sites that are being used toexchange messages between clients on real time system. Server module is storedto serve information and retrieval information during user’s communication onweb application.

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Data Collection They used dataset from global terrorismdatabase GTD, it was open source database. This module, the data was collectedto perform measurements {Ali2013}.Predefined of Data Using Ontology Ontology was representing concept withina domain and relationships among concepts. They used this approach inidentifying the hidden suspicious words from messages and domain such as murder,kidnap, attack, drug supply, smuggling, robbery and other words similar arefound using ontology in SMD framework{Ali2013}. The suspicious word was extractedfrom unstructured text information. Messages spell error checked by usingstinging matching algorithms once the error messages found were stored andignored in the words database. The limitation was difficult to identifysuspicious words accurately during word extraction from ODE ontology framework{Wimalasuriya2010}.Ontology based information extraction isrequire to be implemented due to single word could confirm dissimilar synonymsthat help to builds the knowledge base agreeing topic align with a stem wordsof same topic.

After discovering the suspicious word the used, ontology andtree alignment algorithm mapping suspicious word when IM messages werecommunicated among the users it captured dynamically using ODE ontology {Ali2013}.Security ModuleThis module encrypted messages sent byclients need a difficult analysis with special algorithm standard to decryptionand encryption algorithm, it needs a public keys or private to decrypt theencrypted messages that are shared via social networking sites. A researcherbased on text messages analysis, tested only general messages which arecommunicated among users.E -crime Monitoring System Showing confirmation, extraction ofsuspicious word and accurate track detection in IM and SNS when the usersexchange messages.

Automatic generated report with details of words,cyber-attacks types with details such as phone no, ISP details, IP address, andarea sending to the department. My SQL database used stored information of cyber-attacks,find information completed from database which are sometime hard to getaccurate data, used RDF relational wrapper to get specific domain entitiesattributes and relationships that exist in criminals.SPD AlgorithmIn this section researcher explained SPDalgorithm flow chart implemented from initial stages to capture messages thatare sent between sender and receiver, then stores them into database foridentifying suspicious messages, trace the culprit details for E-crimedepartment. However, it was successful to detect suspicious patterns attacksfrom dynamic messages and find relationships among the people, locations chatonline. But could not apprehend simple English words like kill, murder etc inmost scenarios those words are in specific coding language for example: picnicis used instead of “kill”.                                                                                                                                                                  Also detect short form such as wordbomb, “bom” or tomorrow is “m” doesn’t detect it. Messages communicated amongusers in images hidden ones which are hard to detect.

Other challengesencryption and decryption messages are sending online web application.E-department could not be able to block and blacklist the message not to beviews by users if it contains suspicious words {Ali2013}. Suspicious Word Detection Framework In this section, the discussion is moreabout enhancement of Suspicious Pattern Detection SPD algorithm. SPD algorithmis playing big role of capturing the social media messages sent betweenclients/users and store them into database for categorizing suspicious messagesusing ontology based information extraction (OBIE) and text mining approaches {Wimalasuriya2010}.The system modules are divided into twomodules: Step1:  User register and loginInitially clientsneed to register a username, password, email, phone number etc via social media/ client’s application.

Then after gotten verification email of username andpassword, clients need to sign into clients application by putting username andpassword, through association with different clients to perform such sendingmessages utilizing such sending messages using user chat, send users requestand accept request 


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