SlideShare a Scribd company logo
1 of 10
Data Leakage Detection

(Synopsis)
ABSTRACT:
We study the following problem: A data distributor has given sensitive
data to a set of supposedly trusted agents (third parties). Some of the data
is leaked and found in an unauthorized place (e.g., on the web or
somebody’s laptop). The distributor must assess the likelihood that the
leaked data came from one or more agents, as opposed to having been
independently gathered by other means. We propose data allocation
strategies (across the agents) that improve the probability of identifying
leakages. These methods do not rely on alterations of the released data
(e.g., watermarks). In some cases we can also inject “realistic but fake” data
records to further improve our chances of detecting leakage and identifying
the guilty party.

Objective
The objective of the system is to detect when the distributor’s
sensitive data has been leaked by hackers, and if possible to identify the
agent that leaked the data.
Existing System
The Existing System can detect the hackers but the total no of cookies
(evidence) will be less and the organization may not be able to proceed
legally for further proceedings due to lack of good amount of cookies and the
chances to escape of hackers are high.

Proposed system
In the Proposed System the hackers can be traced with good amount
of evidence. In this proposed system the leakage of data is detected by
the following methods viz.., generating Fake objects, Watermarking and
by Encrypting the data.

Modules:
Module1

: Administrator Module

Module 2

: Employees Module

Module 3

: Data Leakage Detection Module
Administrator Module:
All the privileges of the website are only available with the administrator.
Admin has privileges to accomplish the following responsibilities/tasks:
•

Manage

Users

(Add,

Edit,

Delete,

Lock/Unlock,

Assign

Permissions).
•

Manage Articles (Add, Edit, Update, Delete).

•

Manage Categories (Add, Edit, Update, Delete).

•

Send Messages

•

Upload Documents

Employee Module:
Some of the privileges are restricted to the employee by the administrator.
Only few permissions are available with the employees. Employees have the
following task/responsibilities. Employees have Read-only access to the
content.
•

Employees can Read the articles

•

Download the Documents

•

Read the messages which are send by the Admin

•

Discuss the content in the Discussion Board.
Data Leakage Detection:
The main scope of this module is provide complete information about the
data/content that is accessed by the users within the website.
•

Forms Authentication technique is used to provide security to the
website in order to prevent the leakage of the data.

•

Continuous observation is made automatically and the information is
send to the administrator so that he can identify whenever the data is
leaked.

•

Above all the important aspect providing proof against the Guilty
Objects. The following techniques are used.
o Fake Object Generation.
o Watermarking.
Flow Char for implementation of the following Alogirhtms:
(a)Allocation for Explict Data Request(EF) with fake objects
(b) Agent Selection for e-random and e-optimal
“IN Both the above case

Start

CREATEFAKCEOBJECT()
METHOD GENERATES A
FAKEOBJECT.”

User Request
R Explicit

Check the Condition
Select the agent and
add the fake.
IF B> 0

object
Evaluate The Loop.
Create Fake Object is Invoked

Loop Iterates for n
number of requests

User Receives the
Output.

Stop

Else

Exit
Flow Char for implementation of the following Alogirhtms:
(a) Allocation for Sample Data Request(EF) without any fake objects:
(b) Agent Selection for e-random and e-optimal
“In Both the following cases Select Method() returns the value of ∑ Ri n Rj “
Start

User Request
R Explicit
Check the Condition
Select the agent and
add the fake.
Loop Iterates for n
number of requests

IF B> 0
Evaluate The Loop.
User Receives the
Stop
SelectObject() Method is Invoked
Output.

Else

Exit
object

HARDWARE AND SOFTWARE REQUIREMENTS

Software Requirements:
Language

: Servlets, JSP

Technologies

: JAVA

IDE

: Visual Studio 2008

Operating System

: Microsoft Windows XP SP2 or Later Version

Hardware Requirements:
Processor

: Intel Pentium or more
RAM

: 512 MB (Minimum)

Hard Disk

: 40 GB
RAM

: 512 MB (Minimum)

Hard Disk

: 40 GB

More Related Content

What's hot

SRS for Hospital Management System
SRS for Hospital Management SystemSRS for Hospital Management System
SRS for Hospital Management Systemkataria Arvind
 
Railway reservation system
Railway reservation systemRailway reservation system
Railway reservation systemKOYELMAJUMDAR1
 
Social Networking Project (website) full documentation
Social Networking Project (website) full documentation Social Networking Project (website) full documentation
Social Networking Project (website) full documentation Tenzin Tendar
 
SRS for Library Management System
SRS for Library Management SystemSRS for Library Management System
SRS for Library Management SystemToseef Hasan
 
Banking Management System Project documentation
Banking Management System Project documentationBanking Management System Project documentation
Banking Management System Project documentationChaudhry Sajid
 
Tools and methods used in cybercrime
Tools and methods used in cybercrimeTools and methods used in cybercrime
Tools and methods used in cybercrimepatelripal99
 
Keyloggers and Spywares
Keyloggers and SpywaresKeyloggers and Spywares
Keyloggers and SpywaresAnkit Mistry
 
IoT & Applications Digital Notes.pdf
IoT & Applications Digital Notes.pdfIoT & Applications Digital Notes.pdf
IoT & Applications Digital Notes.pdfkanaka vardhini
 
SRS FOR CHAT APPLICATION
SRS FOR CHAT APPLICATIONSRS FOR CHAT APPLICATION
SRS FOR CHAT APPLICATIONAtul Kushwaha
 
Seminar on yahoo mail cyber attack
Seminar on yahoo mail cyber attackSeminar on yahoo mail cyber attack
Seminar on yahoo mail cyber attackrohit2495
 
Intruders and Viruses in Network Security NS9
Intruders and Viruses in Network Security NS9Intruders and Viruses in Network Security NS9
Intruders and Viruses in Network Security NS9koolkampus
 
Cybercrime: A Seminar Report
Cybercrime: A Seminar ReportCybercrime: A Seminar Report
Cybercrime: A Seminar ReportArindam Sarkar
 
Hospital Management System Network Diagram
Hospital Management System Network DiagramHospital Management System Network Diagram
Hospital Management System Network DiagramNeelam Priya
 

What's hot (20)

Intruders
IntrudersIntruders
Intruders
 
SRS for Hospital Management System
SRS for Hospital Management SystemSRS for Hospital Management System
SRS for Hospital Management System
 
Railway reservation system
Railway reservation systemRailway reservation system
Railway reservation system
 
Social Networking Project (website) full documentation
Social Networking Project (website) full documentation Social Networking Project (website) full documentation
Social Networking Project (website) full documentation
 
SRS for Library Management System
SRS for Library Management SystemSRS for Library Management System
SRS for Library Management System
 
Banking Management System Project documentation
Banking Management System Project documentationBanking Management System Project documentation
Banking Management System Project documentation
 
Cloud computing protocol
Cloud computing protocolCloud computing protocol
Cloud computing protocol
 
Tools and methods used in cybercrime
Tools and methods used in cybercrimeTools and methods used in cybercrime
Tools and methods used in cybercrime
 
Keyloggers and Spywares
Keyloggers and SpywaresKeyloggers and Spywares
Keyloggers and Spywares
 
Ch11
Ch11Ch11
Ch11
 
IoT & Applications Digital Notes.pdf
IoT & Applications Digital Notes.pdfIoT & Applications Digital Notes.pdf
IoT & Applications Digital Notes.pdf
 
Cyber terrorism
Cyber terrorismCyber terrorism
Cyber terrorism
 
SRS FOR CHAT APPLICATION
SRS FOR CHAT APPLICATIONSRS FOR CHAT APPLICATION
SRS FOR CHAT APPLICATION
 
Database security
Database securityDatabase security
Database security
 
Phishing ppt
Phishing pptPhishing ppt
Phishing ppt
 
Seminar on yahoo mail cyber attack
Seminar on yahoo mail cyber attackSeminar on yahoo mail cyber attack
Seminar on yahoo mail cyber attack
 
Intruders and Viruses in Network Security NS9
Intruders and Viruses in Network Security NS9Intruders and Viruses in Network Security NS9
Intruders and Viruses in Network Security NS9
 
Cybercrime: A Seminar Report
Cybercrime: A Seminar ReportCybercrime: A Seminar Report
Cybercrime: A Seminar Report
 
grocery management system
grocery  management systemgrocery  management system
grocery management system
 
Hospital Management System Network Diagram
Hospital Management System Network DiagramHospital Management System Network Diagram
Hospital Management System Network Diagram
 

Similar to Data leakage detection (synopsis)

Data leakage detection
Data leakage detectionData leakage detection
Data leakage detectionAjitkaur saini
 
Data leakage detection
Data leakage detectionData leakage detection
Data leakage detectionbunnz12345
 
83504808-Data-Leakage-Detection-1-Final.ppt
83504808-Data-Leakage-Detection-1-Final.ppt83504808-Data-Leakage-Detection-1-Final.ppt
83504808-Data-Leakage-Detection-1-Final.pptnaresh2004s
 
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdfDrog3
 
Privacy Preserving Based Cloud Storage System
Privacy Preserving Based Cloud Storage SystemPrivacy Preserving Based Cloud Storage System
Privacy Preserving Based Cloud Storage SystemKumar Goud
 
A model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageA model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageeSAT Publishing House
 
A model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageA model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageeSAT Journals
 
Psdot 13 robust data leakage and email filtering system
Psdot 13 robust data leakage and email filtering systemPsdot 13 robust data leakage and email filtering system
Psdot 13 robust data leakage and email filtering systemZTech Proje
 
Deep Learning based Threat / Intrusion detection system
Deep Learning based Threat / Intrusion detection systemDeep Learning based Threat / Intrusion detection system
Deep Learning based Threat / Intrusion detection systemAffine Analytics
 
Beyond Automated Testing - RVAsec 2016
Beyond Automated Testing - RVAsec 2016Beyond Automated Testing - RVAsec 2016
Beyond Automated Testing - RVAsec 2016Andrew McNicol
 
Dn31538540
Dn31538540Dn31538540
Dn31538540IJMER
 
Andrew and Zac RVA-Beyond-Automated-Testing-2016.ppt
Andrew and Zac RVA-Beyond-Automated-Testing-2016.pptAndrew and Zac RVA-Beyond-Automated-Testing-2016.ppt
Andrew and Zac RVA-Beyond-Automated-Testing-2016.pptBUSHRASHAIKH804312
 
Secure Code Warrior - Robust error checking
Secure Code Warrior - Robust error checkingSecure Code Warrior - Robust error checking
Secure Code Warrior - Robust error checkingSecure Code Warrior
 
Final review m score
Final review m scoreFinal review m score
Final review m scoreazhar4010
 
Data Leakage Detection
Data Leakage DetectionData Leakage Detection
Data Leakage DetectionAshwini Nerkar
 
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network Security
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network SecurityWhitepaper- User Behavior-Based Anomaly Detection for Cyber Network Security
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network SecurityHappiest Minds Technologies
 
Corporate Public Investigations
Corporate Public InvestigationsCorporate Public Investigations
Corporate Public InvestigationsCTIN
 
IRJET- Data Leakage Detection System
IRJET- Data Leakage Detection SystemIRJET- Data Leakage Detection System
IRJET- Data Leakage Detection SystemIRJET Journal
 

Similar to Data leakage detection (synopsis) (20)

Data leakage detection
Data leakage detectionData leakage detection
Data leakage detection
 
Data leakage detection
Data leakage detectionData leakage detection
Data leakage detection
 
83504808-Data-Leakage-Detection-1-Final.ppt
83504808-Data-Leakage-Detection-1-Final.ppt83504808-Data-Leakage-Detection-1-Final.ppt
83504808-Data-Leakage-Detection-1-Final.ppt
 
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf
164788616_Data_Leakage_Detection_Complete_Project_Report__1_.docx.pdf
 
Privacy Preserving Based Cloud Storage System
Privacy Preserving Based Cloud Storage SystemPrivacy Preserving Based Cloud Storage System
Privacy Preserving Based Cloud Storage System
 
A model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageA model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakage
 
A model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakageA model to find the agent who responsible for data leakage
A model to find the agent who responsible for data leakage
 
Psdot 13 robust data leakage and email filtering system
Psdot 13 robust data leakage and email filtering systemPsdot 13 robust data leakage and email filtering system
Psdot 13 robust data leakage and email filtering system
 
Deep Learning based Threat / Intrusion detection system
Deep Learning based Threat / Intrusion detection systemDeep Learning based Threat / Intrusion detection system
Deep Learning based Threat / Intrusion detection system
 
Beyond Automated Testing - RVAsec 2016
Beyond Automated Testing - RVAsec 2016Beyond Automated Testing - RVAsec 2016
Beyond Automated Testing - RVAsec 2016
 
Dn31538540
Dn31538540Dn31538540
Dn31538540
 
DLD_SYNOPSIS
DLD_SYNOPSISDLD_SYNOPSIS
DLD_SYNOPSIS
 
Andrew and Zac RVA-Beyond-Automated-Testing-2016.ppt
Andrew and Zac RVA-Beyond-Automated-Testing-2016.pptAndrew and Zac RVA-Beyond-Automated-Testing-2016.ppt
Andrew and Zac RVA-Beyond-Automated-Testing-2016.ppt
 
Secure Code Warrior - Robust error checking
Secure Code Warrior - Robust error checkingSecure Code Warrior - Robust error checking
Secure Code Warrior - Robust error checking
 
Final review m score
Final review m scoreFinal review m score
Final review m score
 
Data Leakage Detection
Data Leakage DetectionData Leakage Detection
Data Leakage Detection
 
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network Security
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network SecurityWhitepaper- User Behavior-Based Anomaly Detection for Cyber Network Security
Whitepaper- User Behavior-Based Anomaly Detection for Cyber Network Security
 
spamzombieppt
spamzombiepptspamzombieppt
spamzombieppt
 
Corporate Public Investigations
Corporate Public InvestigationsCorporate Public Investigations
Corporate Public Investigations
 
IRJET- Data Leakage Detection System
IRJET- Data Leakage Detection SystemIRJET- Data Leakage Detection System
IRJET- Data Leakage Detection System
 

More from Mumbai Academisc

More from Mumbai Academisc (20)

Non ieee java projects list
Non  ieee java projects list Non  ieee java projects list
Non ieee java projects list
 
Non ieee dot net projects list
Non  ieee dot net projects list Non  ieee dot net projects list
Non ieee dot net projects list
 
Ieee java projects list
Ieee java projects list Ieee java projects list
Ieee java projects list
 
Ieee 2014 java projects list
Ieee 2014 java projects list Ieee 2014 java projects list
Ieee 2014 java projects list
 
Ieee 2014 dot net projects list
Ieee 2014 dot net projects list Ieee 2014 dot net projects list
Ieee 2014 dot net projects list
 
Ieee 2013 java projects list
Ieee 2013 java projects list Ieee 2013 java projects list
Ieee 2013 java projects list
 
Ieee 2013 dot net projects list
Ieee 2013 dot net projects listIeee 2013 dot net projects list
Ieee 2013 dot net projects list
 
Ieee 2012 dot net projects list
Ieee 2012 dot net projects listIeee 2012 dot net projects list
Ieee 2012 dot net projects list
 
Spring ppt
Spring pptSpring ppt
Spring ppt
 
Ejb notes
Ejb notesEjb notes
Ejb notes
 
Java web programming
Java web programmingJava web programming
Java web programming
 
Java programming-examples
Java programming-examplesJava programming-examples
Java programming-examples
 
Hibernate tutorial
Hibernate tutorialHibernate tutorial
Hibernate tutorial
 
J2ee project lists:-Mumbai Academics
J2ee project lists:-Mumbai AcademicsJ2ee project lists:-Mumbai Academics
J2ee project lists:-Mumbai Academics
 
Web based development
Web based developmentWeb based development
Web based development
 
Jdbc
JdbcJdbc
Jdbc
 
Java tutorial part 4
Java tutorial part 4Java tutorial part 4
Java tutorial part 4
 
Java tutorial part 3
Java tutorial part 3Java tutorial part 3
Java tutorial part 3
 
Java tutorial part 2
Java tutorial part 2Java tutorial part 2
Java tutorial part 2
 
Engineering
EngineeringEngineering
Engineering
 

Recently uploaded

Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostZilliz
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 

Recently uploaded (20)

Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 

Data leakage detection (synopsis)

  • 2. ABSTRACT: We study the following problem: A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data is leaked and found in an unauthorized place (e.g., on the web or somebody’s laptop). The distributor must assess the likelihood that the leaked data came from one or more agents, as opposed to having been independently gathered by other means. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases we can also inject “realistic but fake” data records to further improve our chances of detecting leakage and identifying the guilty party. Objective The objective of the system is to detect when the distributor’s sensitive data has been leaked by hackers, and if possible to identify the agent that leaked the data.
  • 3. Existing System The Existing System can detect the hackers but the total no of cookies (evidence) will be less and the organization may not be able to proceed legally for further proceedings due to lack of good amount of cookies and the chances to escape of hackers are high. Proposed system In the Proposed System the hackers can be traced with good amount of evidence. In this proposed system the leakage of data is detected by the following methods viz.., generating Fake objects, Watermarking and by Encrypting the data. Modules: Module1 : Administrator Module Module 2 : Employees Module Module 3 : Data Leakage Detection Module
  • 4. Administrator Module: All the privileges of the website are only available with the administrator. Admin has privileges to accomplish the following responsibilities/tasks: • Manage Users (Add, Edit, Delete, Lock/Unlock, Assign Permissions). • Manage Articles (Add, Edit, Update, Delete). • Manage Categories (Add, Edit, Update, Delete). • Send Messages • Upload Documents Employee Module: Some of the privileges are restricted to the employee by the administrator. Only few permissions are available with the employees. Employees have the following task/responsibilities. Employees have Read-only access to the content. • Employees can Read the articles • Download the Documents • Read the messages which are send by the Admin • Discuss the content in the Discussion Board.
  • 5. Data Leakage Detection: The main scope of this module is provide complete information about the data/content that is accessed by the users within the website. • Forms Authentication technique is used to provide security to the website in order to prevent the leakage of the data. • Continuous observation is made automatically and the information is send to the administrator so that he can identify whenever the data is leaked. • Above all the important aspect providing proof against the Guilty Objects. The following techniques are used. o Fake Object Generation. o Watermarking.
  • 6. Flow Char for implementation of the following Alogirhtms: (a)Allocation for Explict Data Request(EF) with fake objects (b) Agent Selection for e-random and e-optimal “IN Both the above case Start CREATEFAKCEOBJECT() METHOD GENERATES A FAKEOBJECT.” User Request R Explicit Check the Condition Select the agent and add the fake. IF B> 0 object Evaluate The Loop. Create Fake Object is Invoked Loop Iterates for n number of requests User Receives the Output. Stop Else Exit
  • 7. Flow Char for implementation of the following Alogirhtms: (a) Allocation for Sample Data Request(EF) without any fake objects: (b) Agent Selection for e-random and e-optimal “In Both the following cases Select Method() returns the value of ∑ Ri n Rj “ Start User Request R Explicit Check the Condition Select the agent and add the fake. Loop Iterates for n number of requests IF B> 0 Evaluate The Loop. User Receives the Stop SelectObject() Method is Invoked Output. Else Exit
  • 8. object HARDWARE AND SOFTWARE REQUIREMENTS Software Requirements: Language : Servlets, JSP Technologies : JAVA IDE : Visual Studio 2008 Operating System : Microsoft Windows XP SP2 or Later Version Hardware Requirements: Processor : Intel Pentium or more
  • 9. RAM : 512 MB (Minimum) Hard Disk : 40 GB
  • 10. RAM : 512 MB (Minimum) Hard Disk : 40 GB