City women’s college of Engineering & Technology

A Technical seminar On

Data leakage detection

DATA LEAKAGE DETECTION

BY :

AFSHAN KHATOON(095X1A0503)

DEPT. OF CSE

INTRODUCTIONISSUESSCOPEANALYSISDESIGNIMPLEMENTATIONS

DATA LEAKAGE DETECTION

To detect whether data has been leaked by agents.

To prevent data leakage.

INTRODUCTION

In the course of doing

business, sometimes

sensitive data must be

handed over to supposedly

trusted third parties.

Our goal is to detect when

the distributor's sensitive

data has been leaked by

agents, and if possible to

identify the agent that

leaked the data.

EXISTING SYSTEM•WATERMARKING

PROPOSED SYSTEM

PROPOSED SYSTEM . In the course of doing business, sometimes sensitive data must be handed over to supposedly trusted third parties. Our goal is to detect when thedistributor's sensitive data has beenleaked by agents, and if possible toidentify the agent that leaked the data.

Types of employees that put your company at risk

The security illiterate

The gadget nerds

The unlawful residents

The malicious/disgruntled employees

Distributor (D) is a system which will distribute data to agents Valuable Data (T) is the set of sensitive data which the system is

going to send to the agents Agent (U) is the set of agents to whom the system is going to send

sensitive data. Request from client will be either sample request or explicit request.

Analysis

ARCHITECTURE DIAGRAM:

Data Distributor

Agents

Agents Requesting Secured data from the Data Distributor

Requesting sensitive data

ARCHITECTURE DIAGRAM:

Data distributor sending the secured data to the agents

Sensitive data is sent

Data Distributor

Agents

Internet

The Sent e-mail don’t contains fake Object/Watermarks.

Forwarded to the

outside world

Agent tries to leak the sensitive data

The Sent e-mail contains fake

Object/Watermarks.

Internet

Infected e-mail

containing fake

object

Agent tries to leak the sensitive data

ImplementationThe system has the following

• Data Allocation -- approach same as watermarking -- less sensitive -- add fake object in some cases

• Fake Object -- Are real looking object -- Should not affect data -- Limit on fake object insertion(e-mail inbox) -- CREATEFAKEOBJECT (Ri, Fi, CONDi)

CONCLUSION

In the real scenario there is no need to hand over the sensitive data to the agents who will unknowingly or maliciously leak it.

However, in many cases, we must indeed work with agents that may not be 100 percent trusted, and we may not be certain if a leaked object came from an agent or from some other source.

In spite of these difficulties, it is possible to assess the likelihood that an agent is responsible for a leak, based on the overlap of his data with the leaked data .

The algorithms we have presented implement a variety of data distribution strategies that can improve the distributor’s chances of identifying a leaker.