data leakage detection

2. BY :
AFSHAN KHATOON(095X1A0503)
DEPT. OF CSE
DATA LEAKAGE
DETECTION

3. INTRODUCTION
ISSUES
SCOPE
ANALYSIS
DESIGN
IMPLEMENTATIONS

4. DATA LEAKAGE DETECTION
 To detect whether data has been leaked by
agents.
 To prevent data leakage.

5. INTRODUCTIO
N
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.

6. • WATERMARKING
PROPOSED SYSTEM

7. 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 the
distributor's sensitive data has been
leaked by agents, and if possible to
identify the agent that leaked the data.

8. Types of employees that put your
company at risk
The security illiterate
The gadget nerds
The unlawful residents
The malicious/disgruntled employees

9. Analysis
 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.

10. ARCHITECTURE DIAGRAM:
Requesting
sensitive data
Data Distributor
Agents Requesting Secured data from
the Data Distributor
Agents

11. ARCHITECTURE DIAGRAM:
Sensitive data is
sent
Data Distributor
Data distributor sending the secured data
to the agents
Agents

12. The Sent e-mail
don’t contains fake
Object/Watermarks.
Internet
Agent tries to leak the
sensitive data
Forwarded
to the
outside
world

13. The Sent e-mail
contains fake
Object/Watermarks.
Internet
Agent tries to leak the
sensitive data
Infected
e-mail
containing
fake
object

14. Implementation
The 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)

15. 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.