SlideShare a Scribd company logo
Data Leakage Detection
Submitted by:
Name: GauravKumar
Sic:15cs0967
Branch: CSE
Mob.No 9572343425
Contents…..
 Introduction
 How data leakage takes place
 Biggest data breaches of the 21st century
 Existing data leakage detection techniques
 Disadvantages of existing techniques
 Future scope
 Applications
 Conclusion
Introduction…..
DATA LEAKAGE is the unauthorized transmission of sensitive data or
information from within an organization to an external destination or
recipient.
SENSITIVE DATA of companies and organization includes
 intellectual property,
 Financial information,
 Patient information,
 Personal credit card data,
and other information depending upon the business and the industry
How data leakage takes place..??
 In the course of doing business, sometimes data must be handed
over to the trusted third parties for some enhancement or
operations.
 Sometimes these trusted third parties may act as points of data
leakage.
 Examples:
A. A hospital may give patient records to researcher who will devise
new treatments.
B. A company may have partnership with other companies that
require sharing of customer data.
C. An enterprise may outsource its data processing, so data must be
given to various other companies.
 Owner of data is termed as the distributor and the third
parties are called as the agents.
 In case of data leakage, the distributor must access the
likelihood that the leaked data come from one or more agents,
as opposed to having been independently gathered by other
means.
Biggest data breaches of the 21st century
1. Yahoo
Date: September 2016
Impact: 3 billion user accounts
Details: In September 2016, the once dominant Internet
giant, while in negotiations to sell itself to Verizon,
announced it had been the victim of the biggest data breach
in history, likely by “a state-sponsored actor,” in 2014. The
attack compromised the real names, email addresses, dates
of birth and telephone numbers of 500 million users. The
company said the "vast majority" of the passwords involved
had been hashed using the robust bcrypt algorithm.
2. eBay
Date: May 2014
Impact: 145 million users compromised
Details: The online auction giant reported a cyberattack in
May 2014 that it said exposed names, addresses, dates of
birth and encrypted passwords of all of its 145 million users.
The company said hackers got into the company network
using the credentials of three corporate employees, and had
complete inside access for 229 days, during which time they
were able to make their way to the user database.
3. Uber
Date: Late 2016
Impact: Personal information of 57 million Uber users and 600,000
drivers exposed.
4. Election Systems & Software – 1.8 million accounts
In August, IT security experts discovered an open Amazon Web
Services (AWS) cloud container. It contained a backup copy of data
from Election Systems & Software (ES&S), a company that
manufactures voting machines and elections management
systems. The data contained a total of almost 2 million accounts
with names, addresses, dates of birth, and party affiliations of
Illinois residents. By default, access to AWS bins is possible only
after authentication; however, for some unknown reason, the
settings on this device were misconfigured, and that made the
container accessible to the public.
 "We have a responsibility to protect your data, and if
we can't then we don't deserve to serve you,"
Zuckerberg said in a statement on his Facebook page.
Over 50 million Facebook profiles were harvested by an
app for data, which was then passed the information on
to Cambridge Analytica.
DATA LEAKAGE DETECTION
 To detect whether data been leaked by agents.
 To prevent data leakage.
Existing data leakage detection techniques
1. Watermarking
2. Steganography
1.Watermarking:
A unique code is embedded in each distributed copy. If
that copy is later discovered in the hands of an
unauthorized party, the leaker can be identified. The
watermark is difficult for an attacker to remove, even
when several individuals conspire together with
independently watermarked copies of the data.
HISTORY:
The term “water-marking” was coined by Andrew Tirkel and Charles Osborne
in December 1992. And the first successful embedding and extraction of it
was demonstrated in 1993 by Andrew Tirkel, Charles Osborne and Gerard
Rankin.
General water-marking procedure
Water-marking program
% Water Marking
clear all; close all
x=double(imread('greens.jpg'));
figure; imshow(x/255);
y=x
a=zeros(300,500);
a(100:250,100:350)=1
figure; imshow(a);
save m.dat a -ascii
x1=x(:,:,1);
x2=x(:,:,2);
x3=x(:,:,3);
dx1=dct2(x1); dx11=dx1; //discrete cosine transform
dx2=dct2(x2); dx22=dx2;
dx3=dct2(x3); dx33=dx3;
load m.dat
g=10; // to decide water-marking limit
[rm,cm]=size(m);
dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m;
dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m;
dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m;
figure,imshow(dx1);
figure,imshow(dx2);
figure,imshow(dx3);
y1=idct2(dx1);
y2=idct2(dx2);
y2=idct2(dx3);
y(:,:,1)=y1;
y(:,:,2)=y2;
y(:,:,3)=y3;
figure,imshow(y1);
figure,imshow(y2);
figure,imshow(y3);
figure;imshow(y/255);
Image before & after water-marking
DRAWBACKS OF WATERMARKING
 It involves some modification of data that is making the
data less sensitive by altering attributes of the data.
 The second problem is that these watermarks can be
sometimes destroyed, if the recipient is malicious.
2.Steganography:
Steganography is a technique for hiding a secret message
within a larger one in such a way that others can’t discern
the presence or contents of the hidden message.
Future scope
 Future work includes the investigation of agent guilt
models that capture the leakage scenarios that are not
yet considered.
 The extension of data allocation strategies so that they
can handle agent requests in an online fashion.
APPLICATIONS OF DATA LEAKAGEDETECTION
 It helps in detecting whether the distributor’s sensitive
data has been leaked by the trustworthy or authorized
agents.
 It helps to identify the agents who leaked the data.
 Reduce cybercrime.
 Copy prevention & control.
 Source tracking.
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.
 We can provide security to our data during its
distribution or transmission and even we can detect if
that gets leaked by using data leakage detection
techniques.
Submitted by:
Name: GAURAV KUMAR
Branch: CSE
Email-id:-
Gaurav.kumar8462@gmail.com

More Related Content

What's hot

Data leakage detection (synopsis)
Data leakage detection (synopsis)Data leakage detection (synopsis)
Data leakage detection (synopsis)
Mumbai Academisc
 
Jpdcs1 data leakage detection
Jpdcs1 data leakage detectionJpdcs1 data leakage detection
Jpdcs1 data leakage detection
Chaitanya Kn
 
CS6004 Cyber Forensics
CS6004 Cyber ForensicsCS6004 Cyber Forensics
CS6004 Cyber Forensics
Kathirvel Ayyaswamy
 
Dark Web Forensics
Dark Web Forensics Dark Web Forensics
Dark Web Forensics
Deepak Kumar (D3)
 
Introduction to Data Mining
Introduction to Data Mining Introduction to Data Mining
Introduction to Data Mining
Sushil Kulkarni
 
Network forensic
Network forensicNetwork forensic
Network forensic
Manjushree Mashal
 
Network Forensic
Network ForensicNetwork Forensic
Network Forensic
Sujeet Kumar
 
Social engineering
Social engineering Social engineering
Social engineering
Vîñàý Pãtêl
 
Presentation(group j)implementing trustworthy computing by Sundas Ilyas
Presentation(group j)implementing  trustworthy computing by Sundas IlyasPresentation(group j)implementing  trustworthy computing by Sundas Ilyas
Presentation(group j)implementing trustworthy computing by Sundas Ilyas
Sundas Kayani
 
Web Browser Artifacts
Web Browser ArtifactsWeb Browser Artifacts
Web Browser Artifacts
primeteacher32
 
The Dark Web
The Dark WebThe Dark Web
The Dark Web
jamiecornista
 
Network Attacks and Countermeasures
Network Attacks and CountermeasuresNetwork Attacks and Countermeasures
Network Attacks and Countermeasures
karanwayne
 
Network attacks
Network attacksNetwork attacks
Network attacks
Manjushree Mashal
 
Digital forensics
Digital forensicsDigital forensics
Digital forensics
Roberto Ellis
 
Spoofing attack: Learn about Email spoofing, IP address spoofing and many other
Spoofing attack: Learn about Email spoofing, IP address spoofing and many otherSpoofing attack: Learn about Email spoofing, IP address spoofing and many other
Spoofing attack: Learn about Email spoofing, IP address spoofing and many other
Pankaj Dubey
 
Insider threat
Insider threatInsider threat
Insider threat
ARCON TECHSOLUTIONS
 
DDoS Attack PPT by Nitin Bisht
DDoS Attack  PPT by Nitin BishtDDoS Attack  PPT by Nitin Bisht
DDoS Attack PPT by Nitin Bisht
Nitin Bisht
 
Mobile security
Mobile securityMobile security
Mobile security
Tapan Khilar
 
Advanced persistent threat (apt)
Advanced persistent threat (apt)Advanced persistent threat (apt)
Advanced persistent threat (apt)
mmubashirkhan
 
Mobile Forensics
Mobile Forensics Mobile Forensics
Mobile Forensics
abdullah roomi
 

What's hot (20)

Data leakage detection (synopsis)
Data leakage detection (synopsis)Data leakage detection (synopsis)
Data leakage detection (synopsis)
 
Jpdcs1 data leakage detection
Jpdcs1 data leakage detectionJpdcs1 data leakage detection
Jpdcs1 data leakage detection
 
CS6004 Cyber Forensics
CS6004 Cyber ForensicsCS6004 Cyber Forensics
CS6004 Cyber Forensics
 
Dark Web Forensics
Dark Web Forensics Dark Web Forensics
Dark Web Forensics
 
Introduction to Data Mining
Introduction to Data Mining Introduction to Data Mining
Introduction to Data Mining
 
Network forensic
Network forensicNetwork forensic
Network forensic
 
Network Forensic
Network ForensicNetwork Forensic
Network Forensic
 
Social engineering
Social engineering Social engineering
Social engineering
 
Presentation(group j)implementing trustworthy computing by Sundas Ilyas
Presentation(group j)implementing  trustworthy computing by Sundas IlyasPresentation(group j)implementing  trustworthy computing by Sundas Ilyas
Presentation(group j)implementing trustworthy computing by Sundas Ilyas
 
Web Browser Artifacts
Web Browser ArtifactsWeb Browser Artifacts
Web Browser Artifacts
 
The Dark Web
The Dark WebThe Dark Web
The Dark Web
 
Network Attacks and Countermeasures
Network Attacks and CountermeasuresNetwork Attacks and Countermeasures
Network Attacks and Countermeasures
 
Network attacks
Network attacksNetwork attacks
Network attacks
 
Digital forensics
Digital forensicsDigital forensics
Digital forensics
 
Spoofing attack: Learn about Email spoofing, IP address spoofing and many other
Spoofing attack: Learn about Email spoofing, IP address spoofing and many otherSpoofing attack: Learn about Email spoofing, IP address spoofing and many other
Spoofing attack: Learn about Email spoofing, IP address spoofing and many other
 
Insider threat
Insider threatInsider threat
Insider threat
 
DDoS Attack PPT by Nitin Bisht
DDoS Attack  PPT by Nitin BishtDDoS Attack  PPT by Nitin Bisht
DDoS Attack PPT by Nitin Bisht
 
Mobile security
Mobile securityMobile security
Mobile security
 
Advanced persistent threat (apt)
Advanced persistent threat (apt)Advanced persistent threat (apt)
Advanced persistent threat (apt)
 
Mobile Forensics
Mobile Forensics Mobile Forensics
Mobile Forensics
 

Similar to Data leakage detection

10.1.1.436.3364.pdf
10.1.1.436.3364.pdf10.1.1.436.3364.pdf
10.1.1.436.3364.pdf
mistryritesh
 
Modeling and Detection of Data Leakage Fraud
Modeling and Detection of Data Leakage FraudModeling and Detection of Data Leakage Fraud
Modeling and Detection of Data Leakage Fraud
IOSR Journals
 
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
Drog3
 
Data Allocation Strategies for Leakage Detection
Data Allocation Strategies for Leakage DetectionData Allocation Strategies for Leakage Detection
Data Allocation Strategies for Leakage Detection
IOSR Journals
 
Case 11. What exactly occurred Twitter is one of popular soci.docx
Case 11. What exactly occurred Twitter is one of popular soci.docxCase 11. What exactly occurred Twitter is one of popular soci.docx
Case 11. What exactly occurred Twitter is one of popular soci.docx
tidwellveronique
 
Privacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposurePrivacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposure
Pvrtechnologies Nellore
 
Secure Multimedia Content Protection and Sharing
Secure Multimedia Content Protection and SharingSecure Multimedia Content Protection and Sharing
Secure Multimedia Content Protection and Sharing
IRJET Journal
 
Privacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposurePrivacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposure
redpel dot com
 
Dn31538540
Dn31538540Dn31538540
Dn31538540
IJMER
 
Securing sensitive data for the health care industry
Securing sensitive data for the health care industrySecuring sensitive data for the health care industry
Securing sensitive data for the health care industry
CloudMask inc.
 
Critical Update Needed: Cybersecurity Expertise in the Boardroom
Critical Update Needed: Cybersecurity Expertise in the BoardroomCritical Update Needed: Cybersecurity Expertise in the Boardroom
Critical Update Needed: Cybersecurity Expertise in the Boardroom
Stanford GSB Corporate Governance Research Initiative
 
Data leakage detection
Data leakage detectionData leakage detection
Data leakage detection
Ajitkaur saini
 
White Paper - Nuix Cybersecurity - US Localized
White Paper - Nuix Cybersecurity - US LocalizedWhite Paper - Nuix Cybersecurity - US Localized
White Paper - Nuix Cybersecurity - US Localized
Stuart Clarke
 
Source Code and Admin Password Shared on Public Site by Developer
Source Code and Admin Password Shared on Public Site by DeveloperSource Code and Admin Password Shared on Public Site by Developer
Source Code and Admin Password Shared on Public Site by Developer
Digital Shadows
 
Rise of cyber security v0.1
Rise of cyber security v0.1Rise of cyber security v0.1
Rise of cyber security v0.1
Sohail Gohir
 
AIDA ICITET
AIDA ICITETAIDA ICITET
Cloud assisted mobile-access of health data with privacy and auditability
Cloud assisted mobile-access of health data with privacy and auditabilityCloud assisted mobile-access of health data with privacy and auditability
Cloud assisted mobile-access of health data with privacy and auditability
Shakas Technologies
 
Sub1555
Sub1555Sub1555
I want you to Read intensively papers and give me a summary for ever.pdf
I want you to Read intensively papers and give me a summary for ever.pdfI want you to Read intensively papers and give me a summary for ever.pdf
I want you to Read intensively papers and give me a summary for ever.pdf
amitkhanna2070
 
Microsoft DATA Protection To Put secure.
Microsoft DATA Protection To Put secure.Microsoft DATA Protection To Put secure.
Microsoft DATA Protection To Put secure.
jayceewong1
 

Similar to Data leakage detection (20)

10.1.1.436.3364.pdf
10.1.1.436.3364.pdf10.1.1.436.3364.pdf
10.1.1.436.3364.pdf
 
Modeling and Detection of Data Leakage Fraud
Modeling and Detection of Data Leakage FraudModeling and Detection of Data Leakage Fraud
Modeling and Detection of Data Leakage Fraud
 
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
 
Data Allocation Strategies for Leakage Detection
Data Allocation Strategies for Leakage DetectionData Allocation Strategies for Leakage Detection
Data Allocation Strategies for Leakage Detection
 
Case 11. What exactly occurred Twitter is one of popular soci.docx
Case 11. What exactly occurred Twitter is one of popular soci.docxCase 11. What exactly occurred Twitter is one of popular soci.docx
Case 11. What exactly occurred Twitter is one of popular soci.docx
 
Privacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposurePrivacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposure
 
Secure Multimedia Content Protection and Sharing
Secure Multimedia Content Protection and SharingSecure Multimedia Content Protection and Sharing
Secure Multimedia Content Protection and Sharing
 
Privacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposurePrivacy preserving detection of sensitive data exposure
Privacy preserving detection of sensitive data exposure
 
Dn31538540
Dn31538540Dn31538540
Dn31538540
 
Securing sensitive data for the health care industry
Securing sensitive data for the health care industrySecuring sensitive data for the health care industry
Securing sensitive data for the health care industry
 
Critical Update Needed: Cybersecurity Expertise in the Boardroom
Critical Update Needed: Cybersecurity Expertise in the BoardroomCritical Update Needed: Cybersecurity Expertise in the Boardroom
Critical Update Needed: Cybersecurity Expertise in the Boardroom
 
Data leakage detection
Data leakage detectionData leakage detection
Data leakage detection
 
White Paper - Nuix Cybersecurity - US Localized
White Paper - Nuix Cybersecurity - US LocalizedWhite Paper - Nuix Cybersecurity - US Localized
White Paper - Nuix Cybersecurity - US Localized
 
Source Code and Admin Password Shared on Public Site by Developer
Source Code and Admin Password Shared on Public Site by DeveloperSource Code and Admin Password Shared on Public Site by Developer
Source Code and Admin Password Shared on Public Site by Developer
 
Rise of cyber security v0.1
Rise of cyber security v0.1Rise of cyber security v0.1
Rise of cyber security v0.1
 
AIDA ICITET
AIDA ICITETAIDA ICITET
AIDA ICITET
 
Cloud assisted mobile-access of health data with privacy and auditability
Cloud assisted mobile-access of health data with privacy and auditabilityCloud assisted mobile-access of health data with privacy and auditability
Cloud assisted mobile-access of health data with privacy and auditability
 
Sub1555
Sub1555Sub1555
Sub1555
 
I want you to Read intensively papers and give me a summary for ever.pdf
I want you to Read intensively papers and give me a summary for ever.pdfI want you to Read intensively papers and give me a summary for ever.pdf
I want you to Read intensively papers and give me a summary for ever.pdf
 
Microsoft DATA Protection To Put secure.
Microsoft DATA Protection To Put secure.Microsoft DATA Protection To Put secure.
Microsoft DATA Protection To Put secure.
 

Recently uploaded

一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
一比一原版卡尔加里大学毕业证(uc毕业证)如何办理一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
oaxefes
 
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
hqfek
 
Senior Software Profiles Backend Sample - Sheet1.pdf
Senior Software Profiles  Backend Sample - Sheet1.pdfSenior Software Profiles  Backend Sample - Sheet1.pdf
Senior Software Profiles Backend Sample - Sheet1.pdf
Vineet
 
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
uevausa
 
SAP BW4HANA Implementagtion Content Document
SAP BW4HANA Implementagtion Content DocumentSAP BW4HANA Implementagtion Content Document
SAP BW4HANA Implementagtion Content Document
newdirectionconsulta
 
06-18-2024-Princeton Meetup-Introduction to Milvus
06-18-2024-Princeton Meetup-Introduction to Milvus06-18-2024-Princeton Meetup-Introduction to Milvus
06-18-2024-Princeton Meetup-Introduction to Milvus
Timothy Spann
 
Sample Devops SRE Product Companies .pdf
Sample Devops SRE  Product Companies .pdfSample Devops SRE  Product Companies .pdf
Sample Devops SRE Product Companies .pdf
Vineet
 
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
Rebecca Bilbro
 
Senior Engineering Sample EM DOE - Sheet1.pdf
Senior Engineering Sample EM DOE  - Sheet1.pdfSenior Engineering Sample EM DOE  - Sheet1.pdf
Senior Engineering Sample EM DOE - Sheet1.pdf
Vineet
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
osoyvvf
 
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
actyx
 
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
eoxhsaa
 
How To Control IO Usage using Resource Manager
How To Control IO Usage using Resource ManagerHow To Control IO Usage using Resource Manager
How To Control IO Usage using Resource Manager
Alireza Kamrani
 
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
ywqeos
 
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
9gr6pty
 
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdfreading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
perranet1
 
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdfNamma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
22ad0301
 
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdfOverview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
nhutnguyen355078
 
一比一原版悉尼大学毕业证如何办理
一比一原版悉尼大学毕业证如何办理一比一原版悉尼大学毕业证如何办理
一比一原版悉尼大学毕业证如何办理
keesa2
 
一比一原版南昆士兰大学毕业证如何办理
一比一原版南昆士兰大学毕业证如何办理一比一原版南昆士兰大学毕业证如何办理
一比一原版南昆士兰大学毕业证如何办理
ugydym
 

Recently uploaded (20)

一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
一比一原版卡尔加里大学毕业证(uc毕业证)如何办理一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
一比一原版卡尔加里大学毕业证(uc毕业证)如何办理
 
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
 
Senior Software Profiles Backend Sample - Sheet1.pdf
Senior Software Profiles  Backend Sample - Sheet1.pdfSenior Software Profiles  Backend Sample - Sheet1.pdf
Senior Software Profiles Backend Sample - Sheet1.pdf
 
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
 
SAP BW4HANA Implementagtion Content Document
SAP BW4HANA Implementagtion Content DocumentSAP BW4HANA Implementagtion Content Document
SAP BW4HANA Implementagtion Content Document
 
06-18-2024-Princeton Meetup-Introduction to Milvus
06-18-2024-Princeton Meetup-Introduction to Milvus06-18-2024-Princeton Meetup-Introduction to Milvus
06-18-2024-Princeton Meetup-Introduction to Milvus
 
Sample Devops SRE Product Companies .pdf
Sample Devops SRE  Product Companies .pdfSample Devops SRE  Product Companies .pdf
Sample Devops SRE Product Companies .pdf
 
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)
 
Senior Engineering Sample EM DOE - Sheet1.pdf
Senior Engineering Sample EM DOE  - Sheet1.pdfSenior Engineering Sample EM DOE  - Sheet1.pdf
Senior Engineering Sample EM DOE - Sheet1.pdf
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
 
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
 
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
 
How To Control IO Usage using Resource Manager
How To Control IO Usage using Resource ManagerHow To Control IO Usage using Resource Manager
How To Control IO Usage using Resource Manager
 
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
 
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
一比一原版(uob毕业证书)伯明翰大学毕业证如何办理
 
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdfreading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
reading_sample_sap_press_operational_data_provisioning_with_sap_bw4hana (1).pdf
 
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdfNamma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
Namma-Kalvi-11th-Physics-Study-Material-Unit-1-EM-221086.pdf
 
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdfOverview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
 
一比一原版悉尼大学毕业证如何办理
一比一原版悉尼大学毕业证如何办理一比一原版悉尼大学毕业证如何办理
一比一原版悉尼大学毕业证如何办理
 
一比一原版南昆士兰大学毕业证如何办理
一比一原版南昆士兰大学毕业证如何办理一比一原版南昆士兰大学毕业证如何办理
一比一原版南昆士兰大学毕业证如何办理
 

Data leakage detection

  • 1. Data Leakage Detection Submitted by: Name: GauravKumar Sic:15cs0967 Branch: CSE Mob.No 9572343425
  • 2. Contents…..  Introduction  How data leakage takes place  Biggest data breaches of the 21st century  Existing data leakage detection techniques  Disadvantages of existing techniques  Future scope  Applications  Conclusion
  • 3. Introduction….. DATA LEAKAGE is the unauthorized transmission of sensitive data or information from within an organization to an external destination or recipient. SENSITIVE DATA of companies and organization includes  intellectual property,  Financial information,  Patient information,  Personal credit card data, and other information depending upon the business and the industry
  • 4. How data leakage takes place..??  In the course of doing business, sometimes data must be handed over to the trusted third parties for some enhancement or operations.  Sometimes these trusted third parties may act as points of data leakage.  Examples: A. A hospital may give patient records to researcher who will devise new treatments. B. A company may have partnership with other companies that require sharing of customer data. C. An enterprise may outsource its data processing, so data must be given to various other companies.
  • 5.  Owner of data is termed as the distributor and the third parties are called as the agents.  In case of data leakage, the distributor must access the likelihood that the leaked data come from one or more agents, as opposed to having been independently gathered by other means.
  • 6. Biggest data breaches of the 21st century
  • 7. 1. Yahoo Date: September 2016 Impact: 3 billion user accounts Details: In September 2016, the once dominant Internet giant, while in negotiations to sell itself to Verizon, announced it had been the victim of the biggest data breach in history, likely by “a state-sponsored actor,” in 2014. The attack compromised the real names, email addresses, dates of birth and telephone numbers of 500 million users. The company said the "vast majority" of the passwords involved had been hashed using the robust bcrypt algorithm.
  • 8. 2. eBay Date: May 2014 Impact: 145 million users compromised Details: The online auction giant reported a cyberattack in May 2014 that it said exposed names, addresses, dates of birth and encrypted passwords of all of its 145 million users. The company said hackers got into the company network using the credentials of three corporate employees, and had complete inside access for 229 days, during which time they were able to make their way to the user database.
  • 9. 3. Uber Date: Late 2016 Impact: Personal information of 57 million Uber users and 600,000 drivers exposed. 4. Election Systems & Software – 1.8 million accounts In August, IT security experts discovered an open Amazon Web Services (AWS) cloud container. It contained a backup copy of data from Election Systems & Software (ES&S), a company that manufactures voting machines and elections management systems. The data contained a total of almost 2 million accounts with names, addresses, dates of birth, and party affiliations of Illinois residents. By default, access to AWS bins is possible only after authentication; however, for some unknown reason, the settings on this device were misconfigured, and that made the container accessible to the public.
  • 10.  "We have a responsibility to protect your data, and if we can't then we don't deserve to serve you," Zuckerberg said in a statement on his Facebook page. Over 50 million Facebook profiles were harvested by an app for data, which was then passed the information on to Cambridge Analytica.
  • 11.
  • 12.
  • 13.
  • 14. DATA LEAKAGE DETECTION  To detect whether data been leaked by agents.  To prevent data leakage.
  • 15. Existing data leakage detection techniques 1. Watermarking 2. Steganography
  • 16. 1.Watermarking: A unique code is embedded in each distributed copy. If that copy is later discovered in the hands of an unauthorized party, the leaker can be identified. The watermark is difficult for an attacker to remove, even when several individuals conspire together with independently watermarked copies of the data. HISTORY: The term “water-marking” was coined by Andrew Tirkel and Charles Osborne in December 1992. And the first successful embedding and extraction of it was demonstrated in 1993 by Andrew Tirkel, Charles Osborne and Gerard Rankin.
  • 18.
  • 19. Water-marking program % Water Marking clear all; close all x=double(imread('greens.jpg')); figure; imshow(x/255); y=x a=zeros(300,500); a(100:250,100:350)=1 figure; imshow(a); save m.dat a -ascii x1=x(:,:,1); x2=x(:,:,2); x3=x(:,:,3);
  • 20. dx1=dct2(x1); dx11=dx1; //discrete cosine transform dx2=dct2(x2); dx22=dx2; dx3=dct2(x3); dx33=dx3; load m.dat g=10; // to decide water-marking limit [rm,cm]=size(m); dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m; dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m; dx1(1:rm,1:cm)=dx1(1:rm,1:cm)g*m; figure,imshow(dx1); figure,imshow(dx2); figure,imshow(dx3);
  • 22. Image before & after water-marking
  • 23. DRAWBACKS OF WATERMARKING  It involves some modification of data that is making the data less sensitive by altering attributes of the data.  The second problem is that these watermarks can be sometimes destroyed, if the recipient is malicious.
  • 24. 2.Steganography: Steganography is a technique for hiding a secret message within a larger one in such a way that others can’t discern the presence or contents of the hidden message.
  • 25. Future scope  Future work includes the investigation of agent guilt models that capture the leakage scenarios that are not yet considered.  The extension of data allocation strategies so that they can handle agent requests in an online fashion.
  • 26.
  • 27. APPLICATIONS OF DATA LEAKAGEDETECTION  It helps in detecting whether the distributor’s sensitive data has been leaked by the trustworthy or authorized agents.  It helps to identify the agents who leaked the data.  Reduce cybercrime.  Copy prevention & control.  Source tracking.
  • 28. 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.  We can provide security to our data during its distribution or transmission and even we can detect if that gets leaked by using data leakage detection techniques.
  • 29. Submitted by: Name: GAURAV KUMAR Branch: CSE Email-id:- Gaurav.kumar8462@gmail.com