IRJET- Encryption based Approach to Find Fake Uploaders in Social Media

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 10 | Oct 2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1668
Encryption Based Approach to Find Fake Uploaders in Social Media
Shereena T Abdul Rasheed 1, Sadakathulla P.K 2
1MCA student, Centre for Computer Science and Information Technology, University of Calicut, Kerala
2Assistant Professor, Centre for Computer Science and Information Technology, University of Calicut, Kerala
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Abstract - In the digital era, we can see rapid growth in
digital contents through different Medias. As we know social
media plays an important role for generating digital contents
using modern electronic devices and sharingof dataandother
digital contents. Digital images are the one of the frequently
used media. In the context we have a challenge to find out the
fake uploaders. In this paper we are proposing a new strategy
to find out such fake uploaders by using encryption based
method. The proposed system uses steganography based
encryption to identify the fake uploaders in an easy way. Here
we embed some personal information In to the digital image
while uploading the content. By using this we can easily find
the individual easily.
Key Words: Encryption, Decryption, Steganography, social
media security, LSB Substitution.
1. INTRODUCTION
In the modern world, there exists a wide range imaging
techniques for capturing, storing and modifying digital
images. With the increase in consumer generated image
content using handheld devices such as mobile cameras and
ease of sharing, fake news via images are spreading rapidly
on social media. There has been a very active research area
in the last decade. Cryptography and steganography can be
used to provide security for digital content. Cryptography
uses mathematics to encrypt and decrypt data to provide
security by transforming plaintext into ciphertext.
Steganography is the art of hiding information in other
information.
With this paper, we mean that along with the photograph,
we also have related meta-data as contact number of the
person who upload that photograph firstly. Here, theperson
behind the photograph can be identified easily by this
application. Identifying person will eliminate the system of
easily spreading the image and this will also act as bigtool to
give evidence in front of justice court. Here we use an
algorithm that hides the contact number of the person who
uploads the image. The contact number that embeddedwith
the image never loses even if it is shared among different
people. Whenever a situation arises to find out the person
who has uploaded the image, we can easily find out the
contact number of the person by just applying the reverse
algorithm.
2. LETERATURE REVIEW
Besides cryptography, steganography can be used to secure
information. Steganography is a technique of hiding
data/information in digital media. Both Cryptography and
steganography methods of digital images are widely used to
protect and frustrate opponents' attacks from unauthorized
access. Thus, image encryption techniques are required to
protect the data [1]. There is a difference between
cryptography and steganography. Cryptography scrambles
messages so that they cannot be understood. On the other
hand, steganography hides the actual messageinanother[2].
Over the last few years, there are many different
steganographic methods areproposed.Mostofthemarevery
simple techniques so that those can be broken easily by
careful analysis of statistical propertiesofthechannel’snoise
[3].Recently,somenewsteganographicalgorithmshavebeen
proposed fortwo-color binaryimages[4].JohnsonandSushil
explain what steganography is and provide a brief history of
steganography, describe how steganography is applied to
hide information in images, and survey a few steganography
software applications [5]. TsungYuan and Wen-Hsiang
proposed a new steganographic method that uses change
tracking technique for hiding data in Microsoft Word
documents [6]. Sinha and Singh proposed a method to
encrypt an image for secure transmission [7].This method
use the digital signature of the image. Digital signatures
enable the recipient of a message to authenticate the sender
and verify that the message isintact.Kisiketal[4]proposeda
steganographic algorithm which embeds a secret message
into bitmap images and palette-based images.
Y.K JainandR.RAhriwalproposedLeastSignificanttechnique
to hide a message in an image. This technique generates a
steganographykeyafterembeddingthemessage.Thekeyhas
different layers. Every layer hasa fixed number of bits.These
bits are embedded in least significant of the image [8].The
method proposed by Mohammad A Ahmed uses Least
Significant technique to hide data in digital image. Then the
digital image will be implemented in hash significant
technique to get the result in hashing value[9].El-Emam
proposed a method which hides message in an image inform
if pixels. To retrieve the hidden message these pixels are
called. Steganography is used to hide and retrieve the
message [10]. Akhtar N, Johri P and Khan S implemented a
variation of traditional Least Significant Bit (LSB) algorithm.
It uses bit inversion method to enhance the quality of the
image which the message is hidden. This method has lesser
modification in pixels compared to traditional LSB method
[11]. P. U. Deshmuk and T. M. Pattewar proposed the edge
adaptive steganography based on LSB substitution method.
They hide secret message in sharp regions of the image.
This technique also improvesthe quality of stego image [12].
D. Baby, J. Thomas, G. Augustine, E. George and N.R. Michael
presented “Novel DWT based image securing method using
steganography”. They proposed a new steganography
technique in which multiple RGB images are embedded into
single RGB image using DWT steganography technique. This

method has level of PSNR (Peak signal - to - noise ratio) and
structural similarity (SSIM) index values [13]. G. Prashanti
and K. Sandhyarani have done survey on LSB based image
steganography and also two new techniques are presented.
First technique hides secret message in the cover image and
second one embeds a grayscaleimageintoanothergrayscale
image. These two techniques have great security because
secret information is hidden on random selected location of
LSBs of the image [14].
3. LETERATURE REVIEW
The proposed system aims tohidesthecontactnumberofthe
person who uploads the image. The following figure shows
the working of the proposed system.
Fig -1: Working of proposed system
Here we use the Least Significant Bit (LSB) substitution
method to hide the data within the image. This method
replaces the pixels of image by the secret data. The image is
stored as m-by-n matrix having several pixels. Each pixel in
the image is represented as RGB components and that
determine color of each individual pixel. RGB images are
stored as 24 bit format, where the RGB components are of 8
bits each.
Here we use the contact number of the person who uploads
the image and a string as a secret data. The string is used to
check whether theimagealreadycontainanycontactnumber
or not. This secret data is then converted into byte array.
Here we use 3 bit of R, 3 bit of G and 3 bit of B to hide 1 byte
of string. Here we replace first some pixels of the image and
the length of the secret data determines the number of pixels
to be replaced. This results only asmall changeinthevalueof
RGB component, which human eyes can’t detect.
Whenever any situationarises,thereversealgorithmhelpsto
identify the contact number of thepersonwhofirstlyuploads
the image. This secret data will not loss even if it shared by
different people.
3.1 Algorithm to hide data
Step 1: Load image into a variable ‘image’.
Step 2: Check whether the image is already contains any
contact number or not by reverse algorithm.
Step 3: If the image does not contain any numberthenchecks
the mode of image.
Step 4: If the image is an RGB image then store the secret
message into a variable ‘msg’ and set,
length= len(msg)
width, height= image . size
index= 0
encoded= image.copy()
Step 5: Repeat the following steps 6 to 8 until reachesthelast
pixel
Step 6: Store RGBcomponentof 1 pixel into variables r, gand
b
Step 7: if index < length then
c= msg[index]
imsg= int (ord(c))
r1= imsg & 7
imsg= imsg >> 3
g1=imsg & 7
imsg= imsg >> 3
b1=imsg & 7
r= r & 248
g= g & 248
b= b & 252
r= r | r1
g= g | g1
b= b| b1
Step 8: encode.putpixel((col,row),(r,g,b)) index= inex+1
Step 9: Stop
3.2 Algorithm to retrieve data
Step 1: Load image into a variable ‘image’
Step 2: Check whether the image is already contains any
contact number or not
Step 3: If the image does not contain any numberthenchecks
the mode of image
Step 4: If the image is an RGB image then store the secret
message into a variable ‘msg’ and set ,
width, height= image . size
index= 0
Step 5: Repeat the following steps 6 to 8 until reachesthelast
pixel
Step 6: Store RGBcomponentof 1 pixel into variables r, gand
b
Step 7: if index < length then
r1= r & 7
g1= (g & 7) << 3
b1= (b & 3) << 6
val = r1 | g1 | b1
msg = msg + (str ( chr ( val ) ) )
Step 8: index= inex+1
Step 9: Stop

4. CONCLUSION
We have studied about the spreading of fake news through
social media and this project aims to control these
fraudulent activities. We have used LSB substitution
algorithm to hide the secret data within the image. This
method is very simple and we can easily extract contact
number from the image by just applying the reverse
algorithm. We have tested our solutionona samplenetwork.
This method proves that it is possible to extract the contact
number of the uploader even if it shared many times.
REFERENCES
[1] H. Zenon, V. Sviatoslav, R.Yuriy, "Cryptography and
steganography of video information in modern
communications," 1998,
Citeseer.ist.psu.edu/hrytskiv98cryptography.html
[2] M.M. Amin, M. Salleh, S. Ibrahim, M.R Katmin, M.Z.I.
Shamsuddin, "Informationhidingusingsteganography,"
Telecommunication Technology, 2003. NCTT 2003
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Workshop oninformationHiding,Noordwijkerhout,The
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[4] EE. Kisik Chang, J. Changho, L. Sangjin, "High Quality
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[14] G. Prashanti, K. Sandhyarani, “A New Approach for Data
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