Secure system based on recombined fingerprints for sharing multimedia files in peer to peer networks

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 04 Issue: 06 | June-2015, Available @ http://www.ijret.org 73
SECURE SYSTEM BASED ON RECOMBINED FINGERPRINTS FOR
SHARING MULTIMEDIA FILES IN PEER TO PEER NETWORKS
D.Amu1
, C.Roselinmary2
, M.Priya3
, S.Vaishnavi4
1
Assistant professor, Dept of Information Technology, Alpha College of Engineering & Technology, Pondicherry
2
B.Tech Student, Dept of Information Technology, Alpha College of Engineering & Technology, Pondicherry
3
4
Abstract
In this paper the execution time is less when compared to previous algorithm. And also it provide security between the merchant
and buyer The traitor tracing protocol is used to detect the illegal transaction. Here we used fingerprinting solution to avoid
illegal redistribution of multimedia contents. Here we convert the multimedia video file into image then encrypting the image after
the encrypted image will be transferred from merchant to buyer. The buyer receives the copyright protection from merchant, he
decrypts the image then converts it into video. After that, the copyright protection of file is transferred to child buyer. Then tracing
traitor protocol is used to checks the fingerprints for merchant to buyer and buyer to child buyer. Traitor tracing protocol is used
to detect the illegal transaction of the content. The Blowfish algorithm is used to encrypt and decrypt the multimedia files. Finally
we detect the performance of our work based on efficiency, accuracy and we achieve security.
Keywords: Fingerprint, Multimedia files, Blowfish algorithm, Merchant, Buyer, Child Buyer, Copyright Protection
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1. INTRODUCTION
Network security consists of the provisions and policies
adopted by a network administrator to prevent and monitor
unauthorized access, misuse, modification, or denial of a
computer network and network-accessible resources.
Network security involves the authorization of access to
data in a network, which is controlled by the network
administrator. Users choose or are assigned an ID and
password or other authenticating information that allows
them access to information and programs within their
authority. Network security covers a variety of computer
networks, both public and private, that are used in everyday
jobs conducting transactions and communications among
businesses, government agencies and individuals. Networks
can be private, such as within a company, and others which
might be open to public access. Network security is
involved in organizations, enterprises, and other types of
institutions.
It does as its title explains: It secures the network, as well as
protecting and overseeing operations being done. The most
common and simple way of protecting a network resource is
by assigning it a unique name and a corresponding
password.
Network security starts with authenticating, commonly with
a username and a password. Since this requires just one
detail authenticating the user name i.e. the password this is
sometimes termed one-factor authentication. With two-
factor authentication, something the user 'has' is also used
(e.g. a security token or 'dongle', an ATM card, or a mobile
phone); and with three-factor authentication, something the
user 'is' is also used. Once authenticated, a firewall enforces
access policies such as what services are allowed to be
accessed by the network users. Though effective to prevent
unauthorized access, this component may fail to check
potentially harmful content such as computer worms or
Trojans being transmitted over the network. Anti-virus
software or an intrusion prevention system (IPS. help detect
and inhibit the action of such malware. An anomaly-based
intrusion detection system may also monitor the network
like wireshark traffic and may be logged for audit purposes
and for later high-level analysis. Fingerprinting emerged as
a technological solution to avoid illegal content re-
distribution. Basically, fingerprinting consists of embedding
an imperceptible mark –fingerprint– in the distributed
content to identify the content buyer. The embedded mark is
different for each buyer, but the content must stay
perceptually identical for all buyers. Fingerprinting schemes
deter people from illegally redistributing digital data by
enabling the original merchant of the data to identify the
original buyer of a redistributed copy. Recently, asymmetric
fingerprinting schemes were introduced. Here, only the
buyer knows the fingerprinted copy after a sale, and if the
merchant finds this copy somewhere, he obtains a proof that
it was the copy of this particular buyer. In case of illegal re-
distribution, the embedded mark allows the identification of
the re-distributor by means of a traitor tracing system,
making it possible to take subsequent legal actions.
Although fingerprinting techniques have been available for
nearly two decades, the first few proposals in this field are
far from nowadays’ requirements such as scalability for
thousands or millions of potential buyers and the
preservation of buyers’ privacy.

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Most fingerprinting systems can be classified in three
categories, namely symmetric, asymmetric and anonymous
schemes. In symmetric schemes, the merchant is the one
who embeds the fingerprint into the content and forwards
the result to the buyer; hence, the buyer cannot be formally
accused of illegal redistribution, since the merchant also had
access to the fingerprinted content and could be responsible
for the redistribution. In asymmetric fingerprinting, the
merchant does not have access to the fingerprinted copy, but
he can recover the fingerprint in case of illegal re-
distribution and thereby identify the offending buyer. In
anonymous fingerprinting, in addition to asymmetry, the
buyer preserves her anonymity (privacy) and hence she
cannot be linked to the purchase of a specific content, unless
she participates in an illegal re-distribution. Peer-to-peer
(P2P) computing or networking is a distributed application
architecture that partitions tasks or workloads between
peers. Peers are equally privileged, equipotent participants
in the application.
They are said to form a peer-to-peer network of nodes. Peers
make a portion of their resources, such as processing power,
disk storage or network bandwidth, directly available to
other network participants, without the need for central
coordination by servers or stable hosts. Peers are both
suppliers and consumers of resources, in contrast to the
traditional client-server model in which the consumption
and supply of resources is divided. Emerging collaborative
P2P systems are going beyond the era of peers doing similar
things while sharing resources, and are looking for diverse
peers that can bring in unique resources and capabilities to a
virtual community thereby empowering it to engage in
greater tasks beyond those that can be accomplished by
individual peers, yet that are beneficial to all the peers.
Many anonymous fingerprinting schemes exploit the
homomorphic property of public-key cryptography. These
schemes allow embedding the fingerprint in the encrypted
domain (with the public key of the buyer) in such a way that
only the buyer obtains the decrypted fingerprinted content
after using her private key. Other approaches for anonymous
fingerprinting do not exploit homomorphic encryption in
this way, but either 1) require highly demanding
technologies such as public-key encryption of the contents,
secure multiparty protocols, commitment protocols or zero-
knowledge proofs, among others, incurring prohibitive
computational and communicational costs; or 2) are based
on theoretical secure embedding algorithms for which no
proof of existence is available.
2. RELATED WORK
2.1 Rational Peer to Peer
The authors J.Domirgo-Ferror and D.Megias proposed
this “Distributed multicast of fingerprinted content based on
a rational peer-to Peer community”. In conventional
multicast transmission, one sender sends the same content to
a set of receivers. This precludes fingerprinting the copy
obtained by each receiver (in view of redistribution control
and other applications). A straightforward alternative is for
the sender to separately fingerprint and send in unicast one
copy of the content for each receiver. This approach is not
scalable and may implode the sender. We present a scalable
solution for distributed multicast of fingerprinted content, in
which receivers rationally co-operate in fingerprinting and
spreading the content. Furthermore, fingerprinting can be
anonymous, in order for honest receivers to stay
anonymous. This paper focuses on proposing a multicast
approach to the anonymous fingerprinting problem which
meets these two goals and shows a proof of concept with a
practical implementation of the proposed system. The idea is
to transfer the burden of a centralized fingerprinting
technology to a distributed network of buyers who will
collaborate to produce further copies of the fingerprinted
contents.
The solution guarantees the following properties:
Correctness: All protocols terminate successfully whenever
players are honest (no matter how other players behaved in
other protocols). Anonymity and unlinkability: Without
obtaining a particularDB, the merchant even when colluding
with the registration center– cannot identify a buyer
(anonymity). Furthermore, the merchant is not able to tell
whether two purchases were made by the same buyer
(unlinkability). Revocability and collusion resistance: Any
collusion of up tocbuyers aiming at producing a version b
D2Dfrom which none of them can be re-identified will fail:
frombDthe merchant will obtain enough information to
identify at least one collusion member. The content carries a
different anonymous fingerprint for each receiver, so that
unlawful content redistribution can be tracked ; honest
receivers stay anonymous. The sender does not need to
fingerprint and send the content individually to each
receiver; one fingerprinting and one unicast transmission by
the server to one collaborative receiver are enough to
bootstrap the process.
The advantages aided in this method are time domain
synchronization watermark is embedded for fast search of
information watermark position.A frequency-domain
information watermark is embedded next to the SYN
marks.Disadvantage of our proposed peer-peer multicast
protocol only deals with the redistribution control.
2.2 Spread Spectrum Fingerprinting in Asymmetric
Cryptographic Protocol
The author M.Kuribayashi Proposed this “On the
Implementation of Spread Spectrum Fingerprinting in
Asymmetric Cryptographic Protocol.Asymmetric Property
If both a buyer and a seller obtain a fingerprinted content in
a fingerprinting protocol, the seller cannot prove to a third
party about the illegal distribution by the buyer, even if the
buyer's fingerprint is extracted. This is because the seller
may distribute it himself in order to frame an innocent
buyer. Hence, it is desirable that only a buyer is able to
obtain his own fingerprinted content in the protocol. Such a
protocol is called asymmetric fingerprinting protocol. We
propose the method for implementing the spread spectrum
watermarking technique by carefully designing parameters
for rounding operation. If frequency components of digital

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contents are used for the embedding fingerprint information,
they must be quantized in order to truncate real value to
integer. Then, the precision of the frequency components
should be considered in order not to degrade a watermarked
image. When the spread spectrum watermarking technique
in is applied, the precision of the representing watermark
signal is sensitive for the implementation. By scaling up the
parameters by multiplying a constant factor, the precision is
increased in our scheme. Then, the trade-off between the
scaling factor and the amount of data to be transmitted must
be considered. In addition, for the characteristic of the
fingerprinting protocol, frequency components and the
watermark signal must be separately encrypted after
quantization. In such a case, the consistency of the precision
is a sensitive issue. Since an embedding operation is
performed by addition of frequency components and a
spread spectrum sequence, the additive homomorphic
property of public-key cryptosystems can be directly
exploited for the embedding. Then, the separate rounding
operation causes interference term in a deciphered data at a
buyer side. Without loss of secrecy of an original content,
the interference term is removed after decryption. The
performance of our proposed method is evaluated
comparing with the conventional scheme, which conrms the
similar identification capability of illegal buyers. In a
fingerprinting scheme, each fingerprinted copy is slightly
different, hence, malicious users will collect some copies
with respective watermark in order to remove/alter the
watermark. Collusion-secure code which has traceability of
colluders.In the watermarking algorithm, it consists of
Embedding and Decryption and Post-Processing.
Advantages is the embedding operation can be easily
performed using the additive homomorphic property of
public-key cryptosystems such as the Okamoto-Uchiyama
encryption scheme. Disadvantages is we can simulate the
scheme on the cryptographic protocol with a limited
precision.
3. EXISTING SYSTEM
3.1 Security Model
The security assumptions of the systems are the following:
The merchant does not need to be trusted the either for
distribution or to associate a pseudonym with the identity of
the buyer. Buyers are not trusted and protocols are provided
to guarantee that 1. They are transferring authenticated
fragments of contents. 2. Their anonymity can be revoked
incase of illegal re-distribution.
The transaction monitor will not have access to the clear text
of the fingerprints. This prevents that any single party single
party can frame an innocent buyer.
The transaction monitor is trusted as the symmetric keys
used for encrypting the fragments. This means that the
Transaction monitor stores the key provided by each parent
buyer and this key can be retrieved only once from its
database.The transaction monitor returns the true
pseudonym corresponding to an illegal re-distributor in the
traitor tracing protocol. This trust can be replaced by a
collection of signatures provided by the proxies. The tracing
authority is a part of the legal system and shall be trusted the
communication between the merchant and the seed buyer
and between the peer buyers within the P2P distribution
system must be anonymous using an onion routing- like
approach. The fragments of content are encrypted using
symmetric cryptography. The proxies are not trusted and the
fragments sent through them shall be encrypted in such a
way that only the sender and the recipient have access to
their clear text.
The multimedia content is divided into several fragments
and each of the fragments is embedded separately with a
random binary sequence. The binary sequence of each
fragment is called segment and the concatenation of all
fragments forms the whole fingerprints. The merchant
distributes the different copies to the seed buyer and
fingerprints of this buyer. After that the buyer receives the
fragments from seed buyer. Then the communication
between the peer buyers is anonymous through onion
routing-like protocol using a proxy. Proxies know the
pseudonyms of source and destination buyers and they have
access to the symmetric keys used for encrypting the
multimedia content. Transaction record is created by
transaction monitor to keep track of each transfer between
peer buyers. These records do not contain the fingerprints,
but only an encrypted hash of them. The fingerprints’ hashes
are encrypted in such a way that the private key of at least
one parent is required for obtaining their clear text. The real
identities of buyers are known only by the merchant.
3.2 Peer to Peer Distribution Protocol
In the original distribution protocol the fingerprints were not
stored in the traitor tracing monitor in order to protect the
privacy of the buyer. Only the hash of the fingerprint was
stored for each buyer. The fingerprint’s hash was encrypted
and stored as many times as parents each buyer each buyer
had, using the public key of the parent for encryption. The
transaction registers would be formed as follows:
Pi --> Username of the buyer
H(c)-> Perceptual content hash
Ehi-> Encrypted hash of the buyer’s fingerprint.
Efi-> Encrypted buyer’s fingerprint.
d-> Transaction date and time.
the transaction monitor stores the following encrypted
version of the fingerprint:
Efi = E (E c
g1 |E c
g2 |….E c
gm ,Ka ) |…..| E (E c
g(L-1)m+2 | Ec
g(L-
1)m+2 |…|E c
gLm ,Ka ).
3.3 Algorithm Description
DES algorithm used in previous work. It uses 64 bit block
cipher and it encrypts 64 bit data at a time. DES uses the
two basic techniques of cryptography - confusion and
diffusion. At the simplest level, diffusion is achieved
through numerous permutations and confusions is achieved
through the XOR operation. The execution time is slow in
DES algorithm.

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4. PROPOSED SYSTEM
To overcome the problems in the existing system, here we
include so many improved measures. In our proposed
system the components we are going to include are
Merchant, seed buyers, other buyers, proxies, tracing
authority and transaction monitor. The work of the merchant
is that he distributes copies of the content legally to the seed
buyers. Each fragment of the content contains a different
segment of the fingerprint embedded into it. The segments
have low pair-wise correlations. The work of seed buyers is
they receive fingerprinted copies of the contents from the
merchant that are used by the P2P distribution system to
bootstrap the system. The works of other buyers are they
purchase the content and obtain their fingerprinted copies
from the P2P distribution system. The content is assembled
from fragments obtained from different parents. Anonymous
connections with peer buyers are provided by means of
proxies. The duties of proxies are they provide anonymous
communication between peer buyers by means of a specific
protocol analogous to Chaum’s mix networks. The work of
tracing monitor is it keeps a transaction register for each
purchase carried out for each buyer. This transaction register
includes an encrypted version of the embedded fingerprints.
The work of tracing authority in case of illegal re-
distribution, it participates in the tracing protocol that is
used to identify the illegal re-distributor(s).The
watermarking method used for embedding and detecting the
fingerprint is transparent, robust and secures enough for a
fingerprinting application. Collusion occurs when several
buyers decide to recombine their fingerprinted copies of a
given content trying to obtain a new copy in which neither
of their fingerprints is detectable. Buyer frameproofness is
related to the possibility that an innocent buyer is accused of
illegal redistribution of the purchased content.
Advantages
 Our proposed system improves the efficiency of the
fingerprinted system
 It also preserves the privacy of the original copy of the
multimedia file
 It effectively detects the traitors who are all misuse the
original copy of multimedia file.
 It uses the recombined fingerprints for validation, so it
generates the effective result.
4.1 Comparison between DES and Blowfish
Algorithm Block
size
Bits Time
consumption
Execution
time
DES 64 bits 64 bits Low high
Blowfish 64 bits 32 to
448
bits
High low
4.2 System Modules
 Data distribution
 Fingerprinted copies to seed buyers
 Distribution to other buyers
 Transaction Monitoring
 Traitor tracing protocol
4.2.1 Data Distribution
In the data distribution process, it first identify the merchant
information. That is full details about the merchant,
merchant id, etc. After that merchant should select the
multimedia file which they going to send to the buyers. In
the process, the name of the multimedia file, type of the
multimedia file and extension of the multimedia file finally
size of the multimedia file are displayed. After that in a
client server process they transmit the merchant information
and the contents they are going to send to the buyers are
viewed. Finally the buyers who are all take part in this file
sharing process are viewed. Here we select the final
selection of buyer and merchant information.
4.2.2 Fingerprinted Copies to Seed Buyers
After the analyzing process, the copies are ready to send to
the buyers. Before the transmission process, we are going to
encrypt the copies. In this process we are going to convert
the multimedia file into number of copies of images. After
that view the information about the images we convert
during the first process. Finally we encrypt the images using
AES algorithm. Using the encryption algorithm we encrypt
the images which we converted during the conversion
process. Finally send the encrypted image copies to the seed
buyers.
4.2.3 Distribution to Other Buyers
The encrypted copies are first received to the seed buyers.
After the copies are received at the seed buyers, these copies
are ready to send to the other buyers. In the middle process,
the copies are converted into the binary values. This binary
value is mainly used for the validation process. These binary
values are the fingerprints of the copies of the video files.
There are separate fingerprint is generated for the each and
every copies send to the seed buyers, from the seed buyers
to the other buyers. Here we show the binary values of the
fingerprints of the copies of the multimedia files are viewed.
4.2.4 Transaction Monitoring
In the transaction monitoring it contains the record of each
and every transaction. That is the copy of the multimedia
file send from one peer to another peer, the ip of the sender
peer and receiver peer are recorded in the transaction
monitoring. This transaction monitoring is helpful to
identify the illegal distribution of multimedia file copies to
the peer involved in the network. It is like a register which
contains the information about all the peers and transactions
etc After that we show all the transaction information about
the peers takes part in the network.
4.2.5 Traitor Tracing Protocol
It is a final step, in this module it detects the tracing of the
illegal distributors. In case of illegal re-distribution, it
participates in the tracing protocol that is used to identify the

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illegal re-distributor(s).By referring the transaction monitor,
it detect the illegal distribution of videos among the
merchant and the seed buyers.
4.3 Proposed Algorithm Description
Blowfish algorithm is a symmetric block cipher key. It is
used for encryption. It takes a variable-length key, from 32
bits to 448 bits. Blowfish is unpatented and license free
algorithm. Blowfish is a variable-length key block cipher. It
is suitable for applications where the key does not change
often, like a communications link or an automatic file
encrypted. It is significantly faster than most encryption
algorithms when implemented on 32-bit microprocessors
with large data caches. It manipulates data in large blocks. It
has a scalable key from 32 bits to at least 256 bits. It has no
linear structures that reduce complexity. Blowfish has 16
rounds. The input is a 64-bit data element, X. It divides X
into 32-bit halves: XL , XR
Then, for i=1 to 16:
XL= XL XOR Pi
XR = F(XL) XOR XR, Swap XL and XR
4.4 Architechture Diagram
The below figure describes, merchant send video file that
file encrypted into segments. Then the buyer provides their
fingerprints to merchant. After that the buyer decrypts the
file . The blowfish algorithm is used for encryption process.
The buyer’s information stored in tracing monitor. The
tracing monitor used to store database of buyers. And
hashed fingerprints. The tracing protocol is used to detect
illegal transaction in peer to peer network.
Fig1.1 Architechture diagram
5. PERFORMANCE METRICS
The graph defines to compare the execution time between
the DES and blowfish algorithm. When comparing these
algorithms the execution time of blowfish is fast.The
execution finished in earl time. In our improved measure
uses the blowfish algorithm for encrypting the file. The
blowfish algorithm is easy to encrypt the file.
0
20
40
60
80
100
120
E
x
ecu
tio
n
T
im
e
Comparison between
DES and Blowfish
Blowfish
DES
Fig 1.2 Comparison of execution time
6. CONCLUSION AND FUTURE WORK
Merchant did not kno about the fingerprint of the buers.
Some of the the buyers fingerprints are embedded and others
fingerprints are obtained from the recombination. This paper
shows that the co-operation of honest buyers in traitor
tracing entails several relevant drawbacks that can make the

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published system fail under some circumstances. Tracing
authority identify the illegal redistribution of data. And the
correct users can get the data without any interruption. If
any unwanted distribution is made the traitor tracing
protocol detects the illegal re-distribution of the content.
Future work in our project will change the algorithm
concept for execution process or change the protocol to
detect illegal transaction.
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