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Cross-Platform Identification of Anonymous Identical Users in Multiple
Social MediaNetworks
Abstract:
• Many types of social networking sites have emerged and contributed
immensely to large volumes of real-world data on social behaviors.
• Recognizing anonymous, yet identical users among multiple SMNs is still
an intractable problem . Moreover, since online SMNs are quite symmetric,
existing user identification schemes based on network structure are not
effective .
• In this proposed To predict the unwanted message shared person from the
Social media networks.
• In this we use joint link attribute algorithm. JLA considered both profile
attributes and network properties.
We also developed two propositions to improve the efficiency of the algorithm.
Results of
extensive experiments demonstrate that FRUI performs much better than current
network structure-based algorithms.
Existing System:
• In Existing FRUI (Friend Relationship-Based User Identification
(FRUI) algorithm used to identify the Anonymous user in social media
networks.
• FRUI calculates a match degree for all candidate User Matched Pairs
(UMPs), and only UMPs with top ranks are considered as identical users. It
need two propositions to improve the efficiency of the algorithm.
Disadvantages:
• It is less Efficient.
• It will not identify all identical users .
Proposed System:
• Identifying anonymous users across multiple SMNs is challenging work.
Therefore, only a portion of identical users with different nicknames can be
recognized with this method. In this system use a approach to developed
for identify all identical users with different nicknames.
• user identification methods can be applied simultaneously to examine
multiple SMN platforms.
• We proposed the concept to block the anonymous users who send
repeateadly unwanted messages.to predict the anonymous users from the
data set then block the user from the social media network.
• To address this problem, proposed an approach based on conditional
random fields called Joint Link-Attribute (JLA). JLA considered both profile
attributes and network properties.
Advantages:
System Requirements:
• Hardware Requirements:
System
: Pentium IV 2.4 GHz.
Hard Disk
: 160 GB.
Floppy Drive : 1.44 Mb.
Monitor
: 15 VGA Color.
Mouse
: Logitech.
RAM
: 2GB.
• Software Requirements:
Operating system: Windows XP.
Front End
: C#
Back End
: SQL Server2012
References:
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traceable are usernames?," Privacy Enhancing Technologies (PETS’11), pp.
1-17, 2011.
 J. Liu, F. Zhang, X. Song, Y.I. Song, C.Y. Lin, and H.W. Hon,"What's in a
name?: an unsupervised approach to link users across communities," Proc.
of the 6th ACM international conference on Web search and data
mining(WDM’13), pp. 495-504, 2013.
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communities," Proc. of the 3rd International ICWSM Conference, pp. 354357, 2009.
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International Conference Knowledge Discovery and Data Mining
(KDD’13), pp.41-49, 2013.
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