seminar on to block unwanted messages _from osn
DESCRIPTION
Seminar On To Block Unwanted Messages From Online Social NetworkingTRANSCRIPT
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SEMINAR ON To Block Unwanted Messages
From OSN
PRESENTED BY:- Shailesh kumar
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CONTENT• Introduction• Current technologies• Filtered wall architecture• Filtering and Blacklist rules• Applications• Conclusion
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WHAT IS OSN ??
Online Social Network MySpace Facebook Linkedin Twitter
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WHAT IS SPAM MESSAGE ??
Junk email which contains Unwanted resource, viruses, worms, and scams.
Unwanted content on particular public/private areas.
Unwanted comments in blogs
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NEED OF FILTERING……. Spam, phishing and malware attacks through social media are growing.
of social media usersreport being hit by spamvia these services
57% 70.6%That’s an increase of
from a year ago
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NEED OF FILTERING Prevent unwanted emails,or messages
from reaching a user’s inbox.
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CURRENT TECHNOLOGIES
Content based Filtering . Information Filtering . Policy-Based Personalization . Maximum Likelihood
Estimation.
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CONVENTIONAL APPROACH: CONTENT BASED FILTERING
Trying to hit a moving target...
...and even mp3s!
PDFs Excel sheets Images
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FILTERED WALL ARCHITECTURE Filtered wall architecture Is a Three-tier
structure.
a.Social Network Manager (SNM) b.Social Network Application (SNA) c.Graphical User Interface (GUI)
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FILTERED WALL CONCEPTUAL ARCHITECTURE
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SOCIAL NETWORK MANAGER(SNM)
It is a Initial layer. Maintains data
regarding to the user profile.
Provides essential OSN functionalities.
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SOCIAL NETWORK APPLICATION (SNA)
It consists of CBMF and Short Text Classifier.
Important layer for message categorization.
Black list is maintained for the users.
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GRAPHICAL USER INTERFACE (GUI) GUI is consists of Filtered Wall. Provides Interface to the user who
wants to post. Filtering Rules are used to filter the
unwanted messages . Provides Black list for the user .
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FILTERING RULES INPUT:- FR= {Author, UserSpec, ContentSpec} PROCESS:-
FM={UserSpec,contentSpec==category(Violence,Vulgar,offensive,Hate,Sextual)}
OUTPUT:- PFM= {ContentSpec, M||Y}
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BLACKLISTS {Author,creatorSpec, creatorBehavior, T}• RF blocked = #bMessages #tMessages Where, #bmessage is Messages that have been blocked, #tMessages is the total number of messages. • minBanned = (min, mode, window)
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APPLICATIONS DicomFWFacebook application that emulates a personal wall using combination of the proposed FRs.
1. view the list of users’ FWs;2. view messages and post a new one on a FW;3. define FRs using the OSA tool.
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IF YOU R BLOCKED………
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FUTURE SCOPE There is a real and huge need in the OSN
for such services. Finally, despite the challenges, the field
has made significant progresses over the past few years.
This work is the first step of a wider project. The encouraging results obtained prompt
us to continue with other work that will improve the quality of classification.
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CONCLUSION Filtered wall is a system to filter undesired
messages from OSN walls. This system approach decides when user
should be inserted into a black list. Filtered wall has a wide variety of
applications in OSN wall. In future, more work is needed on further
improving the performance measures.
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REFERENCES Marco Vanetti, Elisabetta Binaghi, Elena Ferrari,
Barbara Carminati, and Moreno Carullo,” A System to Filter Unwanted Messages from OSN User Walls”,IEEE Trans. Knowledge and Data Eng., vol. 25, no. 2, pp. 1041-4347 February 2013.
J. Golbeck, “Combining Provenance with Trust in Social Networks for Semantic Web Content Filtering,” Proc. Int’l Conf. Provenance and Annotation of Data, L. Moreau and I. Foster, eds., pp. 101-108, 2006.
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THANK YOU