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Traffic Pattern-Based Content Leakage Detection for 
Trusted Content Delivery Networks 
ABSTRACT: 
Due to the increasing popularity of multimedia streaming applications and services 
in recent years, the issue of trusted video delivery to prevent undesirable content-leakage 
has, indeed, become critical. While preserving user privacy, conventional 
systems have addressed this issue by proposing methods based on the observation 
of streamed traffic throughout the network. These conventional systems maintain a 
high detection accuracy while coping with some of the traffic variation in the 
network (e.g., network delay and packet loss), however, their detection 
performance substantially degrades owing to the significant variation of video 
lengths.In this paper, we focus on overcoming this issue by proposing a novel 
content-leakage detection scheme that is robust to the variation of the video length. 
By comparing videos of different lengths, we determine a relation between the 
length of videos to be compared and the similarity between the compared videos. 
Therefore, we enhance the detection performance of the proposed scheme even in 
an environment subjected to variation in length of video. Through a testbed
experiment, the effectiveness of our proposed scheme is evaluated in terms of 
variation of video length, delay variation, and packet loss. 
EXISTING SYSTEM: 
A crucial concern in video streaming services is the protection of the bit stream 
from unauthorized use, duplica-tion and distribution. One of the most popular 
approaches to prevent undesirable contents distribution to unauthorized users 
and/or to protect authors’ copyrights is the digital rights management (DRM) 
technology. Most DRM techni-ques employ cryptographic or digital watermark 
techniques.However, this kind of approaches have no significant effect on 
redistribution of contents, decrypted or restored at the user-side by authorized yet 
malicious users. 
DISADVANTAGES OF EXISTING SYSTEM: 
Moreover, redistribution is technically no longer difficult by using peer-to-peer 
(P2P) streaming software . Hence,streaming traffic may be leaked to P2P 
networks.
PROPOSED SYSTEM: 
In this paper, we focus on the illegal redistribution of streaming content by an 
authorized user to external networks.The existing proposals monitor information 
obtained at different nodes in the middle of the streaming path. The retrieved 
information are used to generate traffic patterns which appear as unique waveform 
per content, just like a fingerprint. 
ADVANTAGES OF PROPOSED SYSTEM: 
 These technologies enhance the distribution of any type of information over the 
Internet . 
 The traffic pattern generation process performed in conventional methods.
SYSTEM ARCHITECTURE: 
SYSTEM REQUIREMENTS: 
HARDWARE REQUIREMENTS: 
 System : Pentium IV 2.4 GHz. 
 Hard Disk : 40 GB. 
 Floppy Drive : 1.44 Mb. 
 Monitor : 15 VGA Colour.
 Mouse : Logitech. 
 Ram : 512 Mb. 
SOFTWARE REQUIREMENTS: 
 Operating system : Windows XP/7. 
 Coding Language : JAVA/J2EE 
 IDE : Netbeans 7.4 
 Database : MYSQL 
REFERENCE: 
Hiroki Nishiyama, Desmond Fomo, Zubair Md. Fadlullah, and Nei Kato “Traffic 
Pattern-Based Content Leakage Detection for Trusted Content Delivery 
Networks” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED 
SYSTEMS,VOL. 25,NO. 2,FEBRUARY 2014.

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JPJ1445 Traffic Pattern-Based Content Leakage Detection for Trusted Content Delivery Networks

  • 1. Traffic Pattern-Based Content Leakage Detection for Trusted Content Delivery Networks ABSTRACT: Due to the increasing popularity of multimedia streaming applications and services in recent years, the issue of trusted video delivery to prevent undesirable content-leakage has, indeed, become critical. While preserving user privacy, conventional systems have addressed this issue by proposing methods based on the observation of streamed traffic throughout the network. These conventional systems maintain a high detection accuracy while coping with some of the traffic variation in the network (e.g., network delay and packet loss), however, their detection performance substantially degrades owing to the significant variation of video lengths.In this paper, we focus on overcoming this issue by proposing a novel content-leakage detection scheme that is robust to the variation of the video length. By comparing videos of different lengths, we determine a relation between the length of videos to be compared and the similarity between the compared videos. Therefore, we enhance the detection performance of the proposed scheme even in an environment subjected to variation in length of video. Through a testbed
  • 2. experiment, the effectiveness of our proposed scheme is evaluated in terms of variation of video length, delay variation, and packet loss. EXISTING SYSTEM: A crucial concern in video streaming services is the protection of the bit stream from unauthorized use, duplica-tion and distribution. One of the most popular approaches to prevent undesirable contents distribution to unauthorized users and/or to protect authors’ copyrights is the digital rights management (DRM) technology. Most DRM techni-ques employ cryptographic or digital watermark techniques.However, this kind of approaches have no significant effect on redistribution of contents, decrypted or restored at the user-side by authorized yet malicious users. DISADVANTAGES OF EXISTING SYSTEM: Moreover, redistribution is technically no longer difficult by using peer-to-peer (P2P) streaming software . Hence,streaming traffic may be leaked to P2P networks.
  • 3. PROPOSED SYSTEM: In this paper, we focus on the illegal redistribution of streaming content by an authorized user to external networks.The existing proposals monitor information obtained at different nodes in the middle of the streaming path. The retrieved information are used to generate traffic patterns which appear as unique waveform per content, just like a fingerprint. ADVANTAGES OF PROPOSED SYSTEM:  These technologies enhance the distribution of any type of information over the Internet .  The traffic pattern generation process performed in conventional methods.
  • 4. SYSTEM ARCHITECTURE: SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS:  System : Pentium IV 2.4 GHz.  Hard Disk : 40 GB.  Floppy Drive : 1.44 Mb.  Monitor : 15 VGA Colour.
  • 5.  Mouse : Logitech.  Ram : 512 Mb. SOFTWARE REQUIREMENTS:  Operating system : Windows XP/7.  Coding Language : JAVA/J2EE  IDE : Netbeans 7.4  Database : MYSQL REFERENCE: Hiroki Nishiyama, Desmond Fomo, Zubair Md. Fadlullah, and Nei Kato “Traffic Pattern-Based Content Leakage Detection for Trusted Content Delivery Networks” IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,VOL. 25,NO. 2,FEBRUARY 2014.