cloud basedmultimedia

8/19/2019 Cloud Basedmultimedia

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CLOUD-BASED MULTIMEDIA CONTENT PROTECTION

SYSTEM

Abstract — We propose a new design for large-scale multimedia content protection

systems. Our design leverages cloud infrastructures to provide cost efficiency,

rapid deployment, scalability, and elasticity to accommodate varying workloads.

The proposed system can be used to protect different multimedia content types,

including 2-D videos, -D videos, images, audio clips, songs, and music clips. The

system can be deployed on private and!or public clouds. Our system has two novel

components" #i$ method to create signatures of -D videos, and #ii$ distributed

matching engine for multimedia ob%ects. The signature method creates robust and

representative signatures of -D videos that capture the depth signals in these

videos and it is computationally efficient to compute and compare as well as it

re&uires small storage. The distributed matching engine achieves high scalability

and it is designed to support different multimedia ob%ects. We implemented the

proposed system and deployed it on two clouds" 'ma(on cloud and our private

cloud. Our e)periments with more than **,+++ -D videos and * million images

show the high accuracy and scalability of the proposed system. n addition, we

compared our system to the protection system used by ouTube and our results

show that the ouTube protection system fails to detect most copies of -D videos,

while our system detects more than /0 of them. This comparison shows the need

for the proposed -D signature method, since the state-of-the-art commercial

system was not able to handle -D videos


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EXISTING SYSTEM:

The problem of protecting various types of multimedia content has attracted

significant attention from academia and industry. One approach to this problem is

using watermarking, in which some distinctive information is embedded in the

content itself and a method is used to search for this information in order to verify

the authenticity of the content. Watermarking re&uires inserting watermarks in the

multimedia ob%ects before releasing them as well as mechanisms!systems to find

ob%ects and verify the e)istence of correct watermarks in them. Thus, this approach

may not be suitable for already-released content without watermarks in them. The

watermarking approach is more suitable for the somewhat controlled

environments, such as distribution of multimedia content on D1Ds or using special

sites and custom players. Watermarking may not be effective for the rapidly

increasing online videos, especially those uploaded to sites such as ouTube and

played back by any video player. Watermarking is not the focus of this paper. The

focus of this paper is on the other approach for protecting multimedia content,

which is content-based copy detection #3D$. n this approach, signatures #or fingerprints$ are e)tracted from original ob%ects. 4ignatures are also created from

&uery #suspected$ ob%ects downloaded from online sites. Then, the similarity is

computed between original and suspected ob%ects to find potential copies. 5any

previous works proposed different methods for creating and matching signatures.

These methods can be classified into four categories" spatial, temporal, color, and

transform-domain. 4patial signatures #particularly the block-based$ are the most

widely used. 6owever, their weakness is the lack of resilience against large

geometric transformations. Temporal and color signatures are less robust and can

be used to enhance spatial signatures. Transform-domain signatures are


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computationally intensive and not widely used in practice. 7or more details, see

surveys for audio fingerprinting and 2-D video fingerprinting.

PROPOSED SYSTEM:

The proposed system is fairly comple) with multiple components, including" #i$

crawler to download thousands of multimedia ob%ects from online hosting sites, #ii$

signature method to create representative fingerprints from multimedia ob%ects, and

#iii$ distributed matching engine to store signatures of original ob%ects and match

them against &uery ob%ects. We propose novel methods for the second and third

components, and we utili(e off-the-shelf tools for the crawler. We have developed

a complete running system of all components and tested it with more than **,+++

-D videos and * million images. We deployed parts of the system on the 'ma(on

cloud with varying number of machines #from eight to *2/$, and the other parts of

the system were deployed on our private cloud. This deployment model was used

to show the fle)ibility of our system, which enables it to efficiently utili(e varying

computing resources and minimi(e the cost, since cloud providers offer different

pricing models for computing and network resources. Through e)tensive

e)periments with real deployment, we show the high accuracy #in terms of

precision and recall$ as well as the scalability and elasticity of the proposed

system.


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CONCLUSION AND FUTURE WORK

Distributing copyrighted multimedia ob%ects by uploading them to online hosting

sites such as ouTube can result in significant loss of revenues for content creators.

4ystems needed to find illegal copies of multimedia ob%ects are comple) and large

scale. n this paper, we presented a new design for multimedia content protection

systems using multi-cloud infrastructures. The proposed system supports different

multimedia content types and it can be deployed on private and!or public clouds.

Two key components of the proposed system are presented. The first one is a new

method for creating signatures of -D videos. Our method constructs coarse-

grained disparity maps using stereo correspondence for a sparse set of points in the

image. Thus, it captures the depth signal of the -D video, without e)plicitly

computing the e)act depth map, which is computationally e)pensive. Our

e)periments showed that the proposed -D signature produces high accuracy in

terms of both precision and recall and it is robust to many video transformations

including new ones that are specific to -D videos such as synthesi(ing new views.

The second key component in our system is the distributed inde), which is used to

match multimedia ob%ects characteri(ed by high dimensions. The distributed inde)

is implemented using the 5ap8educe framework and our e)periments showed that

it can elastically utili(e varying amount of computing resources and it produces

high accuracy. The e)periments also showed that it outperforms the closest system

in the literature in terms of accuracy and computational efficiency. n addition, we

evaluated the whole content protection system with more than **,+++ -D videos

and the results showed the scalability and accuracy of the proposed system.

7inally, we compared our system against the ontent D system used by ouTube.

Our results showed that" #i$ there is a need for designing robust signatures for -D

videos since the current system used by the leading company in the industry fails


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to detect most modified -D copies, and #ii$ our proposed -D signature method

can fill this gap, because it is robust to many 2-D and -D video transformations.

The work in this paper can be e)tended in multiple directions. 7or e)ample, our

current system is optimi(ed for batch processing. Thus, it may not be suitable for

online detection of illegally distributed multimedia streams of live events such as

soccer games. n live events, only small segments of the video are available and

immediate detection of copyright infringement is crucial to minimi(e financial

losses. To support online detection, the matching engine of our system needs to be

implemented using a distributed programming framework that supports online

processing, such as 4park. n addition, composite signature schemes that combine

multiple modalities may be needed to &uickly identify short video segments.

7urthermore, the crawler component needs to be customi(ed to find online sites

that offer pirated video streams and obtain segments of these streams for checking

against reference streams, for which the signatures would also need to be generated

online. 'nother future direction for the work in this paper is to design signatures

for recent and comple) formats of -D videos such as multiview plus depth. '

multiview plus depth video has multiple te)ture and depth components, which

allow users to view a scene from different angles. 4ignatures for such videos would

need to capture this comple)ity, while being efficient to compute, compare, and

store.

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