Implementation of Secondary Available Digital Content Protection

Schemes using Identity-based Signatures

Nozomi Nagashima

, Masaki Inamura

and Keiichi Iwamura

Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan

Center for Research and Collaboration, Tokyo Denki University, Tokyo, Japan

Keywords: Copyright Protection, Edit Control, Digital Signature, ID-based Signature.

Abstract: User generated content (UGC) is widespread, wherein general consumers utilize the Internet to generate

content files. Using this service, content files can be easily created and uploaded. However, copyright is often

not protected on the Internet. An activity known as a creative commons license enables authors to manage the

secondary use of original content files. However, this license cannot prevent malicious editors from using the

original files. Therefore, we propose technical protection measures using the creative commons license and

identity-based signature, wherein authors apply identity-based signatures to content files that need to be

protected. By verifying the signature, malicious edits performed on the files can be detected. We investigated

the processing speed required for this via simulation and used the 3DCG movie editing tool "Miku Miku

Dance" as the content files.

1 INTRODUCTION

The development of the Internet has enabled the easy

generation and publishing of content files. In

particular, services such as YouTube and Nico Nico

Douga allow users to easily publish content files.

User-generated content (UGC) enables browsing and

retrieving such files published by other users.

Therefore, the distribution of secondary content files

has become popular. Herein, it is necessary to protect

the rights of the developer of the original content files

when used as secondary content files. The Creative

Commons license enables the author to manage the

secondary use of his original content files. However,

editors can freely adhere to a Creative Commons

license. Consequently, malicious editors cannot be

prevented from making malicious edits to these files.

Therefore, to prevent the aforementioned issues, we

herein propose technical protection measures

developed by combining the Creative Commons

license and ID-based signature.

We implemented these copyright protection

technologies using a digital signature. The target

content files are a 3DCG model developed using the

3D video creation tool "Miku Miku Dance". On UGC,

there are several advancements that combine studies

https://orcid.org/0000-0001-8056-3820

performed from multiple creators. Therefore,

assuming multiple authors, we adopted ID-based

signatures that do not require verification of public

key certificates.

In the proposed method, the secondary user can

only edit with the author's permission. Verification

fails if an edit is performed without the author’s

permission. If the secondary user complies with the

author's intentions, he or she could use the original

content files without infringing on the author’s rights.

This is achieved by disabling the unauthorized use of

the original content files.

Chapter 2 presents an overview of the existing

literature. Chapter 3 presents the entity, and Chapter

4 presents the algorithm. The simulation results are

discussed in Chapter 5, and the conclusion is

presented in Chapter 6.

2 RELATED WORK

In section 2. 1, we describe existing research on a

scheme that is used for managing content editing.

Tanaka et al. partitioned one 3D model into multiple

content files, thereby enabling the editing of each

Nagashima, N., Inamura, M. and Iwamura, K.

Implementation of Secondary Available Digital Content Protection Schemes using Identity-based Signatures.

DOI: 10.5220/0010245504850491

In Proceedings of the 7th International Conference on Information Systems Security and Privacy (ICISSP 2021), pages 485-491

ISBN: 978-989-758-491-6

485

body component (Tanaka et al, 2017). Thereafter, the

signature method described in Section 2. 2 was used

for protection. In the scheme developed by Tanaka et

al., editing of multiple content files was managed

using the Boneh Lynn Shacham signature (Boneh et

al, 2003). Furthermore, Inamura et al. proposed an

order-specified multisignature scheme capable of

investigating the order in which the signers sign a

document (Inamura et al, 2011).

2.1 Content Editing Method

Tanaka et al. considered content files of multiple 3D

models as humanoid characters. "Miku Miku Dance"

(Higuchi, 2020) enables the creation of dance videos

through the movement of a humanoid character; in

this tool, the coordinates of the hands and feet of the

3D model are set for each movement. Tanaka et al.

partitioned this 3D model into multiple content files

such that each part of the body, such as the right arm

and the left foot, allows detailed editing management

for each part of the body. Permitted editing methods

include deleting, changing, and adding another

content file. However, the inheritance function that

ensures a secondary user adheres to the editing

adjustment specified by the author is not

implemented.

2.1.1 Entity

Following the scheme developed in the previously

mentioned study, an i-th author was introduced and

the word “editor” was not used. Therefore, the two

entities called the i-th author and verifier are

described as follows:

1. The i-th author

The i-th author is involved in the operations and

can set the content file to edit the control

signature and update the aggregate signature.

The operation of this author can be represented

with the help of a tree structure, such as the one

depicted in Fig. 1. In the scheme proposed by

Tanaka et al., the authors located in the root part

of the tree are called the first author. If the height

of the tree is n-1, then the section of the tree root

is called the n-th author. Therefore, i is defined

as the author's position during the operation. The

i-th author can set an edit control signature on

the developed content file. We can edit if the edit

control signature defined by the i-1st author

permits editing. A11 through A16 in Fig. 1

depicts the principal content developed by at

least two first authors. The second author used

the primary content files of the first author to

develop the secondary contents, A21 and A22.

Finally, the third author developed the final

content A31. Consequently, the second author

edited the content file when the edit control

signature settings set by each first author

permitted editing. The third author adhered to

the edit control signature settings set by the first

and second authors.

Figure 1: Entities in the tree structure of content files.

2. Verifier

The verifier verifies if the content file has a valid

signature. By enabling verification on the device

in which the content is played, a system can be

developed that cannot play the content without a

valid signature.

2.1.2 Edit Control

First, the operation of the creator of the content file is

explained. The creator of the content file can set

whether or not to allow content editing. Editability is

converted into parameters and signed together with

the content file. There are two types of parameters,

"No Derivative" and " ShareAlike". If the creator of

the original content permits editing, the editor that

secondarily uses the content file can change the work.

For example, one can change the color of the work or

move the character's arms and legs to change the

pose. If the " No Derivative " content file is changed,

it is judged to be invalid. Next, " ShareAlike " is

described. Set "ShareAlike " when you want the

editor to comply with the settings set by the creator of

the original content. For content files for which "

ShareAlike " is set, the editor after secondary use

cannot change the editing control set by the creator.

This protects the creator's willingness not to change

the work.

Next, the editor that secondarily uses the content

file is described. The editor verifies the signature of

the original content. If editing is performed without

observing the editing control set by the creator of the

content file, it is judged as invalid. If the creator of

the original content has not set " ShareAlike ", the

editor can set new editing controls.

ICISSP 2021 - 7th International Conference on Information Systems Security and Privacy

486

2.2 Digital Signature Scheme

2.2.1 BLS Aggregate Signature

Tanaka et al. used the aggregated signature by BLS.

Boneh. Lynn and Shacham proposed an aggregate

signature scheme based on the BLS signature scheme

using the operation on an elliptic curve and pairing.

This scheme aggregates at least two signatures for

every message into one signature with a steady length

independent of the number of signers.

denote the set of signer groups and the set of signer

symbols that participate in generating an aggregate

signature, respectively. The construction of the

aggregate signature is as follows.

Key Generation: 𝑔 is a generator of 𝔾



. 𝑥



is a value

of 𝑍



. The key generation center is calculated 𝑣



𝑥



𝑔. Herein, 𝑥



is a private key of 𝑢



∈𝐿, and 𝑣



is a

public key of 𝑢



Signing: Let 𝐻:



0,1



∗

→𝔾



be a one-way hash

function. Let 𝑚



be a signer’ s message 𝑢



. Then, the

signer 𝑢



calculates ℎ



=𝐻𝑚



 and sets 𝜎



=𝑥



ℎ



as the signature corresponding to 𝑚



. After signing,

we retrieve all signatures and calculate an aggregate

signature σ=

∑

𝜎



(

𝑗∈𝐽

)

Verification: The verifier retrieves

𝑚

_

,⋯,𝑚

_

,𝜎,𝑔 and verification keys 𝑣



(

𝑗∈𝐽

)

Thereafter, it calculates ℎ



=𝐻𝑚



 from 𝑚



s and

determines if the following is achieved using pairing.

𝑒

(

𝑔,𝜎

)



𝑒𝑣



,ℎ





(

𝑗

∈

𝐽

)

(1)

If the aggregate signature is accurately developed,

the upper equation is achieved.

2.2.2 ID Based Aggregate Signature

Unlike BLS signatures, which generate keys from

random numbers, ID-based signatures generate keys

from author IDs, which represent the author

information set for each author. This eliminates the

need to issue a public key certificate for signature

verification. It utilizes a pairing function with

bilinearity characteristics on elliptic curves. Next, the

ID-based aggregate signature algorithm is used. The

ID-based aggregated signature can aggregate

multiple generated signatures into one.

Let 𝒰=𝑢

_

,⋯,𝑢

_

 be the set of signers

participating in the aggregate signature. Let ℐ=



𝑖_1,⋯,𝑖_𝑡



be the set of participants' symbols in the

aggregate signature.

Preparation: From the generators 𝑔∈𝔾



and 𝑠 ∈

𝑍



, the secret key issuing center calculates𝑔



=𝑠𝑔,

and 𝑠 is the master secret key.

Key Generation: Let the ID information of the signer

𝑢



be 𝐼𝐷



. The private key issuance center uses the

one-way hash function 𝐻





0,1



∗

→𝔾



calculate𝑄





=𝐻



(𝐼𝐷



). Issue 𝑑





=𝑠𝑄





to the

signer as the private key 𝑢



∈𝒰.

Signing: Let 𝑚



be the plaintext signed by the signer

𝑢



. The signer generates a random number 𝑟



∈𝑍



and

is calculated𝑈



=𝑟



𝑔. Then, ℎ



=𝐻



(𝐼𝐷



,𝑚



,𝑈



) is

calculated using the unidirectional hash function

𝐻





0,1



∗

→𝔾



. Then generate 𝑉



=𝑑





+𝑟



ℎ



. Let

𝜎



=< 𝑈



,𝑉



> be the signature for 𝑚



Aggregation: The signature aggregator collects 𝑉=

∑

𝑉



(

𝑖∈ℐ

)

all the signers 𝑢



(∈ 𝒰) and calculates 𝑉



Let the aggregate signature be 𝜎=<

𝑈

_

,⋯,𝑈

_

,𝑉>.

Verification: The verifier collects

𝑔,𝑔



,𝑈

_

,⋯,𝑈

_

,𝑉,𝑚

_

,⋯,𝑚

_

,𝐼𝐷

_

,⋯,𝐼𝐷

_

and calculates 𝑄





=𝐻



(𝐼𝐷



) and ℎ



𝐻



(𝐼𝐷



,𝑚



,𝑈



) . Determine if 𝑒

(

𝑔,𝑉

)

∏

𝑒(𝑔



,𝑄





)𝑒(𝑈



,ℎ



)

(

𝑖∈ℐ

)

holds.

3 USE OF EXISTING SYSTEM

In this section we explain the existing technology

used in the proposed method. Initially, the "Miku

Miku Dance" is described in Section 3. 1. This

software was used as a content file. The creative

commons license is described in Section 3.2. We

utilize the findings of previous studies on the

secondary use of files under a creative commons

license.

3.1 Miku Miku Dance

"Miku Miku Dance" is a 3D music video production

tool distributed freely by Yu Higuchi. Using this tool,

music videos can be developed by operating the

character "Hatsune Miku." Several videos have been

developed using this tool. I have developed such

dance movies, but only using humanoid characters

such as Hatsune Miku. However, recently, four-

legged animals and other humanoids are also

available. In addition, props, stages, and backgrounds

perfect for music videos have been developed.

Several useful materials for developing these videos

are available for free. The "Miku Miku Dance" is

widely used because music videos can be easily

developed using this tool; furthermore, the tool is

very user friendly, in particular, for beginners. Fig. 2

depicts an operation screen of the “Miku Miku

Dance”.

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487

Figure 2: Operating screen of “Miku Miku Dance”.

The character at the center of the screen was

Hatsune Miku. Here, the 3D model of this character

is used as the content file. However, many 3D models

other than humanoid characters are now emerging. In

a non-human 3D model, it is not necessary to divide

the content file for each part of the human body, as in

the previous research. Therefore, in this study, the 3D

model itself is regarded as a single content file.

3.2 Creative Commons License

The copyright protection system proposed uses a

creative commons license for editing management. A

creative commons license is proposed as a new

the author can express his/her intention to “using the

work freely if certain conditions are met” However,

we cannot protect the operation from malicious

secondary users. Therefore, in this study, electronic

signatures are combined to protect the creative

commons license technically. For example, a

malicious secondary user can modify a task that is not

allowed to be modified. Herein, if a signature is

attached to the task, it is revealed through verification

that editing is not permitted. This protects the rights

of the author. Thereafter, the types of editing

permission are described. The creative commons

license has four types of conditions: Attribution,

Noncommercial, No Derivative, and ShareAlike. By

displaying the icon shown in Fig. 3, authors indicate

their intention on the secondary use of the work. The

conditions are described as follows:

Attribution: This license enables others to adapt

and advance an existing task with relevant

acknowledgement of the original creator.

Noncommercial: A task cannot be used

commercially.

No Derivative: A task cannot be shared with

others in adapted form.

ShareAlike: All new works based on the task will

use the same license.

In this program, you can set No Derivative and

ShareAlike among these licenses.

Figure 3:

Creative Commons License icon.

4 ALGORITHM

We describe the algorithm that generates ID-based

signatures and protects content files using the scheme

proposed by Tanaka et al (Tanaka et al, 2017). We

assume that the binding between the signers and the

verification keys is guaranteed by a certification

authority and that the information prepared does not

come from a third party.

Key Generation: IDij is the author ID defined based

on the location of a task. For example, 𝐼𝐷



denotes

the author of the contents 𝐴



in Fig. 1. The key

generation center calculates the following:

𝑔





=𝑠𝑔

)

from the generator 𝑔∈𝔾



and the master secret key

𝑠. Thereafter, the key generation center calculates the

public key and the secret key of the signer IDij by

𝑄





=𝐻



(𝐼𝐷



)

𝑑



=𝑠𝑄



)

Here, 𝑄



denotes the public key, and 𝑑



denotes

the secret key. The signing keys display differences.

Signing: The author performs the signature

generation process prior to publishing the original

content that has obtained an administration signature.

To prevent duplication, the content ID of each content

is different, and the author is identified from the

content ID (where the first half of ICij is equal to IDij).

1. Setting ID

Author IDij determines the control permissions

of change, deletion, addition, diversion, and

succession for each partial content and the

composition of the content. Author IDij

determines the content ID, where ICij is set to

zero for partial contents that can be diverted.

2. Determining parameters

Author IDij uses the parameters 𝑝



and 𝑝



indicate whether it can be modified and

inherited to generate a hash value and an edit

management signature. The parameters are 𝑝



ICISSP 2021 - 7th International Conference on Information Systems Security and Privacy

488

1 if alterations are allowed and 𝑝



= 0

otherwise. Similarly, the parameter is 𝑝



=1 if

inheritance is set and 𝑝



=0 otherwise.

ℎ



=𝐻𝐼𝐶



∥𝐼



∥𝐻

𝐴



∗

∥𝑝



∥𝑝



∥𝑟



(5)

𝜔



=𝑟



ℎ



+𝑑



,𝑈



=𝑟



𝑔

)

3. Aggregating

The author IDij generates each aggregate

signature ( 𝑈



,𝑈



,⋯,𝑈



,𝑈



) by:

𝜔



= 𝜔



+𝑈



,𝑈



,⋯,𝑈



,𝑈



(7)

When an editor creates a new work using the

author's original content, the editor also

generates a signature. In this manner, as the

number of editors increase, so does the number

of signatures. One disadvantage is that the

amount of signature data is large. Therefore,

signatures are aggregated to reduce this.

4. Linking content

Attach the edit management signature if editing

is enabled, and attach the hash value if editing is

not permitted. Furthermore, attach 𝑈



, bID =

aID. The aggregate signature is attached to the

T.B content.

Verification: The verification of the content file is

performed by the playback device before viewing the

content. It is also executed in secondary use. The

individual that verifies the signature of the content is

called the verifier. If viewing content, the verifier is

the viewer. The verifier performs the following

processes: Generates the hash value of each partial

content for each edit. Prepares the key of the authors

and verifies the following equations: The content is

accepted as valid if the results of the examinations are

accurate.

The verifier examines whether the content is in

succession. Then generates the hash value using the

parameters and is examined as follows:

𝑒𝑔,𝜔





=𝑒𝑈



,ℎ



𝑒𝑔



,𝑄





)

If the above validation is successful, the verifier

can view or use the content as legitimate content.

Content files that fail to be verified cannot be used

because they have been illegally edited. This is

consistent with the will of the author.

5 PERFORMANCE

EVALUATION

A computer simulation was performed using the

Oracle VM Virtual Box. The Oracle Virtual Box

develops a virtual machine in the main computer.

Ubuntu software was installed on a virtual computer

and the program was executed. Table 1 presents the

details of the simulation environment.

The simulation compiled a program generated in

C++ using gcc (version 5.4.0) and ran it on the ubuntu

terminal. Furthermore, a library called mcl (Herumi,

2020) was introduced to perform finite field

operations, elliptic curve calculations, and pairing

calculations required for signatures.

5.1 Simulation Environment

A computer simulation was performed using the

Oracle VM Virtual Box. The Oracle Virtual Box

develops a virtual machine in the main computer.

Ubuntu software was installed on a virtual computer

and the program was executed. Table 1 presents the

details of the simulation environment.

Table 1: Simulation environment.

Main machine Simulation Environment

OS Windows10Pro

CPU Intel® Core™

i7-6500U CPU 2.50GHz

RAM 8GB

Virtual machine Simulation Environment

OS Ubuntu6.01

CPU Allocate 1 core from the

main CPU

RAM 4GB

The simulation compiled a program generated in

C++ using gcc (version 5.4.0) and ran it on the ubuntu

terminal. Furthermore, a library called mcl was

introduced to perform finite field operations, elliptic

curve calculations, and pairing calculations required

for signatures.

5.1.1 mcl

mcl is a pairing-based cryptographic library provided

by Shigeo Mitunari. Using this library, optimal

pairing can be performed on two types of curves: the

BN curve and the BLS12-381 curve. mcl is a library

that can operate not only on Windows and Linux but

also on IOS and Android environments. We used this

library on the ubuntu terminal to create and verify

signatures.

Implementation of Secondary Available Digital Content Protection Schemes using Identity-based Signatures

489

A feature of the mcl library is that it is faster than

the conventional elliptical curve and the pairing

arithmetic libraries. For example, 3.9 ms were

required by the mcl library to execute on an elliptic

curve on arm64. University of Tsukuba Elliptic Curve

and Pairing Library (TEPLA), which is another

library, required 17.9 ms to calculate another elliptic

curve in the same environment (Laboratory of

Cryptography and Information Security, 2020).

Therefore, mcl has faster processing capabilities than

elliptic curve calculation libraries such as RELIC

PRIME=254 and MIRACL ake12bnx. We ran the

program after compiling it and measured the time

required for signature and verification.

5.1.2 TEPLA

TEPLA is a library that can implement a

cryptographic protocol using pairing in the C

language. This library is provided by the Laboratory

of Cryptography and Information Security University

of Tsukuba and can be used in operating systems such

as Windows, Mac OS, and Linux. TEPLA supports

calculations on finite fields, elliptic curves, and

pairing. TEPLA version 2.0 was released on

December 20, 2015.

5.2 Outline of Simulation

In this simulation, the 3D model of Miku Miku Dance

was used as the content file. This content file is

created by the creator (the first user) and signed. Next,

there is an editor who secondarily uses this content

file. The creator sets the edit control as a parameter.

Make sure these settings are followed during

secondary use. In addition, suppose some content has

been changed even though "Edit prohibited" is set. If

it is contrary to the intention of the author, check

whether it can be detected as malicious content.

To evaluate the performance of the proposed

algorithm, the time required for signature processing

was compared to the processing time required by

TEPLA. We also measured the processing time

required to verify the signature. Table 3 presents the

details of the simulation environment using the

TEPLA library for comparison. As shown, there is a

single 3D model of Miku Miku dance that must be

signed, and the signature is generated after the

parameters are created by the author.

Figure 4 shows the operation of the user and the

operation of the program when signing the content

file. User operations are shown in yellow, and

program operations are shown in green.

Table 2: Environment TEPLA Ver.2.0.

Main machine Simulation Environment

OS Windows10 Home 64bit

CPU Intel® Core™

i7-9700U CPU

RAM 16GB

Virtual machine Simulation Environment

OS Ubuntu6.01

CPU Allocate 1 core from the

main CPU

RAM 4GB

Figure 4: Signature

generation flowchart.

5.3 Simulation Result

5.3.1 Generating Signature

The time required to generate a signature for one 3D

model was measured using the mcl library. Table 3

presents the time required to generate the signature

using TEPLA. The display time is the average of 5

trials (Fujisaki et al, 2018).

Table 3: Time to generate signature.

Librar

Time[s]

mcl 0.1163

TEPLA 0.2153

Based on the measurement, it can be observed that

the signature generation time is shorter when mcl is

used compared to TEPLA. Therefore, the proposed

algorithm was confirmed to be adequately compatible

for practical use owing to its high speed.

5.3.2 Verification

The time required for signature verification was

measured using the mcl library.

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Table 4: Time to verify signature.

Librar

Time[s]

mcl 0.2972

The processing speed required for signature

verification is also practical.

6 CONCLUSIONS

A program was implemented to protect the “Miku

Miku Dance” content files using ID-based signatures

via the mcl library. This algorithm permits secondary

use but does not prevent the distribution of the

original contents on UGC. Editing can also be

completed by secondary users based on inheritance.

This ensures that copyright protection is compatible

with UGC growth. In addition, the processing speed

increases using the mcl library. Furthermore, the

developed program can be run on a Linux terminal

that, however, hinders observations.

In the future , we plan to incorporate a more user-

friendly interface for ease of use.

REFERENCES

Inamura, M., Iwamura, K., Watanabe, R., Nishikawa, M.,

and, Tanaka, T., 2011. a new tree-structure-specified

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Tanaka, D., Iwamura, K., Inamura, M., and Kaneda, K.,

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Digital Signature, 14

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Fujisaki, M., Iwamura K., Inamura, M., and Kaneda, K.,

2018. Improvement and Implementation of digital

content protection scheme using identity based

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Lin, C. Y., Wu, T. C., and Zhang, F., 2003. A structured

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“Youtube” https://www.youtube.com/

(reading:2020-09-11)

“Niko Niko Douga” www.nicovideo.jp/

(reading:2020-09-11)

“Creative Commons License”

https://creativecommons.org/ (reading:2020-09-16)

Higuchi, Y., ”VPVP” https://sites.google.com/view/vpvp/

(reading:2020-09-11)

Laboratory of Cryptography and Information Security,

University of Tsukuba, "TEPLA"

http://www.cipher.risk.tsukuba.ac.jp/tepla/index.html

(reading:2020-09-11)

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Implementation of Secondary Available Digital Content Protection Schemes using Identity-based Signatures

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