Anti-collusion Code Research Articles

Fingerprint-related chaotic image encryption scheme based on blockchain framework

Chaotic image encryption has been greatly investigated in recent years. However, a considerable number of the encryption schemes had been cracked by chosen plaintext attack (CPA). Although the new proposed plaintext-related chaotic image encryption schemes can resist CPA effectively, the emerged key management problem is a hot potato. In this paper, a novel fingerprint-related chaotic image encryption scheme is proposed. The generation of key streams is affected by the fingerprints of distributors rather than the plaintexts of images. In addition, the blockchain framework is adopted to ensure that the encrypted image was sent correctly form the distributor. Moreover, the distributors’ fingerprints embedded in the encrypted images are encoded by the anti-collusion code in order to record multiple fingerprints with fixed length of data. The proposed method has the following superiorities: 1) Security. CPA is invalid because the attacker does not have the fingerprint of the legal receiver. Meanwhile, no key management problem is caused. 2) Authenticity. The image, the sender and the receiver are all verified by using blockchain framework. 3) Traceability. All distributors’ fingerprints can be extracted correctly from the merged fingerprint based on the anti-collusion code, and the transmission of the image can be traced.

Collusion Attack Resilient 3D Mesh Watermarking Based on Anti-Collusion Fingerprint Code

Collusion attack is one of the techniques used for unauthorized removal of embedded marks. However, there are no algorithms that utilize the averaging-resilient fingerprint code into 3D mesh watermarking. In this paper, we propose a collusion resilient 3D mesh watermark based on mesh spectral analysis and the anti-collusion fingerprint code. We present two fingerprint schemes by exploiting the theoretically proven anti-collusion codes: the group-divisible partially balanced incomplete block design, and Tardos’s fingerprint code. The proposed extraction scheme not only met the requirement for an anti-collusion code but also provided sufficient length of the payload for the fingerprint code. To minimize the detection error, we also modeled the response of the detector and herein present optimized thresholds for our method. Based on the experiments with public benchmarks, the proposed method outperformed conventional robust mesh watermarking against collusion attack, and provided robustness to the combination of a small amount of added noise and collusion attack.

On Anti-Collusion Codes and Detection Algorithms for Multimedia Fingerprinting

Multimedia fingerprinting is an effective technique to trace the sources of pirate copies of copyrighted multimedia information. AND anti-collusion codes can be used to construct fingerprints resistant to collusion attacks on multimedia contents. In this paper, we first investigate AND anti-collusion codes and related detection algorithms from a combinatorial viewpoint, and then introduce a new concept of logical anti-collusion code to improve the traceability of multimedia fingerprinting. It reveals that frameproof codes have traceability for multimedia contents. Relationships among anti-collusion codes and other structures related to fingerprinting are discussed, and constructions for both AND anti-collusion codes and logical anti-collusion codes are provided.

A simple fingerprinting scheme for large user groups

Digital fingerprinting is an emerging technology to protect multimedia data from piracy, where each distributed copy is labeled with unique identification information. In coded fingerprinting, each codeword of the anti-collusion code is used to represent a user's fingerprint. In real-world applications, the number of potential users can be very large and hence, the used anticollusion code should be easy to construct and have as many codewords as possible. This paper proposes a simple coded fingerprinting scheme, where the anticollusion code is constructed with an identity matrix. The main advantage of our scheme is its simplicity, as a large number of fingerprints can easily be generated to accommodate a large number of users. To improve collusion resistance, some transformations are performed on the original fingerprint in the embedding phase and the corresponding inverse transformations are performed on the extracted sequence in the detection phase.

Fingerprinting Codes for Internet-Based Live Pay-TV System Using Balanced Incomplete Block Designs

In recent years, with the rapid growth of the Internet as well as the increasing demand for broadband services, live pay-television broadcasting via the Internet has become a promising business. To get this implemented, it is necessary to protect distributed contents from illegal copying and redistributing after they are accessed. Fingerprinting system is a useful tool for it. This paper shows that the anti-collusion code has advantages over other existing fingerprinting codes in terms of efficiency and effectivity for live pay-television broadcasting. Next, this paper presents how to achieve efficient and effective anti-collusion codes based on unital and affine plane, which are two known examples of balanced incomplete block design (BIBD). Meanwhile, performance evaluations of anti-collusion codes generated from unital and affine plane are conducted. Their practical explicit constructions are given last.

선형결합 공모공격에 강인한 각도해석 기반의 대용량 핑거프린팅

Fingerprinting scheme uses digital watermarks to trace originator of unauthorized or pirated copies, however, multiple users may collude and escape identification by creating an average or median of their individually watermarked copies. Previous research works are based on ACC (anti-collusion code) for identifying each user, however, ACC are shown to be resilient to average and median attacks, but not to LCCA and cannot support large number of users. In this paper, we propose a practical SACC (scalable anti-collusion code) scheme and its angular decoding strategy to support a large number of users from basic ACC (anti-collusion code) with LCCA (linear combination collusion attack) robustness. To make a scalable ACC, we designed a scalable extension of ACC codebook using a Gaussian distributed random variable, and embedded the resulting fingerprint using human visual system based watermarking scheme. We experimented with standard test images for colluder identification performance, and our scheme shows good performance over average and median attacks. Our angular decoding strategy shows performance gain over previous decoding scheme on LCCA colluder set identification among large population.

Design and Analysis of High-Capacity Anti-Collusion Hiding Codes

A new methodology for the design of high-capacity anti-collusion hiding codes in a large-scale fingerprint-based traitor tracing system is proposed in this work. We consider a hiding code of MN bits, where M bits are used as the user ID and N bits are the length of the spreading codes. Since each user is assigned one out of 2 M ID numbers and one out of N spreading codewords, the total number of users is equal to 2 M N. To accommodate an even larger number of users, we propose a shifted spreading scheme that shifts the spreading codeword circularly by a certain amount. By allowing P shifts (with P mod N), the total number of users increases from 2 M N to 2 M NP. When multiple users perform a weighted collusion attack, we show that the task of identifying colluders and their attack weights can be formulated as a user detection and channel estimation problem in a multiuser wireless communication system with a multipath fading channel. For the latter, there exist code design techniques that choose the spreading codes carefully so as to reduce multiaccess interference of users with different spreading codewords effectively. By exploiting this analogy, we develop an anti-collusion code called OSIFT (Orthogonal Spreading followed by the Inverse Fourier Transform). We compare several hiding codes in a fingerprinting system consisting of hundreds of colluders. It is demonstrated by computer simulation that, when the OSIFT code is adopted, colluders and their attack weights can be found by the proposed fingerprinting system more accurately.

제로기반 코드 변조 기법을 통한 비디오 핑거프린팅 시스템

Digital fingerprinting is a contents-protection technique, where customer information is inserted into digital contents. Fingerprinted contents undergo various attacks. Especially, attackers can remove easily the inserted fingerprint by collusion attacks, because digital fingerprinting inserts slightly different codes according to the customers. Among collusion attacks, averaging attack is a simple, fast, and efficient attack. In this paper, we propose a video fingerprinting system that is robust to the averaging attack. In order to achieve code efficiency and robustness against the averaging attack, we adopt anti-collusion code (fingerprint code) from GD-PBIBD theory. When the number of users is increased, the size of fingerprint code also grows. Thus, this paper addresses a zero-based code modulation technique to embed and detect this fingerprint code efficiently. We implemented a blind video fingerprinting system based on our proposed technique and performed experiments on various colluding cases. Based on the results, we could detect most of colluders. In the worst case, our scheme could trace at least one colluder successfully.