Software Piracy Root Detection Framework Using SVM Based On Watermarking

Software root piracy detection is tool to use for detect the owner of java software project or unauthorized copy of jar file. Existing system content the licensing mechanism for protecting our software from piracy but by skipping license or cracking that key piracy is done. The proposed system java based piracy detection software tool to overcome from this problem of piracy and find the offender. Proposed system use ‘Watermarking’ is a technique which attempts to protect the software by adding copyright notices or unique identifiers into software to prove ownership. We evaluate the existing Java watermarking systems and algorithms by using them to watermark byte code files. We develop the piracy root detection mechanism in this system. The advantage of this technique is that software watermarking is handled as the knowledge embedded into support vector machine and is closely associated with the program logic. It makes watermark more impossible to be destroyed and removed. We have to apply the watermarking content to the jar files of java software in this system the invisible watermarking is use. The results of the experiment further indicate that the proposed technique is a lightweight and effective software watermarking scheme

Graph Spectral Domain Watermarking for Unstructured Data from Sensor Networks

The modern applications like social networks and sensors networks are increasingly used in the recent years. These applications can be represented as a weighted graph using irregular structure. Unfortunately, we cannot apply the techniques of the traditional signal processing on those graphs. In this paper, graph spread spectrum watermarking is proposed for networked sensor data authentication. Firstly, the graph spectrum is computed based on the eigenvector decomposition of the graph Laplacian. Then, graph Fourier coefficients are obtained by projecting the graph signals onto the basis functions which are the eigenvectors of the graph Laplacian. Finally, the watermark bits are embedded in the graph spectral coefficients using a watermark strength parameter varied according to the eigenvector number. We have considered two scenarios: blind and non-blind watermarking. The experimental results show that the proposed methods are robust, high capacity and result in low distortion in data. The proposed algorithms are robust to many types of attacks: noise, data modification, data deletion, rounding and down-sampling

Graph spectral domain blind watermarking

This paper proposes the first ever graph spectral domain blind watermarking algorithm. We explore the recently developed graph signal processing for spread-spectrum watermarking to authenticate the data recorded on non-Cartesian grids, such as sensor data, 3D point clouds, Lidar scans and mesh data. The choice of coefficients for embedding the watermark is driven by the model for minimisation embedding distortion and the robustness model. The distortion minimisation model is proposed to reduce the watermarking distortion by establishing the relationship between the error distortion using mean square error and the selected Graph Fourier coefficients to embed the watermark. The robustness model is proposed to improve the watermarking robustness against the attacks by establishing the relationship between the watermark extraction and the effect of the attacks, namely, additive noise and nodes data deletion. The proposed models were verified by the experimental results

Publicly Detectable Watermarking for Intellectual Property Authentication in VLSI Design

Highlighted with the newly released intellectual property (IP) protection white paper by VSI Alliance, the protection of virtual components or IPs in very large scale integration (VLSI) design has received a great deal of attention recently. Digital signature/watermark is one of the most promising solutions among the known protection mechanisms. It provides desirable proof of authorship without rendering the IP useless. However, it makes the watermark detection, which is as important as watermarking, an NP-hard problem. In fact, the tradeoff between hard-to-attack and easy-to-detect and the lack of efficient detection schemes are the major obstacles for digital signatures to thrive. In this paper, the authors propose a new watermarking method which allows the watermark to be publicly detected without losing its strength and security. The basic idea is to create a cryptographically strong pseudo-random watermark, embed it into the original problem as a special (which the authors call mutual exclusive) constraint, and make it public. The authors combine data integrity technique and the unique characteristics in the design of VLSI IPs such that adversaries will not gain any advantage from the public watermarking for forgery. This new technique is compatible with the existing constraint-based watermarking/fingerprinting techniques. The resulting public–private watermark maintains the strength of a watermark and provides easy detectability with little design overhead. The authors build the mathematical framework for this approach based on the concept of mutual exclusive constraints. They use popular VLSI CAD problems, namely technology mapping, partitioning, graph coloring, FPGA design, and Boolean satisfiability, to demonstrate the public watermark’s easy detectability, high credibility, low design overhead, and robustness

Effective Iterative Techniques for Fingerprinting Design IP

Fingerprinting is an approach that assigns a unique and invisible ID to each sold instance of the intellectual property (IP). One of the key advantages fingerprinting-based intellectual property protection (IPP) has over watermarking-based IPP is the enabling of tracing stolen hardware or software. Fingerprinting schemes have been widely and effectively used to achieve this goal; however, their application domain has been restricted only to static artifacts, such as image and audio, where distinct copies can be obtained easily. In this paper, we propose the first generic fingerprinting technique that can be applied to an arbitrary synthesis (optimization or decision) or compilation problem and, therefore to hardware and software IPs. The key problem with design IP fingerprinting is that there is a need to generate a large number of structurally unique but functionally and timing identical designs. To reduce the cost of generating such distinct copies, we apply iterative optimization in an incremental fashion to solve a fingerprinted instance. Therefore, we leverage on the optimization effort already spent in obtaining previous solutions, yet we generate a uniquely fingerprinted new solution. This generic approach is the basis for developing specific fingerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell placement. We demonstrate the effectiveness of the new fingerprinting-based IPP techniques on a number of standard benchmarks

FSM BASED DIGITAL WATERMARKING IN IP SECURITY

IP providers are in pressing need of a convenient means to track the illegal redistribution of the sold IPs. An active approach to protect a VLSI design against IP infringement is by embedding a signature that can only be uniquely generated by the IP author into the design during the process of its creation. a VLSI IP is developed in several levels of design abstraction with the help of many sophisticated electronic design automation tools. Each level of design abstraction involves solving some NP-complete optimization problems to satisfy a set of design constraints. In this paper, a new dynamic watermarking scheme is proposed. The watermark is embedded in the state transitions of FSM at the behavioral level