Invisible Watermarking for Audio Generation Diffusion Models

Diffusion models have gained prominence in the image domain for their capabilities in data generation and transformation, achieving state-of-the-art performance in various tasks in both image and audio domains. In the rapidly evolving field of audio-based machine learning, safeguarding model integrity and establishing data copyright are of paramount importance. This paper presents the first watermarking technique applied to audio diffusion models trained on mel-spectrograms. This offers a novel approach to the aforementioned challenges. Our model excels not only in benign audio generation, but also incorporates an invisible watermarking trigger mechanism for model verification. This watermark trigger serves as a protective layer, enabling the identification of model ownership and ensuring its integrity. Through extensive experiments, we demonstrate that invisible watermark triggers can effectively protect against unauthorized modifications while maintaining high utility in benign audio generation tasks.Comment: This is an invited paper for IEEE TPS, part of the IEEE CIC/CogMI/TPS 2023 conferenc

Design and implementation of a high-performance continuous media-on-demand server

High performance servers and high speed networks will form the backbone of the infrastructure required for distributed multimedia information systems. A server for an interactive distributed multimedia system may require thousands of gigabytes of storage space and high I/O bandwidth. Continuous media data, such as video or audio data, typically have large file size and need deadline-driven data delivery. This dissertation presents a high-performance solution to the I/O retrieval problem in a server for a distributed multimedia system. An architectural model of a server for such a system is developed. Parallelism of data retrieval is achieved by striping the data across multiple disks. The admission control policy for accepting a new request at steady state is presented. The performance of any server ultimately depends on the data access patterns. Modifications of the basic retrieval algorithm that exploit data access patterns in order to improve system throughput are presented. The results of a detailed, component-wise instrumentation of an implementation of the server model are presented. In order to maximize system utilization, and thus minimize cost, it is essential that the load be balanced among each of the server\u27s components viz. the disks, the interconnection network and the scheduler. We develop dynamic allocation policies for improving server capacity. These policies assign media requests to the nodes of the server so as to balance the load on the interconnection network and the scheduling nodes. Five policies for request assignment, Round Robin (RR), Minimum Link Allocation (MLA), Minimum Contention Allocation (MCA), Weighted Minimum Link Allocation (WMLA) and Weighted Minimum Contention Allocation (WMCA) are developed. We also address the issues of file replication for achieving load balancing among the disks in the storage subsystem, and the effect of varying the concurrency of data retrieval from the storage subsystem. The performance of the dynamic allocation policies on an implementation of the server model is evaluated. The experimental results demonstrate the differences in the performance of the dynamic allocation policies with respect to the important metric of server stream capacity. The WMLA and WMCA policies significantly improve the stream capacity over that due to the other policies

Techniques for increasing the stream capacity of a multimedia server

A server for an interactive distributed multimedia system may require thousands of gigabytes of storage space and high I/O bandwidth. In order to maximize system utilization, and thus minimize cost, the load must be balanced among the server’s disks, interconnection network and scheduler. Many algorithms for mnvim;hnn “Y”LY”YY”Y,“y ~ot~;~~,nl,I,*, YYYW ” ““y”cYYy rnmnr;fw J’“,, ” f-nm fho Y,YC uY”,“y ” ctnvwno U,y”Y~,,” cwrfom have been proposed. This paper presents techniques for improving server capacity by assigning media requests to the nodes of a server so as to balance the load on the interconnection network and the scheduling nodes. Five policies for request assignment are developed. The T‘.J”. nPrfnrmnnrP..“_.“V1 nf 1J t.h.ese I,“““-“-nnliriP.G 0 % g serl_re?- p-Q&l &y/oped earlier is presented. 1

Design and evaluation of data storage and retrieval strategies in a distributed memory continuous media server

High performance servers and high-speed networks will form the backbone of the infra-structure required for distributed multimedia information systems. Given that the goal of such a server is to support hundreds of interactive data streams simultaneously, various tradeoffs are possible with respect to the storage of data on secondary memory, and its retrieval therefrom. In this paper we identify and evaluate these tradeoffs. We evaluate the effect of varying the stripe factor and also the performance of batched retrieval of disk–resident data. We develop a methodology to predict the stream capacity of such a server. The evaluation is done for both uniform and skewed access patterns. Experimental results on the Intel Paragon computer are presented.

Design Issues in High Performance Media-on-Demand Servers

This paper addresses applications of only the former type. Interactive services present the consumer with tremendous flexibility. The main reasons in support of interactive services such as entertainment-on-demand are

Design and Evaluation of Data Storage and Retrieval Strategies in a Distributed Memory Continuous Media Server

High performance servers and high-speed networks will form the backbone of the infra-structure required for distributed multimedia information systems. Given that the goal of such a server is to support hundreds of interactive data streams simultaneously, various tradeoffs are possible with respect to the storage of data on secondary memory, and its retrieval therefrom. In this paper we identify and evaluate these tradeoffs. We evaluate the effect of varying the stripe factor and also the performance of batched retrieval of disk--resident data. We develop a methodology to predict the stream capacity of such a server. The evaluation is done for both uniform and skewed access patterns. Experimental results on the Intel Paragon computer are presented. 1 Introduction Digitalization of traditionally analog data such as video and audio, and the feasibility of obtaining networking bandwidths above the gigabit-per-second range are two key advances that have made possible the realization, in ..

I/O Scheduling Tradeoffs in a High Performance Media-on-Demand Server

One of the key components of a multi-user multimedia-on-demand system is the data server. Digitalization of traditionally analog data such as video and audio, and the feasibility of obtaining network bandwidths above the gigabit-per-second range are two important advances that have made possible the realization, in the near future, of interactive distributed multimedia systems. Secondary-to-main memory I/O technology has not kept pace with advances in networking, main memory and CPU processing power. Consequently, the performance of the server has a direct bearing on the overall performance of such a system. We have developed a high-performance solution to the I/O retrieval Parallelism of data retrieval in our architectural model of the server is achieved by striping the data across multiple disks. We identify the design parameters that affect the throughput of the server. In this paper we evaluate how the parameters identified affect the data retrieval efficiency of the server. The re..

CacheCOW: QoS for Storage System Caches

Managed hosting and enterprise wide resource consolidation trends are increasingly leading to sharing of storage resources across multiple classes, corresponding to different applications/customers, each with a different Quality of Service (QoS) requirement. To enable a storage system to meet diverse QoS requirements, we present two algorithms for dynamically allocating cache space among multiple _classes of workloads. Our algorithms dynamically adapt the cache space allocated to each class depending upon the observed response time, the temporal locality of reference, and the arrival pattern for each class. Using trace driven simulations collected from large storage system installations, we experimentally demonstrate the following properties of CacheCOW