nils-herrmann/clean_scirepeval huggingface dataset:
Selfish Colluder Detection and Identification in Traitors within Traitors

During collusion attacks against multimedia forensics, an important issue that colluders need to address is the fairness of the attack, i.e., whether all colluders take the same risk of being detected. Although they might agree so, some selfish colluders may break away from their fair-collusion agreement and process their fingerprinted copies before collusion to further lower their risk. On the other hand, to protect their own interests, other attackers may wish to detect and prevent such selfish pre-collusion processing. It is important to study this problem of traitors within traitors, formulate the dynamics among colluders and build a complete model of multi-user collusion. This paper investigates techniques that attackers can use to detect and identify selfish colluders without revealing the secrecy of any fingerprinted copies. Our simulation results show that the proposed scheme accurately identifies all selfish colluders without falsely accusing any others.
Data-Driven Stochastic Models and Policies for Energy Harvesting Sensor Communications

Energy harvesting from the surroundings is a promising solution to perpetually power-up wireless sensor communications. This paper presents a data-driven approach of finding optimal transmission policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission parameters, power levels and modulation types, to the changes of channel fading and battery recharge. We formulate this problem as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. With the observed solar irradiance at each time epoch, a mixed strategy is developed to compute the belief information of the underlying solar states for the choice of transmission parameters. In addition, a theoretical analysis is conducted for a simple on-off policy, in which a predetermined transmission parameter is utilized whenever a sensor node is active. We prove that such an optimal policy has a threshold structure with respect to battery states and evaluate the performance of an energy harvesting node by analyzing the expected net bit rate. The design framework is exemplified with real solar data records, and the results are useful in characterizing the interplay that occurs between energy harvesting and expenditure under various system configurations. Computer simulations show that the proposed policies significantly outperform other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.
Obtaining full-diversity space-frequency codes from space-time codes via mapping

This paper considers the problem of space-frequency code design for frequency-selective multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) modulation. We show that space-time codes achieving full diversity in quasistatic flat fading environment can be used to construct space-frequency codes that can achieve the maximum diversity available in frequency-selective MIMO fading channels. Since the codes are constructed via a simple mapping from space-time codes to space-frequency codes, the abundant classes of existing space-time block and trellis codes can be used for full diversity transmission in MIMO-OFDM systems. The proposed mapping provides a tradeoff between the achieved diversity order and the symbol rate. Moreover, we characterize the performance of the space-frequency codes obtained via the mapping by finding lower and upper bounds on their coding advantages as functions of the coding advantages of the underlying space-time codes. This result will allow us to investigate the effects of the delay distribution and the power distribution of the channel impulse responses on the performance of the resulting space-frequency codes. Extensive simulation results are also presented to illustrate and support the theory.
A Broad Beamforming Approach for High-Mobility Communications

To leverage the benefits of multiple-input multiple-output in high-mobility communications, this paper proposes a broad beamforming approach (BBA), which focuses a broad beam on a moving user on the basis of the moving user's current location and velocity information. So, the moving user can be covered and tracked by the broad beam and is able to achieve high received signal-to-noise ratio (SNR). An optimization problem is formulated to minimize the required power by jointly optimizing the transmit and the receiving beam vectors, while guaranteeing the desired information rate of the moving user. Since the problem is with infinite constraints and has no known solution, we design an efficient algorithm to solve it, where the transmit and receiving beam vectors are optimized by using semidefinite relaxation alternatively in an iterative manner. Simulation results show that by using our proposed BBA, the desired information rate of the high-mobility user can be guaranteed. Compared with existing schemes, with the same power consumption, our proposed scheme can enhance the SNR greatly within the moving region of interest. Besides, by increasing the number of transmit antennas, the required power can be further decreased.
Forensic identification of compressively sensed signals

Identifying a signal's origin and how it was acquired is an important problem for digital forensics. Recently, compressive sensing has achieved substantial attention due to its ability to accurately acquire sparse signals at rates below the Nyquist rate. The increased popularity of this signal acquisition technique gives rise to a new forensic problem: is it possible to distinguish signals that have been compressively sensed from traditionally sampled ones? In our previous work, we addressed this problem of differentiating between traditionally acquired and compressively sensed images. In this paper, we examine the problem of distinguishing traditionally sampled signals from compressively sensed ones for a broader class of signals. We categorize those compressive sensing applicable signals into two cases: sparse signals with noise and nearly sparse signals. For each category, we discuss the traces left in a signal by compressive sensing and propose a corresponding detection scheme. Experimental results show that both of our proposed detection schemes can be effectively used to distinguish compressively sensed signals from traditionally sensed signals.
Defense against injecting traffic attacks in cooperative ad hoc networks

In this paper we investigate how to defend against injecting traffic attacks in cooperative ad hoc networks. By injecting an overwhelming amount of packets into the network, the attackers can easily consume valuable network resources and reduce nodes' lifetime. Since in cooperative ad hoc networks nodes will usually unconditionally forward packets for other nodes, such networks are extremely vulnerable to injecting traffic attacks, especially those launched by inside attackers. In this paper, the possible types of injecting traffic attackers are studied, and a set of mechanisms are proposed to protect cooperative ad hoc network against such attacks. The performance of the proposed mechanisms is analyzed, which show that from attackers' point of view, the best strategy is not to launch injecting traffic attacks. Simulation studies also confirm the theoretical analysis.
Multi-node cooperative resource allocation to improve coverage area in wireless networks

It is of great importance for service providers to improve the coverage area without cost of more infrastructure in wireless networks especially in rural areas. Recently, cooperative communication has brought a new communication paradigm. In this paper, multi-node cooperative resource allocation is studied to schedule the transmission time slots so as to maximize the network overall rate (or the coverage area) under the quality of services constraints. To optimize the performance, first, the performance of the multi-node cooperative transmission is analyzed. Then a protocol is constructed between the mobiles and the base station for the resource allocation. From the simulation results, the proposed scheme can increase the user's rate by 5% for large cell sizes and improve the coverage by 180%, compared with the traditional scheme without cooperative transmission
Multi-layer key management for secure multimedia multicast communications

An important application of multicasting is group-oriented multimedia communication, such as video-on-demand and video conferencing. Before these services can be successfully deployed, security infrastructures must be developed to ensure access control to multicast content. In this paper, we present a multi-group key management scheme tailored to multimedia multicast services that distribute data in multi-layer or multi-object format. Compared with the existing tree-based key management schemes that are used for generic data multicasting services, the proposed scheme can reduce the communication overhead by a factor of (M + 1)/2 and M is the number of layers. For example, when the multimedia data is encoded into three layers according to different quality requirements, the proposed scheme reduces the communication overhead associated with key updating by 50%.
Morphological filtering and stochastic modeling-based segmentation of masses on mammographic images

The objective of this study is to develop an efficient method to highlight the geometric characteristics of mass patterns, and isolate the suspicious regions which in turn provide the improved segmentation of suspected masses. In this work, a combined method of using morphological operations, finite generalized Gaussian mixture modeling, and contextual Bayesian relaxation labeling was developed to enhance and segment various mammographic contexts and textures. This method was applied to segment suspicious masses on mammographic images. The testing results showed that the proposed method can detect all suspected masses as well as high contrast objects and can be used as an effective pre-processing step of mass detection in computer-aided diagnosis systems.
Algorithm-based low-power/high-speed Reed-Solomon decoder design

With the spread of Reed-Solomon (RS) codes to portable wireless applications, low-power RS decoder design has become important. This paper discusses how the Berlekamp Massey decoding algorithm can be modified and mapped to obtain a low-power architecture. In addition, architecture level modifications that speed-up the syndrome and error computations are proposed. Then the VLSI architecture and design of the proposed low power/high-speed decoder is presented. The proposed design is compared with a normal design that does not use these algorithm/architecture modifications. The power reduction when compared to the normal design is estimated. The results indicate a power reduction of about 40% or a speed-up of 1.34.
Interpolation-free subpixel motion estimation techniques in DCT domain

Currently existing subpixel motion estimation algorithms require interpolation of interpixel values which undesirably increases the overall complexity and data flow and deteriorates the estimation accuracy. We develop discrete cosine transform (DCT)-based techniques to estimate subpel motion at different desired subpel levels of accuracy in the DCT domain without interpolation. We show that subpixel motion information is preserved in the DCT of a shifted signal under some condition in the form of pseudophases, and we establish subpel sinusoidal orthogonal principles to extract this information. The proposed subpixel techniques are flexible and scalable in terms of estimation accuracy with very low computational complexity O(N/sup 2/) compared to O(N/sup 4/) for the full-search block-matching approach and its subpixel versions. Above all, motion estimation in the DCT domain instead of the spatial domain simplifies the conventional hybrid DCT-based video coder, especially the heavily loaded feedback loop in the conventional design, resulting in a fully DCT-based high-throughput video codec. In addition, the computation of pseudophases is local, and thus a highly parallel architecture is feasible for the DCT-based algorithms. Finally, simulation on video sequences of different characteristics shows comparable performance of the proposed algorithms to block-matching approaches.
Optimal Pricing for Mobile Video Streaming Using Behavior Analysis

Mobile phones are among the most popular consumer devices and the recent developments of 3G networks and smart phones enable users to watch video programs by subscribing data plans from service providers. Due to the ubiquity of mobile phones and phone-to-phone communication technologies, subscribers can redistribute the video content to non-subscribers. Such a redistribution mechanism is a potential competitor for the service provider and is very difficult to trace given the users'' high mobility. The service provider has to set a reasonable price for the data plan to prevent such re-distribution behavior to protect his/her own profit. In this paper, we analyze the optimal price setting for the service provider by investigating the equilibrium between the subscribers and the secondary buyers in the content-redistribution network. We model the behavior between the subscribers and the secondary buyers as a hybrid Stackelburg auction game and find the optimal price and quantity for both groups of users. Such an analysis can help the service provider preserve their profit under the threat of the redistribution networks and can improve the quality of service for end users.
Joint source-channel multistream coding and optical network adapter design for video over IP

We present a panorama picture on how to achieve end-to-end video over IP service under the communication environments, consisting of backbone networks, hybrid access networks, and the end users. The paper consists of three equally weighted subtopics which cover some novel thoughts in designing and implementing the video over IP system in the different areas, namely, a Synchronous Optical NETwork (SONET) network adapter for backbone connections, the joint source-channel multistream coding in hybrid access networks, and the content-based source coding in the transform domain. We propose to link the three different problems associated with the hybrid networks, which have different characteristics and design requirements, to improve the critical performances in various areas of video over IP systems. The goal is to deliver video over IP networks in more cost-effective and reliable manner. IP/ATM over SONET is currently a commonly used backbone technique. In the first part of this paper, we present a flexible design and implementation of a SONET network adapter to carry IP traffic via optical fiber. Unlike many conventional designs, our single-chip implementation supports different data rates (OC-3, OC-12, and OC-48), carries IP traffic directly over fiber, achieves more flexible for multivendor interoperability, and provides bandwidth efficient designs at the lower system latency. Hybrid access-networks via wireline or wireless connections are most likely needed for last-mile services. In the second part of this paper, we propose a joint source-channel multistream video coding scheme to combat the transmission errors under the harsh network conditions. On top of traditional error control techniques, the simulation results demonstrate that our multistream design outperform the conventional approaches by up to 5-7 dB under the harsh network conditions. To support our multistream video coding scheme, we need to access and manipulate video objects rather than the frame of pixels. In the third part of this paper, we focus on the coding of arbitrary shape video fully in the transform domain.
Sign onto Technical Committees [President's Message]

hen someone is new to the IEEE Signal Processing Society (SPS) and asks how to get involved with the community, a seasoned member will readily suggest that one starts out by joining a technical committee (TC). True, a TC is the home of a technical community, and it is essential for community building. Let's turn the clock back about 40 years, to when the first IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) was held. Back then in 1976, there were five TCs supporting one journal, the one that is now called  The TCs were digital signal processing, digital measurement of noise, electroacoustic transducers, speech processing , and underwater acoustics. You cannot recognize some of them now, right? Neither can I! Yes, time flies. What used to be popular or important may not seem relevant now. Now let's move ten years forward to around 1987, at which time I was still a graduate student. There were seven TCs then: audio and electroacoustics, digital signal processing, multidimentional signal processing, spectral estimation and modeling, speech processing, underwater acoustics, and VLSI for signal processing. At the same time, SPS still had one transaction and one three-year-old magazine. Let's fast-forward to the present. Now we have 12 TCs. None of them has the exact same name as those mentioned above. All have evolved to where they are today, plus many new disciplines have been added to the SPS family. As it stands now, all 12 TCs support seven Society-owned journals with many cosponsored journals, and two flagship conferences (there will be three by the end of this year) with many workshops and cospon-sored conferences. Our Society has grown a lot over the past few decades to become a multifac-eted, international community encompassing various activities. We went from a TC-centric structure to one with major boards on awards, membership, conference , publications, and technical directions. But one thing that has not changed over time but continues to get stronger is the TC as the home of a technical community. Those who work in the same technical areas will join the same TCs to share/exchange their findings and develop a network of community. But how many people can join a TC? The normal size of a TC in SPS has about 30–40 members. I asked a volunteer leader in this area what the size of the speech community within …
A robust method for QRS detection based on modified p-spectrum

In this paper, we propose a robust method based on the modified p-spectrum to detect heart beats in ECG signals, which is also referred as QRS detection in the literature. QRS detection is an old problem that has been studied for several decades. In the literature, there are many methods based on various forms of transformations and thresholding, which require predetermined or fine-tuned thresholds. Another class of existing methods are based on machine learning, which require carefully labeled training data. In our study, we propose the modified p-spectrum for QRS detection, which does not require either predetermined thresholds or training data, and can operate in real-time. The proposed method is evaluated using the MIT-BIH arrhythmia database.
Autonomous Identification of Selfish Colluders in Traitor-within-Traitor Behavior Forensics

During multi-user collusion attacks against digital fingerprinting, an important issue that colluders have to address is to distribute the risk evenly among all colluders and achieve fairness of the attack. Although they might agree so, some selfish colluders may break their agreement and process their fingerprinted copies before collusion in order to further reduce their own risk. To protect their own interest, other colluders have to detect these selfish colluders and exclude them from multi-user collusion. This paper studies this problem of traitors within traitors. We propose an autonomous selfish colluder detection and identification algorithm, in which colluders help each other detect selfish behavior. We show that the proposed algorithm can correctly identify all selfish colluders without falsely accusing any others, even when a small group of selfish colluders collaborate with each other to change the detection results.
Characterization of Distortion-SNR Performance for Practical Joint Source-Channel Coding Systems

This paper studies the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve, for systems using Joint Source-Channel Coding (JSCC) bit rate allocation. The D-SNR curve is shown to be well approximated for certain multimedia systems using practical source and channel codes, by a linear function in log-log scales. The D-SNR curve is characterized by following an approach that considers a set of carefully selected points, which are those where the relative contribution of channel errors to end-to-end distortion is small. The D-SNR characterization is applied to study the effects on performance of channel codes of different strength or source codes with different compression efficiency. The approach followed to characterize the D-SNR curve has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation, as it is illustrated for a scheme carrying voice traffic.
A context adaptive predictor of sensor pattern noise for camera source identification

Sensor pattern noise (SPN) is a noise-like spread-spectrum signal inherently cast onto every digital image by each imaging device and has been recognised as a reliable device fingerprint for camera source identification (CSI) and image origin verification. It can be estimated as the noise residual between the image content and its denoised version. However, the SPN extracted from a single image can be contaminated largely by image scene because image edge noise is usually much stronger than the SPN. So the identification performance is heavily dependent upon the purity of the estimated SPN, especially for small size images because they have less and weaker SPN. Although there are some existing works dedicated to improving the performance of source camera identification, an effective method to eliminate the contamination of image scene and extract an accurate SPN is currently lacking. In this paper, we will propose an edge adaptive SPN predictor based on context adaptive interpolation (PCAI) to exclude the contamination of image scene. Different from most of the existing methods extracting SPN from wavelet high frequency coefficients, we extract SPN directly from the spatial domain with a pixel-wise adaptive Wiener filter, based on the assumption that the SPN is a white signal. Extensive experiments show that our proposed PCAI method achieves the best receiver operating characteristic (ROC) performance among all of the state-of-the-art CSI schemes on different sizes of images, and has the best performance in resisting JPEG compression (e.g. with a quality factor of 90%) simultaneously.