Article
Computer Science, Artificial Intelligence
Mukesh Dalal, Mamta Juneja
Summary: This paper provides a qualitative and quantitative analysis of various video steganography techniques, discussing their properties, challenges, pros, and cons, as well as different quality metrics and steganalysis attacks. It also includes experimental analysis of prominent techniques and highlights real-life applications of video steganography along with suggesting future research directions. The main objective is to assist beginners in understanding the basic concepts of the research domain and initiating their own research in this field.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Multidisciplinary Sciences
Ying Liu, Jiangqun Ni, Wenkang Su
Summary: Research has found that combining logic-based and local Lagrangian cost quotient features is more effective in detecting video steganography than using a single feature. The proposed method exhibits superior detection performance compared to other existing schemes and works well even when there is a mismatch between the cover source and steganographic scheme, indicating its practical applicability.
Article
Computer Science, Information Systems
Negin Ghamsarian, Klaus Schoeffmann, Morteza Khademi
Summary: The paper introduces a method for detecting MV-based video steganography using spatio-temporal features for blind detection. Experimental results demonstrate that the performance of these features far exceeds that of existing steganalysis methods.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Yuanzhi Yao, Nenghai Yu
Summary: This paper proposes a payload allocation strategy in video steganography based on motion vector modification distortion analysis, which can enhance the performance of motion vector-based video steganographic methods and achieve lower computational complexity by restraining residue deviation propagation.
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
(2021)
Article
Engineering, Electrical & Electronic
Ying Liu, Jiangqun Ni, Weizhe Zhang, Jiwu Huang
Summary: In this study, a novel steganographic scheme in the motion vector domain for H.264 video is proposed. The scheme improves the security performance against the newly emerged multi-domain feature set MVC, while maintaining good coding efficiency.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Theory & Methods
Quentin Giboulot, Tomas Pevny, Andrew D. D. Ker
Summary: The highly heterogeneous nature of images in real-world environments poses a challenge for steganalysis techniques. Recent advancements in understanding image properties and deep neural networks have helped tackle this problem, but the current modeling of the game between steganographer and steganalyst lacks important features. We propose a two-player game considering the adaptability of the steganographer, the impact of cover source distribution, and the different goals of both parties. By applying this approach to contemporary steganography and steganalysis, we show that classifiers that do not adapt to the environment underperform.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Jun Li, Minqing Zhang, Ke Niu, Xiaoyuan Yang
Summary: This paper proposes three principles for cost assignment in the motion vector domain and designs three corresponding practical distortion functions. A joint distortion function is then constructed based on these principles to improve overall performance.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Hyeokjoon Kweon, Jinsun Park, Sanghyun Woo, Donghyeon Cho
Summary: In this paper, a deep multi-image steganography method with private keys is proposed to hide multiple secret images within a single cover image while ensuring high security. By introducing private keys for each secret image, the method allows individual access to each secret image and ensures the confidentiality of other hidden images and private keys. The proposed algorithm effectively conceals and reveals multiple secret images in a visually similar container image.
Article
Computer Science, Hardware & Architecture
Zhonghao Li, Xinghao Jiang, Yi Dong, Laijin Meng, Tanfeng Sun
Summary: This article proposes a prediction unit(PU) based wide residual-net steganography(PWRN) for HEVC videos. The data hiding method in this article allows to modify all types of PUs except for 2N x 2N according to the secret data. The experimental results show that PWRN successfully resists the latest PU-targeted steganalysis algorithms and achieves the lowest bitrate cost and highest visual quality under the same capacity compared to the state-of-the-art work.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2023)
Article
Computer Science, Information Systems
Yi Dong, Xinghao Jiang, Zhaohong Li, Tanfeng Sun, Zhenzhen Zhang
Summary: This paper proposes an HEVC steganographic algorithm that resists IPM shift by introducing channel division and distortion function based on block size, and discovering a unique IPM transition probability distribution in HEVC. A mapping rule is designed based on this distribution to achieve a better embedding effect. Experimental results show that the proposed algorithm outperforms the state-of-the-art steganography in resisting steganalysis, bitrate controlling, and visual quality.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Computer Science, Information Systems
Mukesh Dalal, Mamta Juneja
Summary: The proposed scheme uses H.264/AVC video format for steganography, employs Discrete Wavelet Transform and multiple object tracking on ROI for embedding secret data, demonstrating high robustness and security in testing.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Review
Chemistry, Analytical
Zhijun Wu, Junjun Guo, Chenlei Zhang, Changliang Li
Summary: The paper discusses the research hotspots of steganography and steganalysis based on VoIP, divided into two categories: based on voice payload and protocol. It summarizes their characteristics and development directions.
Article
Chemistry, Analytical
Alexandre Augusto Giron, Jean Everson Martina, Ricardo Custodio
Summary: Steganography, a method of hiding data between parties, has been suggested to be potentially used in public blockchains for hiding communications, although concrete evidence of actual use is lacking. Researchers have developed a steganalysis approach for Bitcoin and Ethereum to investigate the presence of steganography in these cryptocurrencies.
Article
Computer Science, Artificial Intelligence
Junfeng Zhao, Shen Wang
Summary: This paper proposes a stable GAN-based image steganography method called UMC-GAN, which improves security performance through a redesigned and adjustable nested U-Shape generator and deep supervision.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Theory & Methods
Qingxiao Guan, Peng Liu, Weiming Zhang, Wei Lu, Xinpeng Zhang
Summary: In this paper, we propose a coding scheme framework extended from Dual-Syndrome Trellis Codes (Dual-STCs) for robust adaptive steganography. We design an iteratively decoding scheme for error-correcting two layer stego bits from their joint conditional probabilities, and strict proof its convergence. We also introduce a method to estimate these probability distributions from stego data pairs uploaded/downloaded from the lossy transmission channel.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Engineering, Electrical & Electronic
Alam Abbas Syed, Hassan Foroosh
Summary: This paper presents effective methods using spherical polar Fourier transform data for two different applications: 3D volumetric registration and machine learning classification network. The proposed method for registration offers unique and effective techniques, handling arbitrary large rotation angles and showing robustness. The modified classification network achieves robust classification results in processing spherical data.
Article
Engineering, Electrical & Electronic
Ruibo Fan, Mingli Jing, Jingang Shi, Lan Li, Zizhao Wang
Summary: In this study, a new low-rank sparse decomposition algorithm named TVRPCA+ is proposed for foreground-background separation. The algorithm combines spectral norm, structured sparse norm, and total variation regularization to suppress noise and obtain cleaner foregrounds. Experimental results demonstrate that TVRPCA+ achieves high performance in complex backgrounds and noise scenarios.
Article
Engineering, Electrical & Electronic
Omair Aldimashki, Ahmet Serbes
Summary: This paper proposes a coarse-to-fine FrFT-based algorithm for chirp-rate estimation of multi-component LFM signals, which achieves improved performance and a reduced signal-to-noise breakdown threshold by utilizing mathematical models for coarse estimation and a refined estimate-and-subtract strategy. Extensive simulation results demonstrate that the proposed algorithm performs very close to the Cramer-Rao lower bound, with the advantages of eliminating leakage effect, avoiding error propagation, and maintaining acceptable computational cost compared to other state-of-the-art methods.
Article
Engineering, Electrical & Electronic
Xinlei Shi, Xiaofei Zhang, Yuxin Sun, Yang Qian, Jinke Cao
Summary: In this paper, a low-complexity localization approach for multiple sources using two-dimensional discrete Fourier transform (2D-DFT) is proposed. The method computes the cross-covariance and utilizes phase offset method and total least square solution to obtain accurate position estimates.
Article
Engineering, Electrical & Electronic
Prabhanjan Mannari, Ratnasingham Tharmarasa, Thiagalingam Kirubarajan
Summary: This paper discusses the problem of extended target tracking for a single 2D extended target with a known convex polytope shape and dynamics. It proposes a framework based on the existing point multitarget tracking framework to address the challenges of uncertainty in shape and kinematics, as well as self-occlusion. The algorithm developed using this framework is capable of dynamically changing the number of parameters used to describe the shape and estimating the whole target shape even when different parts of the target are visible at different frames.
Article
Engineering, Electrical & Electronic
Yongsong Li, Zhengzhou Li, Jie Li, Junchao Yang, Abubakar Siddique
Summary: This paper proposes a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The WARTH method effectively measures local and global feature information using an adaptive ring-shaped structural element and a target awareness indicator, resulting in accurate detection of small targets with minimized false alarms.
Article
Engineering, Electrical & Electronic
Yu Wang, Zhen Qin, Jun Tao, Yili Xia
Summary: In this paper, an enhanced sparsity-aware recursive least squares (RLS) algorithm is proposed, which combines the proportionate updating (PU) and zero-attracting (ZA) mechanisms, and introduces a general convex regularization (CR) function and variable step-size (VSS) technique to improve performance.
Article
Engineering, Electrical & Electronic
Neil J. Bershad, Jose C. M. Bermudez
Summary: This paper analyzes the impact of processing delay on the Least Mean Squares (LMS) algorithm in system identification, highlighting bias issues in the resulting weight vector.
Article
Engineering, Electrical & Electronic
Kanghui Jiang, Defu Jiang, Mingxing Fu, Yan Han, Song Wang, Chao Zhang, Jingyu Shi
Summary: In this paper, a novel method for velocity estimation using multicarrier signals in a single dwell is proposed, which effectively addresses the issue of Doppler ambiguity in pulse Doppler radars.
Article
Engineering, Electrical & Electronic
Xiao-Jun Zhang, Peng-Lang Shui, Yu-Fan Xue
Summary: This paper proposes a method for low-velocity small target detection in maritime surveillance radars. It models sea clutter sequences using the spherical invariant random vector (SIRV) model with block tridiagonal speckle covariance matrix and inverse Gamma distributed texture. The proposed detector, which is a long-time adaptive generalized likelihood ratio test with linear threshold detector (GLRT-LTD), shows competitive detection performance in experiments.
Article
Engineering, Electrical & Electronic
Aiyi Zhang, Fulai Liu, Ruiyan Du
Summary: This paper proposes an adaptive weighted robust data recovery method with total variation regularization for hyperspectral image. The method models the HSI recovery problem as a tensor robust principal component analysis optimization problem, decomposing the data into low-rank HSI data, outliers, and noise component. An adaptive weighted strategy is then defined to impose on the tensor nuclear norm and outliers, using the priori information of singular values and strengthening the sparsity of outliers.
Article
Engineering, Electrical & Electronic
Hamid Asadi, Babak Seyfe
Summary: This paper presents a novel approach for estimating the model order in the presence of observation errors. The proposed method is based on correntropy estimation of eigenvalues in the observation space, which is further enhanced by resampling the observations using the bootstrap method. The algorithm partitions the observation space into signal and noise subspaces using the covariance matrix of mixtures, and determines the model order based on a correntropy estimator with kernel functions. Theoretical analysis and comparative evaluations demonstrate the superiority of this information-theoretic approach.
Article
Engineering, Electrical & Electronic
Buket colak Guvenc, Engin Cemal Menguc
Summary: In this paper, a novel family of online censoring based complex-valued least mean kurtosis (CLMK) algorithms is proposed. The algorithms censor less informative complex-valued data streams and reduce the costs of data processing without affecting accuracy. Robust algorithms are also developed to handle outliers. The simulation results confirm the attractive features of the proposed algorithms in large-scale system identification and regression scenarios.
Article
Engineering, Electrical & Electronic
Yun Su, Weixian Tan, Yifan Dong, Wei Xu, Pingping Huang, Jianxin Zhang, Diankun Zhang
Summary: In this study, a novel method for detecting low-resolution and small targets in millimeter wave radar images is proposed. The Wavelet-Conv structure and Wavelet-Attention mechanism are introduced to overcome the limitations of existing detectors. Experimental results demonstrate that the proposed method improves recall and mean average precision while maintaining competitive inference speed.
Article
Engineering, Electrical & Electronic
Xin Wang, Xingxing Jiang, Qiuyu Song, Jie Liu, Jianfeng Guo, Zhongkui Zhu
Summary: This study proposes a variational mode extraction (VME) method for extracting specific modes from complicated signals. By exploring the convergence property of VME, strategies for identifying ICF and determining the balance parameter are designed, and a bandwidth estimation strategy is constructed. The effectiveness of the proposed method for bearings fault diagnosis is verified and compared with other methods.