Article
Engineering, Electrical & Electronic
Tong Qiao, Shengwang Xu, Shuai Wang, Xiaoshuai Wu, Bo Liu, Ning Zheng, Ming Xu, Binmin Pan
Summary: Steganography can achieve covert communication in public channels, but its effectiveness is challenged in practical applications. This study proposes a framework to generalize and compare different robust steganographic methods, and evaluates their performance in real-world applications, finding that methods modifying the sign of DCT coefficients perform better on social media.
EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING
(2023)
Article
Optics
Huatao Zhu, Zhanqi Liu, Peng Xiang, Shuwen Chen, Feiyu LI, Xiangming Xu
Summary: This paper proposes a quantum-noise stream ciphered optical stealth communication approach, which achieves covert transmission through techniques such as time spreading and phase modulation.
Article
Engineering, Electrical & Electronic
Yunzhao Yang, Xiaowei Yi, Xianfeng Zhao, Jinghong Zhang
Summary: A fast and secure MP3 steganographic scheme with multi-domain is proposed in this paper to address the issues of single domain embedding and encoder dependence. By combining multiple domains and designing a distortion function based on statistical properties, the scheme significantly improves imperceptibility and statistical undetectability, while decreasing execution time and increasing embedding capacity.
Article
Computer Science, Artificial Intelligence
Zhengze Li, Xiaoyuan Yang, Kangqing Shen, Fazhen Jiang, Jin Jiang, Huwei Ren, Yixiao Li
Summary: Image steganography is a longstanding image security problem, and the application of deep learning in recent years has outperformed traditional methods. However, CNN-based steganalyzers pose a serious threat to steganography. To address this, a new adversarial steganography framework called StegoFormer is proposed, based on CNN and Transformer with shifted window local loss. Experimental results show that StegoFormer surpasses existing methods in anti-steganalysis ability, steganography effectiveness, and information restoration.
Article
Computer Science, Information Systems
Alaa Abdulsalm Alarood, Ahmed Mohammed Alghamdi, Ahmed Omar Alzahrani, Abdulrahman Alzahrani, Eesa Alsolami
Summary: MP3 is a widely used audio file format known for its ability to reduce file sizes and ease of implementation. Steganography is an art of protecting communication from attackers. This paper presents a new steganography algorithm that uses an improved LSB technique to encode secret messages in MP3 audio files.
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY
(2022)
Article
Engineering, Electrical & Electronic
Wei Lu, Junhong Zhang, Xianfeng Zhao, Weiming Zhang, Jiwu Huang
Summary: This paper proposes a secure robust JPEG steganographic scheme based on an autoencoder and adaptive BCH encoding to prevent secret messages from being damaged during transmission in social networks. The autoencoder is pretrained to fit the transformation relationship between JPEG images before and after compression, and the BCH encoding is adaptively utilized to decrease the error rate of secret message extraction. DCT coefficient adjustment based on practical JPEG channel characteristics further improves the robustness and statistical security of the proposed scheme, which outperforms prior state-of-the-art schemes in terms of robust performance and statistical security.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Mahmoud M. Mahmoud, Huwaida T. Elshoush
Summary: We propose a novel LSB-BMSE method for enhancing LSB audio steganography by using an innovative mechanism, BMSE, to embed a secret message after hiding its size in random samples. Experimental results demonstrate that LSB-BMSE significantly surpasses existing methods in terms of hiding capacity and imperceptibility.
Article
Computer Science, Information Systems
Krystian Grzesiak, Zbigniew Piotrowski, Jan M. Kelner
Summary: This paper discusses the use of open and hidden transmission techniques in modern telecommunications systems, as well as how covert channels based on steganography ensure transmission security. A novel steganographic transmission method based on phase drift is presented, allowing for adaptive bit rates according to modulation types and radio channel conditions.
Article
Chemistry, Analytical
Jiao Yang Lu, Quan Jiang, Jiao Jiao Lei, Ying Xuan He, Wei Tao Huang
Summary: This study demonstrates the integration of DNA encoding and molecular recognition with electrochemistry for the detection of fish pathogens and molecular information encryption. The electrochemical system enables rapid and accurate detection of fish pathogens while protecting encoded information hidden in DNA. This system has the potential to advance molecular-level digitization technology.
ANALYTICA CHIMICA ACTA
(2022)
Article
Multidisciplinary Sciences
Dandan Hui, Husain Alqattan, Simin Zhang, Vladimir Pervak, Enam Chowdhury, Mohammed Th. Hassan
Summary: Modern electronics switch electrical signals using radio frequency electromagnetic fields on the nanosecond time scale, limiting the speed to gigahertz. Optical switches using terahertz and ultrafast laser pulses have recently been developed, increasing the switching speed to picoseconds and femtoseconds. This study demonstrates optical switching with attosecond resolution using the reflectivity modulation of a fused silica dielectric system, and shows the capability of controlling the switching signal using synthesized laser pulses for binary encoding. The results pave the way for optical switches and light-based electronics with petahertz speeds, significantly faster than current semiconductor-based electronics, and have important implications for information technology, optical communications, and photonic processor technologies.
Article
Computer Science, Information Systems
P. Mathivanan, A. Balaji Ganesh
Summary: This study proposes a steganography method using ECG signals as cover data for remote health monitoring. The watermarked data is transformed into QR codes to enhance security, and the selection of coefficient positions near zero helps minimize signal degradation. The imperceptibility of the watermarked ECG signals is evaluated using various performance metrics, while the quality of extracted watermarks is assessed using the Bit Error Rate. The results show good imperceptibility and identical reconstruction to the original ECG signals.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Nabanita Mukherjee (Ganguly), Goutam Paul, Sanjoy Kumar Saha
Summary: This work demonstrates a method to hide secret data in pixel difference values with a high capacity and efficiency, capable of withstanding various attacks. The method does not require the use of seeds or keys, showing strong resistance against attacks.
INFORMATION SCIENCES
(2021)
Article
Chemistry, Analytical
Jiao Yang Lu, Zhen Qi Bu, Wei Tao Huang
Summary: In this study, a comprehensive demonstration of peptide-based sensing of Pb2+, logic computing, information encoding, and security applications was conducted. The fluorescently labeled Pb2+-binding peptide exhibited different responses to various metal ions but was specific to Pb2+, which enabled the quantification of Pb2+ and logic calculations. Additionally, the peptide sequences and their selectivity allowed for information encoding and protection, providing a new option for information representation.
MICROCHEMICAL JOURNAL
(2023)
Article
Materials Science, Multidisciplinary
Qiaoli Ren, Gerile Aodeng, Lu Ga, Jun Ai
Summary: The new PCSS system integrates beneficial features such as high switching rate, high reversibility, and safety, which can be widely used in rewritable paper and is in line with the environmental protection concept of green printing.
MATERIALS & DESIGN
(2021)
Article
Mathematics, Interdisciplinary Applications
Chuanzhen Wu
Summary: This study investigates the impact of window selection on in-sample coefficient estimation and out-of-sample forecasting, finding that different window selections result in varying levels of stability in coefficient estimation and some specific window sizes show better accuracy in left-tail predictions. It suggests the possibility of achieving better out-of-sample forecasts by choosing a window from historical data.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Computer Science, Information Systems
Tianyun Liu, Diqun Yan, Nan Yan, Gang Chen
Summary: Fake-quality audio detection, specifically in the context of stereo-faked audio, is an important field in digital audio forensics. This study proposes an anti-forensic framework based on generative adversarial network to expose the weaknesses of stereo-faking detectors. By generating fake stereo audio using a mono audio, the researchers demonstrate that detection accuracy can significantly decrease while the false acceptance rate increases.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Hui Xiao, Dong Li, Hao Xu, Shuibo Fu, Diqun Yan, Kangkang Song, Chengbin Peng
Summary: This study proposes a cross-teacher training framework with three modules, including a cross-teacher module, high-level contrastive learning module, and low-level contrastive learning module, to significantly improve traditional semi-supervised learning methods. Experimental results demonstrate that our framework outperforms state-of-the-art methods on benchmark datasets.
Review
Acoustics
Jinxing Gao, Diqun Yan, Mingyu Dong
Summary: This article introduces speech emotion recognition as a key branch of affective computing and explores the performance of different emotion recognition methods. The author improves the robustness of the model by using black-box attacks and finds the effectiveness of adversarial training in combating attacks.
EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING
(2022)
Article
Computer Science, Information Systems
Yi Xie, Xianliang Jiang, Guang Jin, Ziyi Jiang, DiQun Yan
Summary: This paper introduces an enhanced LEDBAT protocol called NLPC, which aims to solve the throughput degradation issue of LEDBAT in high-speed and lossy networks. By introducing a variable gain value that can dynamically adapt to the network congestion degree to update the sending rate, NLPC increases throughput up to 40% compared to LEDBAT in high-speed lossy networks, while maintaining the low-priority feature as other LBE protocols.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Acoustics
Mingyu Dong, Diqun Yan, Yongkang Gong
Summary: This paper proposes a defense method to enhance the robustness and security of automatic speech recognition (ASR) systems against adversarial examples. It introduces an algorithm for devastating and detecting adversarial examples that can attack advanced ASR systems.
JOURNAL OF THE AUDIO ENGINEERING SOCIETY
(2023)
Correction
Computer Science, Artificial Intelligence
Hui Xiao, Li Dong, Hao Xu, Shuibo Fu, Diqun Yan, Kangkang Song, Chengbin Peng
Article
Computer Science, Information Systems
Lang Chen, Rangding Wang, Li Dong, Diqun Yan
Summary: Recently, deep learning based audio steganalysis methods have posed significant challenges to conventional audio steganography by demonstrating superior performance in detecting it. In this work, the authors propose an imperceptible audio steganography method based on a psychoacoustic model, taking into consideration the vulnerability of neural networks to adversarial examples. They use a two-stage optimization strategy to minimize the loss function and add perturbation to the stego audio to deceive the steganalyzer. Experimental results show that the proposed method outperforms conventional audio steganography schemes in terms of imperceptibility and undetectability.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Kailai Shen, Diqun Yan, Zhe Ye, Xianbo Xu, JinXing Gao, Li Dong, Chengbin Peng, Kun Yang
Summary: Speech quality in online conferencing applications is often influenced by various factors like background noise, reverberation, packet loss, and network jitter. It is challenging to evaluate the quality of conferencing speech without a clean reference signal. Therefore, an effective non-intrusive speech quality assessment method is needed. This paper proposes a network framework for NISQA based on ResNet and BiLSTM, which can extract local features and integrate representative features with long-term time dependencies and sequential characteristics. Experimental results show a strong correlation between the proposed method and the mean opinion score of clean, noisy, and processed speech.
SIGNAL IMAGE AND VIDEO PROCESSING
(2023)
Article
Acoustics
Kailai Shen, Diqun Yan, Li Dong
Summary: This research proposes a framework called MSQAT, which includes three modules - ASTB, TAB, and RSTB, to enhance the interactions between local and global speech regions. Additionally, a two-branch structure is designed for better speech quality evaluation. Experimental results demonstrate that MSQAT achieves state-of-the-art performance on three standard datasets, and the pure attention model can achieve or surpass the performance of other CNN-attention hybrid models.
Article
Engineering, Electrical & Electronic
Zhe Ye, Diqun Yan, Li Dong, Jiacheng Deng, Shui Yu
Summary: Deep learning has made significant progress in speaker recognition, but malicious third-party platforms pose a serious security threat through backdoor attacks. Existing speech backdoor attack methods use fixed and unnoticeable perturbations as triggers, which can still be detected. To overcome this, we propose PhaseBack, a novel backdoor attack paradigm that injects triggers in the phase spectrum, leveraging the insensitivity of the human ear to phase information. PhaseBack's effectiveness and stealthiness are demonstrated through extensive experiments on the Voxceleb1 dataset, and it also shows strong resistance against several defense methods.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Proceedings Paper
Computer Science, Information Systems
Jiale Chen, Li Dong, Rangding Wang, Diqun Yan, Weiwei Sun, Hang-Yu Fan
Summary: In this work, a physical anti-copying semi-robust randomly watermarking system for QR code is proposed. By exploiting the distortion characteristics between authentic and counterfeit channels, a randomly watermark embedding system is devised. Experimental results demonstrate the effectiveness of the proposed watermarking system.
DIGITAL FORENSICS AND WATERMARKING, IWDW 2022
(2023)
Proceedings Paper
Computer Science, Information Systems
Weipeng Liang, Li Dong, Rangding Wang, Diqun Yan, Yuanman Li
Summary: Digital documents are increasingly being used as credible evidence, but they are vulnerable to forgery and manipulation. This study proposes a robust method for detecting document image forgery, using a neural network architecture and attention mechanisms to extract features and identify forgeries.
2022 IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS, TRUSTCOM
(2022)
Article
Engineering, Electrical & Electronic
Jiacheng Deng, Li Dong, Rangding Wang, Rui Yang, Diqun Yan
Summary: This letter proposes a two-step query-efficient decision-based attack based on local low-frequency perturbation for speaker recognition systems, which achieves a higher attacking success rate.
IEEE SIGNAL PROCESSING LETTERS
(2022)
Article
Computer Science, Information Systems
Yongkang Gong, Diqun Yan, Terui Mao, Donghua Wang, Rangding Wang
Summary: This study focuses on countermeasures against audio adversarial examples, finding that frame offsets with silence clip appended at the beginning of an audio can degenerate adversarial perturbations to normal noise. Different strategies like defending, detecting, and hybrid strategies are proposed to exploit frame offsets for various scenarios, offering a simpler, more generic, and efficient defense method against audio adversarial examples.
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
(2021)
Article
Computer Science, Information Systems
Kaiyu Ying, Rangding Wang, Yuzhen Lin, Diqun Yan
Summary: Syndrome-Trellis Code (STC) is a near-optimal convolutional method for adaptive steganography that improves embedding position control; an Adaptive-STC approach utilizes an adaptive parity-check matrix generation method to enhance steganography performance; the proposed method outperforms existing techniques in reducing embedding changes and improving audio quality.
Article
Computer Science, Information Systems
Kashan Ahmed, Syed Khaldoon Khurshid, Sadaf Hina
Summary: This paper mainly introduces the construction of the cyber threat intelligence knowledge graph and the information extraction technique. By using joint extraction technique, it solves the problem of traditional techniques becoming ineffective due to the increasing size of CTI data. Experimental results show that this technique outperforms state-of-the-art models in knowledge triple extraction on CTI data and improves the F1 score.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Xinlong He, Yang Xu, Sicong Zhang, Weida Xu, Jiale Yan
Summary: This paper proposes a new membership inference attack method in federated learning, which utilizes data poisoning and sequence prediction confidence. The attack is effective and results in minimal overall model performance degradation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Tieming Chen, Huan Zeng, Mingqi Lv, Tiantian Zhu
Summary: In this paper, the authors propose a deep learning based dynamic malware detection method called CTIMD, which integrates threat knowledge from CTIs into the learning process of API call sequences with runtime parameters. Experimental results show that CTIMD outperforms existing methods in terms of performance.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wonwoo Choi, Minjae Seo, Seongman Lee, Brent Byunghoon Kang
Summary: This paper proposes SUM, a backward-edge control flow protection scheme for ARM Cortex-M processors. It combines MPU and the overlooked hardware feature FaultMask to achieve efficient and robust protection. The empirical evaluation shows minimal runtime overhead for the proposed solution.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Liliana Ribeiro, Ines Sousa Guedes, Carla Sofia Cardoso
Summary: Phishing susceptibility is influenced by individual and contextual factors. The study found that individuals who perceive themselves as capable of detecting phishing and those who use online services more frequently are more susceptible to phishing. However, technology competencies and other individual variables do not predict phishing susceptibility.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wenjie Wang, Yuanhai Shao, Yiju Wang
Summary: In this paper, we investigate the adversarial perturbations of twin support vector machines (TWSVMs) and propose an optimization framework, which provides explicit solutions to increase the interpretability of the conclusion and convenience for calculation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Snofy D. Dunston, V. Mary Anita Rajam
Summary: This paper proposes a novel adversarial attack technique that can synthesize adversarial images to mislead deep learning models, and also studies interpretability plots. The research findings show that the proposed attack technique influences the interpretability plots, regardless of the success of the attack.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Junchen Li, Guang Cheng, Zongyao Chen, Peng Zhao
Summary: Protocol Reverse Engineering (PRE) is a direct approach for analyzing unknown traffic. This paper proposes a method for clustering unknown traffic based on private protocol labels, and the experimental results demonstrate its advantages on real-world network traffic.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Rafal Kozik, Massimo Ficco, Aleksandra Pawlicka, Marek Pawlicki, Francesco Palmieri, Michal Choras
Summary: The inclusion of Explainability of Artificial Intelligence (xAI) has become a mandatory requirement for designing and implementing reliable, interpretable, and ethical AI solutions. However, it has been shown that xAI can enable successful adversarial attacks in the domain of fake news detection, leading to a decrease in AI security. This paper presents an attack scheme that uses an explainable solution to reshape the structure of the original message, allowing the adversary to manipulate the model's prediction while keeping the message's meaning intact.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Benyuan Yang, Lili Luo, Zhimeng Wang
Summary: Interoperation is widely used in practical industrial applications, but merging local access control policies may lead to security violations. Dealing with these issues in a multidomain environment is critical, but finding the maximum secure interoperation among individual systems poses a challenge due to the large number of entities and access involved.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Binghui Zou, Chunjie Cao, Longjuan Wang, Sizheng Fu, Tonghua Qiao, Jingzhang Sun
Summary: The ongoing struggle between security researchers and malware has led to the exploration of using convolutional neural networks and capsule networks for classification and identification of malware. However, training these networks requires a significant amount of data and parameters, and the research on capsule networks is still in its early stages, posing challenges.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Hongsong Chen, Xingyu Li, Wenmao Liu
Summary: Multivariate time-series anomaly detection is crucial for maintaining normal operation of physical equipment. Recent advances have been made in this field, but two challenges have limited the model's ability to generalize. To address these challenges, a multivariate time-series anomaly detection model consisting of a characterization network and a forecasting network is proposed. Experimental results demonstrate that this method outperforms baseline methods in terms of detection performance and robustness.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Roberto Doriguzzi-Corin, Domenico Siracusa
Summary: This paper discusses the application of federated learning in the field of cybersecurity and proposes an adaptive mechanism-based federated learning solution for DDoS attack detection in dynamic cybersecurity scenarios. Through experiments, it is demonstrated that the proposed solution outperforms state-of-the-art federated learning algorithms in terms of convergence time and accuracy.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Antonio Giovanni Schiavone
Summary: The usage of HTTPS protocol is crucial for secure communication with websites, ensuring the confidentiality, integrity, and authenticity of online data transmissions. The Municipality2HTTPS research project analyzed the implementation of HTTPS in Italian municipalities' websites and identified areas for improvement.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Domna Bilika, Nikoletta Michopoulou, Efthimios Alepis, Constantinos Patsakis
Summary: Voice Assistants (VAs) are widely used in smart devices, but are vulnerable to attacks, as shown by experiments with popular VAs revealing successful attack rates exceeding 30% and statistical variations among vendors, calling for additional countermeasures to protect user information.
COMPUTERS & SECURITY
(2024)
