Visible to the public Biblio

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2021-06-28
Sarabia-Lopez, Jaime, Nuñez-Ramirez, Diana, Mata-Mendoza, David, Fragoso-Navarro, Eduardo, Cedillo-Hernandez, Manuel, Nakano-Miyatake, Mariko.  2020.  Visible-Imperceptible Image Watermarking based on Reversible Data Hiding with Contrast Enhancement. 2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE). :29–34.
Currently the use and production of multimedia data such as digital images have increased due to its wide use within smart devices and open networks. Although this has some advantages, it has generated several issues related to the infraction of intellectual property. Digital image watermarking is a promissory solution to solve these issues. Considering the need to develop mechanisms to improve the information security as well as protect the intellectual property of the digital images, in this paper we propose a novel visible-imperceptible watermarking based on reversible data hiding with contrast enhancement. In this way, a watermark logo is embedded in the spatial domain of the original image imperceptibly, so that the logo is revealed applying reversible data hiding increasing the contrast of the watermarked image and the same time concealing a great amount of data bits, which are extracted and the watermarked image restored to its original conditions using the reversible functionality. Experimental results show the effectiveness of the proposed algorithm. A performance comparison with the current state-of-the-art is provided.
Li, Meng, Zhong, Qi, Zhang, Leo Yu, Du, Yajuan, Zhang, Jun, Xiang, Yong.  2020.  Protecting the Intellectual Property of Deep Neural Networks with Watermarking: The Frequency Domain Approach. 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). :402–409.
Similar to other digital assets, deep neural network (DNN) models could suffer from piracy threat initiated by insider and/or outsider adversaries due to their inherent commercial value. DNN watermarking is a promising technique to mitigate this threat to intellectual property. This work focuses on black-box DNN watermarking, with which an owner can only verify his ownership by issuing special trigger queries to a remote suspicious model. However, informed attackers, who are aware of the watermark and somehow obtain the triggers, could forge fake triggers to claim their ownerships since the poor robustness of triggers and the lack of correlation between the model and the owner identity. This consideration calls for new watermarking methods that can achieve better trade-off for addressing the discrepancy. In this paper, we exploit frequency domain image watermarking to generate triggers and build our DNN watermarking algorithm accordingly. Since watermarking in the frequency domain is high concealment and robust to signal processing operation, the proposed algorithm is superior to existing schemes in resisting fraudulent claim attack. Besides, extensive experimental results on 3 datasets and 8 neural networks demonstrate that the proposed DNN watermarking algorithm achieves similar performance on functionality metrics and better performance on security metrics when compared with existing algorithms.
2021-05-25
[Anonymous].  2020.  B-DCT based Watermarking Algorithm for Patient Data Protection in IoMT. 2020 International Conference on Information Security and Cryptology (ISCTURKEY). :1—4.
Internet of Medical Things (IoMT) is the connection between medical devices and information systems to share, collect, process, store, and integrate patient and health data using network technologies. X-Rays, MR, MRI, and CT scans are the most frequently used patient medical image data. These images usually include patient information in one of the corners of the image. In this research work, to protect patient information, a new robust and secure watermarking algorithm developed for a selected region of interest (ROI) of medical images. First ROI selected from the medical image, then selected part divided equal blocks and applied Discrete Cosine Transformation (DCT) algorithm to embed a watermark into the selected coefficients. Several geometric and removal attacks are applied to the watermarked multimedia element such as lossy image compression, the addition of Gaussian noise, denoising, filtering, median filtering, sharpening, contrast enhancement, JPEG compression, and rotation. Experimental results show very promising results in PSNR and similarity ratio (SR) values after blocked DCT (B-DCT) based embedding algorithm against the Discrete Wavelet Transformation (DWT), Least Significant Bits (LSB) and DCT algorithms.
2021-04-09
Mir, N., Khan, M. A. U..  2020.  Copyright Protection for Online Text Information : Using Watermarking and Cryptography. 2020 3rd International Conference on Computer Applications Information Security (ICCAIS). :1—4.
Information and security are interdependent elements. Information security has evolved to be a matter of global interest and to achieve this; it requires tools, policies and assurance of technologies against any relevant security risks. Internet influx while providing a flexible means of sharing the online information economically has rapidly attracted countless writers. Text being an important constituent of online information sharing, creates a huge demand of intellectual copyright protection of text and web itself. Various visible watermarking techniques have been studied for text documents but few for web-based text. In this paper, web page watermarking and cryptography for online content copyrights protection is proposed utilizing the semantic and syntactic rules using HTML (Hypertext Markup Language) and is tested for English and Arabic languages.
2021-04-08
Zheng, Y., Cao, Y., Chang, C..  2020.  A PUF-Based Data-Device Hash for Tampered Image Detection and Source Camera Identification. IEEE Transactions on Information Forensics and Security. 15:620—634.
With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identification. Unfortunately, existing solutions that address image tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured images. In this paper, a new perceptual data-device hash is proposed to locate maliciously tampered image regions and identify the source camera of the received image data as a non-repudiable attestation in digital forensics. The presented image may have been either tampered or gone through benign content preserving geometric transforms or image processing operations. The proposed image hash is generated by projecting the invariant image features into a physical unclonable function (PUF)-defined Bernoulli random space. The tamper-resistant random PUF response is unique for each camera and can only be generated upon triggered by a challenge, which is provided by the image acquisition timestamp. The proposed hash is evaluated on the modified CASIA database and CMOS image sensor-based PUF simulated using 180 nm TSMC technology. It achieves a high tamper detection rate of 95.42% with the regions of tampered content successfully located, a good authentication performance of above 98.5% against standard content-preserving manipulations, and 96.25% and 90.42%, respectively, for the more challenging geometric transformations of rotation (0 360°) and scaling (scale factor in each dimension: 0.5). It is demonstrated to be able to identify the source camera with 100% accuracy and is secure against attacks on PUF.
2021-03-17
Wang, M., Xiao, J., Cai, Z..  2020.  An effective technique preventing differential cryptanalysis attack. 2020 IEEE 29th Asian Test Symposium (ATS). :1—6.
In this paper, an adaptive scan chain structure based plaintext analysis technique is proposed. The technology is implemented by three circuits, including adaptive scan chain circuit, plaintext analysis circuit and controller circuit. The plaintext is analyzed whether meet the characteristics of the differential cryptanalysis in the plaintext analysis module. The adaptive scan chain contains MUX, XOR and traditional scan chain, which is easy to implement. If the last bit of two plaintexts differs by one, the adaptive scan chain is controlled to input them into different scan chain. Compared with complicated scan chain, the structure of adaptive scan chain is variable and can mislead attackers who use differential cryptanalysis attack. Through experimental analysis, it is proved that the security of the adaptive scan chain structure is greatly improved.
2021-03-09
Sibahee, M. A. A., Lu, S., Abduljabbar, Z. A., Liu, E. X., Ran, Y., Al-ashoor, A. A. J., Hussain, M. A., Hussien, Z. A..  2020.  Promising Bio-Authentication Scheme to Protect Documents for E2E S2S in IoT-Cloud. 2020 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). :1—6.

Document integrity and origin for E2E S2S in IoTcloud have recently received considerable attention because of their importance in the real-world fields. Maintaining integrity could protect decisions made based on these message/image documents. Authentication and integrity solutions have been conducted to recognise or protect any modification in the exchange of documents between E2E S2S (smart-to-smart). However, none of the proposed schemes appear to be sufficiently designed as a secure scheme to prevent known attacks or applicable to smart devices. We propose a robust scheme that aims to protect the integrity of documents for each users session by integrating HMAC-SHA-256, handwritten feature extraction using a local binary pattern, one-time random pixel sequence based on RC4 to randomly hide authentication codes using LSB. The proposed scheme can provide users with one-time bio-key, robust message anonymity and a disappearing authentication code that does not draw the attention of eavesdroppers. Thus, the scheme improves the data integrity for a users messages/image documents, phase key agreement, bio-key management and a one-time message/image document code for each users session. The concept of stego-anonymity is also introduced to provide additional security to cover a hashed value. Finally, security analysis and experimental results demonstrate and prove the invulnerability and efficiency of the proposed scheme.

Guibene, K., Ayaida, M., Khoukhi, L., MESSAI, N..  2020.  Black-box System Identification of CPS Protected by a Watermark-based Detector. 2020 IEEE 45th Conference on Local Computer Networks (LCN). :341–344.

The implication of Cyber-Physical Systems (CPS) in critical infrastructures (e.g., smart grids, water distribution networks, etc.) has introduced new security issues and vulnerabilities to those systems. In this paper, we demonstrate that black-box system identification using Support Vector Regression (SVR) can be used efficiently to build a model of a given industrial system even when this system is protected with a watermark-based detector. First, we briefly describe the Tennessee Eastman Process used in this study. Then, we present the principal of detection scheme and the theory behind SVR. Finally, we design an efficient black-box SVR algorithm for the Tennessee Eastman Process. Extensive simulations prove the efficiency of our proposed algorithm.

elazm, L. A. Abou, Ibrahim, S., Egila, M. G., Shawkey, H., Elsaid, M. K. H., El-Shafai, W., El-Samie, F. E. Abd.  2020.  Hardware Implementation of Cancellable Biometric Systems. 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :1145–1152.

The use of biometrics in security applications may be vulnerable to several challenges of hacking. Thus, the emergence of cancellable biometrics becomes a suitable solution to this problem. This paper presents a one-way cancellable biometric transform that depends on 3D chaotic maps for face and fingerprint encryption. It aims to avoid cloning of original biometrics and allow the templates used by each user in different applications to be variable. The permutations achieved with the chaotic maps guarantee high security of the biometric templates, especially with the 3D implementation of the encryption algorithm. In addition, the paper presents a hardware implementation for this framework. The proposed algorithm also achieves good performance in the presence of low and moderate levels of noise. An experimental version of the proposed cancellable biometric system has been applied on FPGA model. The obtained results achieve a powerful performance of the proposed cancellable biometric system.

2021-02-23
Kabatiansky, G., Egorova, E..  2020.  Adversarial multiple access channels and a new model of multimedia fingerprinting coding. 2020 IEEE Conference on Communications and Network Security (CNS). :1—5.

We consider different models of malicious multiple access channels, especially for binary adder channel and for A-channel, and show how they can be used for the reformulation of digital fingerprinting coding problems. In particular, we propose a new model of multimedia fingerprinting coding. In the new model, not only zeroes and plus/minus ones but arbitrary coefficients of linear combinations of noise-like signals for forming watermarks (digital fingerprints) can be used. This modification allows dramatically increase the possible number of users with the property that if t or less malicious users create a forge digital fingerprint then a dealer of the system can find all of them with zero-error probability. We show how arisen problems are related to the compressed sensing problem.

2021-02-15
Rana, M. M., Mehedie, A. M. Alam, Abdelhadi, A..  2020.  Optimal Image Watermark Technique Using Singular Value Decomposition with PCA. 2020 22nd International Conference on Advanced Communication Technology (ICACT). :342–347.
Image watermarking is very important phenomenon in modern society where intellectual property right of information is necessary. Considering this impending problem, there are many image watermarking methods exist in the literature each of having some key advantages and disadvantages. After summarising state-of-the-art literature survey, an optimum digital watermark technique using singular value decomposition with principle component analysis (PCA) is proposed and verified. Basically, the host image is compressed using PCA which reduces multi-dimensional data to effective low-dimensional information. In this scheme, the watermark is embedded using the discrete wavelet transformation-singular value decomposition approach. Simulation results show that the proposed method improves the system performance compared with the existing method in terms of the watermark embedding, and extraction time. Therefore, this work is valuable for image watermarking in modern life such as tracing copyright infringements and banknote authentication.
2020-11-09
Sengupta, A., Gupta, G., Jalan, H..  2019.  Hardware Steganography for IP Core Protection of Fault Secured DSP Cores. 2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin). :1–6.
Security of transient fault secured IP cores against piracy, false claim of ownership can be achieved during high level synthesis, especially when handling DSP or multimedia cores. Though watermarking that involves implanting a vendor defined signature onto the design can be useful, however research has shown its limitations such as less designer control, high overhead due to extreme dependency on signature size, combination and encoding rule. This paper proposes an alternative paradigm called `hardware steganography' where hidden additional designer's constraints are implanted in a fault secured IP core using entropy thresholding. In proposed hardware steganography, concealed information in the form of additional edges having a specific entropy value is embedded in the colored interval graph (CIG). This is a signature free approach and ensures high designer control (more robustness and stronger proof of authorship) as well as lower overhead than watermarking schemes used for DSP based IP cores.
Bose, S., Raikwar, M., Mukhopadhyay, D., Chattopadhyay, A., Lam, K..  2018.  BLIC: A Blockchain Protocol for Manufacturing and Supply Chain Management of ICS. 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :1326–1335.
Blockchain technology has brought a huge paradigm shift in multiple industries, by integrating distributed ledger, smart contracts and consensus protocol under the same roof. Notable applications of blockchain include cryptocurrencies and large-scale multi-party transaction management systems. The latter fits very well into the domain of manufacturing and supply chain management for Integrated Circuits (IC), which, despite several advanced technologies, is vulnerable to malicious practices, such as overproduction, IP piracy and deleterious design modification to gain unfair advantages. To combat these threats, researchers have proposed several ideas like hardware metering, design obfuscation, split manufacturing and watermarking. In this paper, we show, how these issues can be complementarily dealt with using blockchain technology coupled with identity-based encryption and physical unclonable functions, for improved resilience against certain adversarial motives. As part of our proposed blockchain protocol, titled `BLIC', we propose an authentication mechanism to secure both active and passive IC transactions, and a composite consensus protocol designed for IC supply chains. We also present studies on the security, scalability, privacy and anonymity of the BLIC protocol.
2020-10-16
Al-Haj, Ali, Farfoura, Mahmoud.  2019.  Providing Security for E-Government Document Images Using Digital Watermarking in the Frequency Domain. 2019 5th International Conference on Information Management (ICIM). :77—81.

Many countries around the world have realized the benefits of the e-government platform in peoples' daily life, and accordingly have already made partial implementations of the key e-government processes. However, before full implementation of all potential services can be made, governments demand the deployment of effective information security measures to ensure secrecy and privacy of their citizens. In this paper, a robust watermarking algorithm is proposed to provide copyright protection for e-government document images. The proposed algorithm utilizes two transforms: the Discrete Wavelet Transformation (DWT) and the Singular Value Decomposition (SVD). Experimental results demonstrate that the proposed e-government document images watermarking algorithm performs considerably well compared to existing relevant algorithms.

2020-10-06
Marquis, Victoria, Ho, Rebecca, Rainey, William, Kimpel, Matthew, Ghiorzi, Joseph, Cricchi, William, Bezzo, Nicola.  2018.  Toward attack-resilient state estimation and control of autonomous cyber-physical systems. 2018 Systems and Information Engineering Design Symposium (SIEDS). :70—75.

This project develops techniques to protect against sensor attacks on cyber-physical systems. Specifically, a resilient version of the Kalman filtering technique accompanied with a watermarking approach is proposed to detect cyber-attacks and estimate the correct state of the system. The defense techniques are used in conjunction and validated on two case studies: i) an unmanned ground vehicle (UGV) in which an attacker alters the reference angle and ii) a Cube Satellite (CubeSat) in which an attacker modifies the orientation of the satellite degrading its performance. Based on this work, we show that the proposed techniques in conjunction achieve better resiliency and defense capability than either technique alone against spoofing and replay attacks.

2020-07-30
Ernawan, Ferda, Kabir, Muhammad Nomani.  2018.  A blind watermarking technique using redundant wavelet transform for copyright protection. 2018 IEEE 14th International Colloquium on Signal Processing Its Applications (CSPA). :221—226.
A digital watermarking technique is an alternative method to protect the intellectual property of digital images. This paper presents a hybrid blind watermarking technique formulated by combining RDWT with SVD considering a trade-off between imperceptibility and robustness. Watermark embedding locations are determined using a modified entropy of the host image. Watermark embedding is employed by examining the orthogonal matrix U obtained from the hybrid scheme RDWT-SVD. In the proposed scheme, the watermark image in binary format is scrambled by Arnold chaotic map to provide extra security. Our scheme is tested under different types of signal processing and geometrical attacks. The test results demonstrate that the proposed scheme provides higher robustness and less distortion than other existing schemes in withstanding JPEG2000 compression, cropping, scaling and other noises.
Sengupta, Anirban, Roy, Dipanjan.  2018.  Reusable intellectual property core protection for both buyer and seller. 2018 IEEE International Conference on Consumer Electronics (ICCE). :1—3.
This paper presents a methodology for IP core protection of CE devices from both buyer's and seller's perspective. In the presented methodology, buyer fingerprint is embedded along seller watermark during architectural synthesis phase of IP core design. The buyer fingerprint is inserted during scheduling phase while seller watermark is implanted during register allocation phase of architectural synthesis process. The presented approach provides a robust mechanisms of IP core protection for both buyer and seller at zero area overhead, 1.1 % latency overhead and 0.95 % design cost overhead compared to a similar approach (that provides only protection to IP seller).
Wang, Tianhao, Kerschbaum, Florian.  2019.  Attacks on Digital Watermarks for Deep Neural Networks. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). :2622—2626.
Training deep neural networks is a computationally expensive task. Furthermore, models are often derived from proprietary datasets that have been carefully prepared and labelled. Hence, creators of deep learning models want to protect their models against intellectual property theft. However, this is not always possible, since the model may, e.g., be embedded in a mobile app for fast response times. As a countermeasure watermarks for deep neural networks have been developed that embed secret information into the model. This information can later be retrieved by the creator to prove ownership. Uchida et al. proposed the first such watermarking method. The advantage of their scheme is that it does not compromise the accuracy of the model prediction. However, in this paper we show that their technique modifies the statistical distribution of the model. Using this modification we can not only detect the presence of a watermark, but even derive its embedding length and use this information to remove the watermark by overwriting it. We show analytically that our detection algorithm follows consequentially from their embedding algorithm and propose a possible countermeasure. Our findings shall help to refine the definition of undetectability of watermarks for deep neural networks.
Deeba, Farah, Tefera, Getenet, Kun, She, Memon, Hira.  2019.  Protecting the Intellectual Properties of Digital Watermark Using Deep Neural Network. 2019 4th International Conference on Information Systems Engineering (ICISE). :91—95.

Recently in the vast advancement of Artificial Intelligence, Machine learning and Deep Neural Network (DNN) driven us to the robust applications. Such as Image processing, speech recognition, and natural language processing, DNN Algorithms has succeeded in many drawbacks; especially the trained DNN models have made easy to the researchers to produces state-of-art results. However, sharing these trained models are always a challenging task, i.e. security, and protection. We performed extensive experiments to present some analysis of watermark in DNN. We proposed a DNN model for Digital watermarking which investigate the intellectual property of Deep Neural Network, Embedding watermarks, and owner verification. This model can generate the watermarks to deal with possible attacks (fine tuning and train to embed). This approach is tested on the standard dataset. Hence this model is robust to above counter-watermark attacks. Our model accurately and instantly verifies the ownership of all the remotely expanded deep learning models without affecting the model accuracy for standard information data.

Xiao, Lijun, Huang, Weihong, Deng, Han, Xiao, Weidong.  2019.  A hardware intellectual property protection scheme based digital compression coding technology. 2019 IEEE International Conference on Smart Cloud (SmartCloud). :75—79.

This paper presents a scheme of intellectual property protection of hardware circuit based on digital compression coding technology. The aim is to solve the problem of high embedding cost and low resource utilization of IP watermarking. In this scheme, the watermark information is preprocessed by dynamic compression coding around the idle circuit of FPGA, and the free resources of the surrounding circuit are optimized that the IP watermark can get the best compression coding model while the extraction and detection of IP core watermark by activating the decoding function. The experimental results show that this method not only expands the capacity of watermark information, but also reduces the cost of watermark and improves the security and robustness of watermark algorithm.

2020-07-03
Gupta, Arpit, Kaur, Arashdeep, Dutta, Malay Kishore, Schimmel, Jiří.  2019.  Perceptually Transparent Robust Audio Watermarking Algorithm Using Multi Resolution Decomposition Cordic QR Decomposition. 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). :313—317.

This paper proposes an audio watermarking algorithm having good balance between perceptual transparency, robustness, and payload. The proposed algorithm is based on Cordic QR decomposition and multi-resolution decomposition meeting all the necessary audio watermarking design requirements. The use of Cordic QR decomposition provides good robustness and use of detailed coefficients of multi-resolution decomposition help to obtain good transparency at high payload. Also, the proposed algorithm does not require original signal or the embedded watermark for extraction. The binary data embedding capacity of the proposed algorithm is 960.4 bps and the highest SNR obtained is 35.1380 dB. The results obtained in this paper show that the proposed method has good perceptual transparency, high payload and robustness under various audio signal processing attacks.

Singh, Neha, Joshi, Sandeep, Birla, Shilpi.  2019.  Suitability of Singular Value Decomposition for Image Watermarking. 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN). :983—986.

Digital images are extensively used and exchanged through internet, which gave rise to the need of establishing authorship of images. Image watermarking has provided a solution to prevent false claims of ownership of the media. Information about the owner, generally in the form of a logo, text or image is imperceptibly hid into the subject. Many transforms have been explored by the researcher community for image watermarking. Many watermarking techniques have been developed based on Singular Value Decomposition (SVD) of images. This paper analyses Singular Value Decomposition to understand its use, ability and limitations to hide additional information into the cover image for Digital Image Watermarking application.

2020-01-20
Guha, Krishnendu, Saha, Debasri, Chakrabarti, Amlan.  2019.  Zero Knowledge Authentication for Reuse of IPs in Reconfigurable Platforms. TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON). :2040–2045.
A key challenge of the embedded era is to ensure trust in reuse of intellectual properties (IPs), which facilitates reduction of design cost and meeting of stringent marketing deadlines. Determining source of the IPs or their authenticity is a key metric to facilitate safe reuse of IPs. Though physical unclonable functions solves this problem for application specific integrated circuit (ASIC) IPs, authentication strategies for reconfigurable IPs (RIPs) or IPs of reconfigurable hardware platforms like field programmable gate arrays (FPGAs) are still in their infancy. Existing authentication techniques for RIPs that relies on verification of proof of authentication (PoA) mark embedded in the RIP by the RIP producers, leak useful clues about the PoA mark. This results in replication and implantation of the PoA mark in fake RIPs. This not only causes loss to authorized second hand RIP users, but also poses risk to the reputation of the RIP producers. We propose a zero knowledge authentication strategy for safe reusing of RIPs. The PoA of an RIP producer is kept secret and verification is carried out based on traversal times from the initial point to several intermediate points of the embedded PoA when the RIPs configure an FPGA. Such delays are user specific and cannot be replicated as these depend on intrinsic properties of the base semiconductor material of the FPGA, which is unique and never same as that of another FPGA. Experimental results validate our proposed mechanism. High strength even for low overhead ISCAS benchmarks, considered as PoA for experimentation depict the prospects of our proposed methodology.
2019-12-10
Huang, Xuping.  2018.  Mechanism and Implementation of Watermarked Sample Scanning Method for Speech Data Tampering Detection. Proceedings of the 2Nd International Workshop on Multimedia Privacy and Security. :54-60.

The integrity and reliability of speech data have been important issues to probative use. Watermarking technologies supplies an alternative solution to guarantee the the authenticity of multiple data besides digital signature. This work proposes a novel digital watermarking based on a reversible compression algorithm with sample scanning to detect tampering in time domain. In order to detect tampering precisely, the digital speech data is divided into length-fixed frames and the content-based hash information of each frame is calculated and embedded into the speech data for verification. Huffman compression algorithm is applied to each four sampling bits from least significant bit in each sample after pulse-code modulation processing to achieve low distortion and high capacity for hiding payload. Experimental experiments on audio quality, detection precision and robustness towards attacks are taken, and the results show the effectiveness of tampering detection with a precision with an error around 0.032 s for a 10 s speech clip. Distortion is imperceptible with an average 22.068 dB for Huffman-based and 24.139 dB for intDCT-based method in terms of signal-to-noise, and with an average MOS 3.478 for Huffman-based and 4.378 for intDCT-based method. The bit error rate (BER) between stego data and attacked stego data in both of time-domain and frequency domain is approximate 28.6% in average, which indicates the robustness of the proposed hiding method.

2019-11-04
Wang, Jingyuan, Xie, Peidai, Wang, Yongjun, Rong, Zelin.  2018.  A Survey of Return-Oriented Programming Attack, Defense and Its Benign Use. 2018 13th Asia Joint Conference on Information Security (AsiaJCIS). :83-88.

The return-oriented programming(ROP) attack has been a common access to exploit software vulnerabilities in the modern operating system(OS). An attacker can execute arbitrary code with the aid of ROP despite security mechanisms are involved in OS. In order to mitigate ROP attack, defense mechanisms are also drawn researchers' attention. Besides, research on the benign use of ROP become a hot spot in recent years, since ROP has a perfect resistance to static analysis, which can be adapted to hide some important code. The results in benign use also benefit from a low overhead on program size. The paper discusses the concepts of ROP attack as well as extended ROP attack in recent years. Corresponding defense mechanisms based on randomization, frequency, and control flow integrity are analyzed as well, besides, we also analyzed limitations in this defense mechanisms. Later, we discussed the benign use of ROP in steganography, code integrity verification, and software watermarking, which showed the significant promotion by adopting ROP. At the end of this paper, we looked into the development of ROP attack, the future of possible mitigation strategies and the potential for benign use.