Embedding Security Research Articles

Information Embedding in Additively Manufactured Parts Through Printing Speed Control

Abstract Information lithography in manufacturing is a broad set of techniques for encoding sequences of bits as physical or behavioral features in physical parts. It is an effective approach for part traceability and anti-counterfeiting. Several techniques have recently been proposed for embedding 2D codes in 3D printed parts by local control of geometry or material. This paper presents an approach to embed and retrieve information in additive manufacturing (AM) parts by controlling the printing process parameters. The approach leverages variations in printing speed to encode information on the surface of AM parts. Optical imaging devices, such as 2D scanners and optical profilometers, are employed to read the embedded information, enabling the capture of local height differences on the part surfaces that embody 2D codes such as QR codes. The retrieved information is processed using computer vision techniques such as morphological segmentation and binary classification. First, the impact of variations in the encoding parameters on the information retrieval accuracy is characterized. Then, the feasibility and effectiveness of the proposed scheme are demonstrated through experimental results, showcasing a high accuracy in retrieving encoded messages and successfully distinguishing subtle surface features resulting from varying printing speeds. The proposed approach offers an inexpensive and efficient method for information lithography, allowing for the secure embedding of information, e.g., serial numbers and watermarks, while addressing counterfeiting and security concerns in diverse industries.

Embedding security into ferroelectric FET array via in situ memory operation

Non-volatile memories (NVMs) have the potential to reshape next-generation memory systems because of their promising properties of near-zero leakage power consumption, high density and non-volatility. However, NVMs also face critical security threats that exploit the non-volatile property. Compared to volatile memory, the capability of retaining data even after power down makes NVM more vulnerable. Existing solutions to address the security issues of NVMs are mainly based on Advanced Encryption Standard (AES), which incurs significant performance and power overhead. In this paper, we propose a lightweight memory encryption/decryption scheme by exploiting in-situ memory operations with negligible overhead. To validate the feasibility of the encryption/decryption scheme, device-level and array-level experiments are performed using ferroelectric field effect transistor (FeFET) as an example NVM without loss of generality. Besides, a comprehensive evaluation is performed on a 128 × 128 FeFET AND-type memory array in terms of area, latency, power and throughput. Compared with the AES-based scheme, our scheme shows ~22.6×/~14.1× increase in encryption/decryption throughput with negligible power penalty. Furthermore, we evaluate the performance of our scheme over the AES-based scheme when deploying different neural network workloads. Our scheme yields significant latency reduction by 90% on average for encryption and decryption processes.

Leaving the Business Security Burden to LiSEA: A Low-Intervention Security Embedding Architecture for Business APIs

In the evolving landscape of complex business ecosystems and their digital platforms, an increasing number of business Application Programming Interfaces (APIs) are encountering challenges in ensuring optimal authorization control. This challenge arises due to factors such as programming errors, improper configurations, and sub-optimal business processes. While security departments have exhibited proficiency in identifying vulnerabilities and mitigating certain viral or adversarial incursions, the safeguarding of comprehensive business processes remains an intricate task. This paper introduces a novel paradigm, denoted as the Low-Intervention Security Embedding Architecture (LiSEA), which empowers business applications to enhance the security of their processes through judicious intervention within business APIs. By strategically incorporating pre- and post-intervention checkpoints, we devise a finely grained access control model that meticulously assesses both the intent of incoming business requests and the outcomes of corresponding responses. Importantly, these advancements are seamlessly integrated into the existing business codebase. Our implementation demonstrates the effectiveness of LiSEA, as it adeptly addresses eight out of the ten critical vulnerabilities enumerated in the OWASP API Security Top 10. Notably, when the number of threads is less than 200, LiSEA brings less than 20 msec of latency to the business process, which is significantly less than the microservice security agent based on the API gateway.

An Overview of Computer Operating Systems and Emerging Trends

This article presents an overview of computer operating systems (OS) and emerging trends. OS is simply defined as an interface between computer hardware and the user. The objective of the study is to investigate the emerging trends of OS and to find out the direction of OS for modern computing systems. To achieve this goal the paper looks at the concepts of OS, its underlying architectures and evolution. The papers also outline the components of the OS provide knowledge on security issues with OS architectures and provide best practices to secure OS. The paper found out that the current trends in OS include IoT OS, Cloud OS, AI-powered OS, Blockchain OS, Hybrid OS and Container OS. The paper compares the strengths and weaknesses of the major OS. The Paper proposes a double-layer security approach where the OS is hardened with security policies and embedding security protocols in the Hardware architecture of the OS. It was discovered that every technology comes with its unique architecture and OS. This makes it worrisome for engineers to crack their brains to develop such a system. The paper further proposes the development of a universal OS for all architectures leaving room for further expansion while mitigating power consumption issues by incorporating green computing technology in the design architecture.

An RGB Color Image Steganography Scheme by Binary Lower Triangular Matrix

Steganography is an area where researchers focus on how to develop novel hiding techniques that are aided by the mathematical or computational model. In order to conceal the secret bits in a cover image, the imperceptible property and embedding payload capacity must be maintained. In most of the developed methods, some selective least significant bits (LSBs) of each pixel of the cover image is modified to hide the data which may lead to substantial distortion in the stego-image especially when the payload size is large. Therefore, to attain the trade-off between payload capacity and image quality, the authors have devised a binary lower triangular matrix-based secret message embedding process in which data can be hidden in the color pixel. In this secret message embedding process, the secret data is embedded aided by the binary lower triangular matrix. The formulated mathematical model for the secret message embedding process has ensured a secure embedding technique with reduced aberration on the stego-image. The proposed steganography scheme is preserving significant visual quality while emphasizing the security aspect by adopting an indirect data-hiding mechanism in contrast to the conventional mechanism. Furthermore, for the betterment of the visual properties of the stego-image, we have generically extended the formulation and tested it to check the visual quality. The empirical results of the proposed steganography scheme depict outcomes satisfactorily for the RGB color images. Researchers can explore and apply this novel data-hiding scheme in different data communication applications.

Enhancing image steganography via adversarial optimization of the stego distribution

Adversarial steganography aims to fool steganalysis models and enhance embedding security. Its application in the sequential min-max steganographic game has recently shown state-of-the-art embedding security. However, current methods suffer from high computational costs and inferior convergence. These issues could be caused by unnecessary optimization on distortions and the monotonous criterion for adversaries. This paper introduces a novel and concise scheme for conducting adversarial steganography and refines the criterion for adversaries. The suggested adversarial optimizations leave out distortions and focus on optimizing the stego distribution, whose difference with the intrinsic cover distribution is the primary factor affecting embedding security. These optimization techniques are accomplished by utilizing gradient descent on embedding modification probabilities and introducing a novel protocol for cover enhancement. Moreover, the proposed criteria for adversaries prioritize enhancing the similarity between each cover-stego pair, rather than evading steganalysis models, to break monotony and enhance convergence. The discussion and refinement of the loss function and termination setting of the optimization process are also provided. The proposed method demonstrates its benefits in increased security and computation efficiency in experiments. After collaborating with the steganographic min-max game, the state-of-the-art embedding security and stronger resistance to various and unexpected steganalysis models are seen.

DevSecOps in AWS: Embedding security into the heart of DevOps practices

In today's digital landscape, rapid software development and deployment are critical for organizational success. However, security concerns have become a significant challenge in the DevOps environment. DevSecOps, which integrates security practices within the DevOps workflow, has emerged as a solution to address this gap. This paper focuses on the implementation of DevSecOps in AWS, emphasizing how security can be embedded into DevOps processes. The study explores methodologies used to integrate security within cloud-based applications, highlights the challenges and benefits of adopting DevSecOps in AWS, and provides recommendations for improving security integration in development processes.

Increase Security of Image Encryption Depends on Change Pixel Location

In any communication, security is the most important issue in today’s world. The information security has be come one of the most signify can tproblemsin data communication. Lots of datasecurity and data hiding algorithmshavebeendevelopedinthelastdecade. Cryptography and steganography are the two major techniques for secret communication. In this paper, the secret text is first encryptedbyusingAESwhichhasverygood performanceandisamostpowerfultechnique. Now this encrypted text is embedded using steganography. Our proposed system gives threestages of security for secret. The main aim of proposed method to increase security of embedding and extraction phase using AESencryption,steganography and change pixel location. In order to evaluate performance the proposed algorithm performs series of tests. These tests include, PSNR and MSE.

A Review and Analysis of Attack Vectors on MIL-STD-1553 Communication Bus

MIL-STD-1553 has been used for the past four decades by the military as a standardized, reliable, and fault-tolerant communication bus to provide connectivity between different embedded components in mission-critical military vehicles. The bus was designed with a great focus on reliability, responsiveness, and fault tolerance. However, its security aspects were an afterthought. Indeed, in the early 1970s, the notion of cyberattacks was not ubiquitous as it is today. Attacking computerized systems located at very high altitudes was an inconceivable scenario for many people, including security engineers. With current developments in cybersecurity and telecommunication networks, the security analysis of the MIL-STD-1553 bus reveals that the system is not immune from cyberattacks. The bus is vulnerable to many attacks that could seriously damage the entire system. Rebuilding the security of MIL-STD-1553 from scratch is cost prohibitive and a very complex, not scalable, and inflexible approach. A common alternative to embedding security to the existing system is the development of an intrusion detection system that can be added to the MIL-STD-1553 bus with minimal cost. In this article, we review and discuss some possible attack vectors on the MIL-STD-1553 bus. Then, we analyze the risk and consequences of each attack vector on a fighter jet. This review and analysis will provide security engineers with a holistic overview of possible attacks and their related risk on MIL-STD-1553 to better design an effective intrusion detection system.

On-Farm Data Security: Practical Recommendations for Securing Farm Data

The growth in the use of Information and Communications Technology (ICT) and Artificial intelligence (AI) has improved the productivity and efficiency of modern agriculture, which is commonly referred to as precision farming. Precision farming solutions are dependent on collecting a large amount of data from farms. Despite the many advantages of precision farming, security threats are a major challenge that is continuously on the rise and can harm various stakeholders in the agricultural system. These security issues may result in security breaches that could lead to unauthorized access to farmers' confidential data, identity theft, reputation loss, financial loss, or disruption to the food supply chain. Security breaches can occur because of an intentional or unintentional actions or incidents. Research suggests that humans play a key role in causing security breaches due to errors or system vulnerabilities. Farming is no different from other sectors. There is a growing need to protect data and IT assets on farms by raising awareness, promoting security best practices and standards, and embedding security practices into the systems. This paper provides recommendations for farmers on how they can mitigate potential security threats in precision farming. These recommendations are categorized into human-centric solutions, technology-based solutions, and physical aspect solutions. The paper also provides recommendations for Agriculture Technology Providers (ATPs) on best practices that can mitigate security risks.

A Large Payload Data Hiding Scheme Using Scalable Secret Reference Matrix

When imperceptibility is an issue, data-hiding techniques typically become limited to small payloads. In this paper, a novel data-hiding scheme is proposed that allows embedding large payloads while maintaining high stego-image quality. The scheme utilizes an N×N sub-block for constructing a reference matrix as a secret key that allows the symmetric embedding and extraction of secret data from a grayscale cover image, where N is a positive integer greater than or equal to two. With proper modification, the proposed method can be directly converted to a symmetric cryptosystem. For cases with acceptable stego-image quality (i.e., PSNR > 34), the experimental results showed that the proposed method can embed, on average, four bits per pixel (bpp), a higher hiding capacity than in previous works, and also offers the ability to adjust the capacity by varying N. The number of solutions for a sub-block reaches the factorial of N2, guaranteeing the security of data embedding and extraction. In addition, the proposed method has low computational complexity and can be implemented in a straightforward manner.

Improving the Security of Reversible Data Hiding Using Multiple Histogram Modification

Reversible data hiding (RDH) allows carrying secret information in cover media without introducing permanent distortion. For a RDH method, the important performance measurements are embedding capacity and image quality. Since embedding capacity is an important requirement in the field of data hiding, it is necessary to consider the security of data embedding in RDH applications. In general, RDH algorithms usually prefer data embedding in simple image regions with low local complexity. As a result, image degradation is alleviated at the cost of poor embedding security. In this study, a novel RDH method is proposed to embed data into complex image regions, wherein the data hiding becomes more secure in defending against modern steganalysis. To measure regional local complexity, the harmonic mean of directional local variances is employed to combine directional pixel differences. To embed data into complex regions instead of smooth regions, multiple histogram modification is adopted and updated for optimized data embedding with higher complexity. Experiment results show that embedding security is significantly improved with a considerable amount of payload and well-preserved image quality.

Visually meaningful image encryption based on universal embedding model

Visually meaningful image encryption (VMIE) means that a plain image can be encrypted into a visually meaningful cipher image (VMCI), which makes the secret more imperceptible than noise-like cipher images. Here, we first present a universal embedding model (UEM) and further present a new UEM-based VMIE algorithm. The plain image is pre-encrypted and then embedded into the integer wavelet subbands of the host image in a dynamic way. In order to avoid the overflow, a threshold limiting function is used to modify the range of pixel values of the host image. To adapt different types of wavelet transform subbands, a UEM is proposed to be used to embed the secret information domain into the host domain. Moreover, in the embedding process, a four-dimensional discrete chaotic system is used to ensure the security of embedding. The numbers of embedded bits in the four embedded domains can be adjusted flexibly. A traversal algorithm is designed to find the optimal numbers of embedded bits for different types of wavelet transform in order to achieve an optimal visual quality of cipher images. A matrix-bit-depth-conversion algorithm is designed where a large matrix with low bit depth can be transformed into a small matrix with high bit depth to meet the input requirements of UEM, which means that the size of the plain image is not limited to a quarter of the size of the host image. Simulation results and performance comparisons show that the proposed VMIE algorithm can achieve a better visual quality than existing VMIE algorithms.

Coded Caching in the Presence of a Wire and a Cache Tapping Adversary of Type II

This paper introduces the notion of cache-tapping into the information theoretic models of coded caching. The wiretap channel II in the presence of multiple receivers equipped with fixed-size cache memories, and an adversary which selects symbols to tap into from cache placement and/or delivery is introduced. The legitimate terminals know neither whether placement, delivery, or both are tapped, nor the positions in which they are tapped. Only the size of the overall tapped set is known. For two receivers and two files, the strong secrecy capacity- the maximum achievable file rate while keeping the overall library strongly secure- is identified. Lower and upper bounds on the strong secrecy file rate are derived when the library has more than two files. Achievability relies on a code design which combines wiretap coding, security embedding codes, one-time pad keys, and coded caching. A genie-aided upper bound, in which the transmitter is provided with user demands before placement, establishes the converse for the two-files case. For more than two files, the upper bound is constructed by three successive channel transformations. Our results establish provable security guarantees against a powerful adversary which optimizes its tapping over both phases of communication in a cache-aided system.

An Automatic Cost Learning Framework for Image Steganography Using Deep Reinforcement Learning

Automatic cost learning for steganography based on deep neural networks is receiving increasing attention. Steganographic methods under such a framework have been shown to achieve better security performance than methods adopting hand-crafted costs. However, they still exhibit some limitations that prevent a full exploitation of their potentiality, including using a function-approximated neural-network-based embedding simulator and a coarse-grained optimization objective without explicitly using pixel-wise information. In this article, we propose a new embedding cost learning framework called SPAR-RL (Steganographic Pixel-wise Actions and Rewards with Reinforcement Learning) that overcomes the above limitations. In SPAR-RL, an agent utilizes a policy network which decomposes the embedding process into pixel-wise actions and aims at maximizing the total rewards from a simulated steganalytic environment, while the environment employs an environment network for pixel-wise reward assignment. A sampling process is utilized to emulate the message embedding of an optimal embedding simulator. Through the iterative interactions between the agent and the environment, the policy network learns a secure embedding policy which can be converted into pixel-wise embedding costs for practical message embedding. Experimental results demonstrate that the proposed framework achieves state-of-the-art security performance against various modern steganalyzers, and outperforms existing cost learning frameworks with regard to learning stability and efficiency.

Two level data encoding approach for reversible data hiding in dual Stego images

Due to high embedding capacity and security, dual stego-image based data hiding has become so popular. This paper proposes a two-level data encoding approach for reversible data hiding in dual stego-images. In the first level of encoding, the encoded intensities are estimated from the message intensities by assigning lower intensities to higher histogram data and higher intensities to lower histogram data. In the second level of encoding, the encoded intensities are folded by identifying the negative values to obtain the folded intensities. The folded intensities are embedded in the cover image to obtain the dual stego-images. The two-level data encoding process reduces the intensity of secret data which increases the quality of the two stego-images. During the extraction process, the folded intensities are extracted from the dual stego images. The folded intensities are decoded to encoded intensities and then to message intensities to obtain the secret data. This two-level data encoding approach increases the peak signal to noise ratio (PSNR) around 2 dB, and embedding rate (bpp) by 1%when compared to the traditional data hiding approach in dual stego images.

Research on Region Selection Strategy for Visible Watermark Embedding

ABSTRACT Visible watermarking is one of the most direct and effective copyright protection methods for digital images and videos, but it faces the problems of easy detection of watermarking location and watermarking removal attacks. It requires that the visible watermarking not only can not affect visual quality of original digital products but also can resist accidental editing and malicious attacks. In this paper, an adaptive region selection method for visible watermark embedding is proposed. First, an improved region selection method based on the model of saliency-based visual attention (MSVA) is used to more accurately distinguish salient and non-salient regions of host image; then, the non-salient regions of image are divided into sub-blocks to calculate texture complexity respectively; finally, a moderate image block is selected as the embedding region of visible watermark image according to the distribution of image texture complexity. The experimental results show that the proposed method can identify saliency regions more accurately, thus ensuring that the important contents of host image will not be occluded. The adaptive selection of embedding region based on image complexity not only ensures the recognizability and aesthetics of visible watermark embedding effect but also takes into account the security of watermark embedding, and especially reduces the risk of batch removal attacks.

A New Kind of High Capacity and Security Reversible Data Hiding Scheme

A novel high capacity and security reversible data hiding scheme is proposed in this article, in which the secret data is represented by different orthogonal spreading sequences and repeatedly embedded into the cover image without disturbing each other in the light of Code Division Multiple Access (CDMA) technique, and thus the embedding capacity is enlarged. As most elements of orthogonal spreading sequences are mutually canceled in the process of repeated embedding, it keeps the distortion of the embedded image at a low level even with high embedding capacity. Moreover, only the receiver who has the spreading sequence and the embedding gain factor the same as the sender can extract the secret data and achieve the original image exactly, thus the proposed scheme achieves high embedding security than other schemes. The results of the experiment demonstrates that the CDMA based reversible data hiding scheme could achieve higher image quality at moderate-to-high embedding capacity compared with other state-of-the-art schemes.

Visual IoT Security: Data Hiding in AMBTC Images Using Block-Wise Embedding Strategy.

This study investigates combining the property of human vision system and a 2-phase data hiding strategy to improve the visual quality of data-embedded compressed images. The visual Internet of Things (IoT) is indispensable in smart cities, where different sources of visual data are collected for more efficient management. With the transmission through the public network, security issue becomes critical. Moreover, for the sake of increasing transmission efficiency, image compression is widely used. In order to respond to both needs, we present a novel data hiding scheme for image compression with Absolute Moment Block Truncation Coding (AMBTC). Embedding secure data in digital images has broad security uses, e.g., image authentication, prevention of forgery attacks, and intellectual property protection. The proposed method embeds data into an AMBTC block by two phases. In the intra-block embedding phase, a hidden function is proposed, where the five AMBTC parameters are extracted and manipulated to embed the secret data. In the inter-block embedding phase, the relevance of high mean and low mean values between adjacent blocks are exploited to embed additional secret data in a reversible way. Between these two embedding phases, a halftoning scheme called direct binary search is integrated to efficiently improve the image quality without changing the fixed parameters. The modulo operator is used for data extraction. The advantages of this study contain two aspects. First, data hiding is an essential area of research for increasing the IoT security. Second, hiding in compressed images instead of original images can improve the network transmission efficiency. The experimental results demonstrate the effectiveness and superiority of the proposed method.

A novel image steganography technique based on quantum substitution boxes

Substitution boxes play an essential role in designing secure cryptosystems. With the evolution of quantum technologies, current data security mechanisms may be broken due to their construction based on mathematical computation. Quantum walks, a universal quantum computational model, play an essential role in designing quantum algorithms. We utilize the benefits of quantum walks to present a novel technique for constructing substitution boxes (S-boxes) based on quantum walks (QWs). The performance of the presented QWs S-box technique is evaluated by S-box evaluation criteria, and our results prove that the constructed S-box has vital qualities for viable applications in security purposes. Furthermore, a new technique for image steganography is constructed. The proposed technique is an integrated mechanism between classical data hiding and quantum walks to achieve better security for the embedded data. The embedding and extraction procedures are controlled by QWs S-box. The inclusion of cryptographic QWs S-box ensures the security of both embedding and extraction phases. At the extraction phase, only the stego image and the secret values are needed for constructing the secret data. Experimental results demonstrate that the presented technique has a high-security, high embedding capacity and good visual quality.