Enhancing visual security: An image encryption scheme based on parallel compressive sensing and edge detection embedding

A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.

EG-STC: An Efficient Secure Two-Party Computation Scheme Based on Embedded GPU for Artificial Intelligence Systems

This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.

CL2ES-KDBC:A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.

The Anti-Piracy Measure Using Encryption of Embedded Products May Mitigate the Security Strength

In this paper, firstly we describe the piracy problem of embedded products. Then we formulate the security features of anti-piracy embedded products. Finally we prove that the anti-piracy measure using encryption of embedded products may mitigate the security strength.

Design Pattern Representation for Safety-Critical Embedded Systems

Design Patterns, which give abstract solutions to commonly recurring design problems, have been widely used in the software and hardware domain. As non-functional requirements are an important aspect in the design of safety-critical embedded systems, this work focuses on the integration of non-functional implications in an existing design pattern concept. We propose a pattern representation for safety-critical embedded application design methods by including fields for the implications and side effects of the represented design pattern on the non-functional requirements of the overall systems. The considered requirements include safety, reliability, modifiability, cost, and execution time.

Security-Aware Periodic-Write Scheduling for Mission-Critical Embedded Storage System

High quality of security and guaranteed real-time requirements are two key goals of mission- critical embedded storage systems. But most existing real-time disk scheduling algorithms do not consider improving security performance of disk requests. A security-aware periodic-write （SAPW） scheduling algorithm is proposed to judiciously select appropriate security level for each disk request to maximize security value of N periodic disk users, while without sacrificing timing constraint of each user. Simulation results show the significant effectiveness of SAPW algorithm, and the average security improvement is up to 223.6% over other three algorithms.

Secure encryption embedded processor design for wireless sensor network application

This paper presents a new encryption embedded processor aimed at the application requirement of wireless sensor network （WSN）. The new encryption embedded processor not only offers Rivest Shamir Adlemen （RSA）, Advanced Encryption Standard （AES）, 3 Data Encryption Standard （3 DES） and Secure Hash Algorithm 1 （SHA - 1 ） security engines, but also involves a new memory encryption scheme. The new memory encryption scheme is implemented by a memory encryption cache （MEC）, which protects the confidentiality of the memory by AES encryption. The experi- ments show that the new secure design only causes 1.9% additional delay on the critical path and cuts 25.7% power consumption when the processor writes data back. The new processor balances the performance overhead, the power consumption and the security and fully meets the wireless sensor environment requirement. After physical design, the new encryption embedded processor has been successfully tape-out.

Embedded TLS 1.2 Implementation for Smart Metering & Smart Grid Applications

Digital networked communications are the key to all Internet-of-things applications, but especially to smart metering systems and the smart grid. In order to ensure a safe operation of systems and the privacy of users, the transport layer security （TLS） protocol, a mature and well standardized solution for secure communications, may be used. We implemented the TLS protocol in its latest version in a way suitable for embedded and resource-constrained systems. This paper outlines the challenges and opportunities of deploying TLS in smart metering and smart grid applications and presents performance results of our TLS implementation. Our analysis shows that given an appropriate implementation and configuration, deploying TLS in constrained smart metering systems is possible with acceptable overhead.

A Multilayer Security Framework for Cloud Computing in Internet of Things (IoT) Domain

Cloud computing is a type of emerging computing technology that relies on shared computing resources rather than having local servers or personal devices to handle applications. It is an emerging technology that provides services over the internet: Utilizing the online services of different software. Many works have been carried out and various security frameworks relating to the security issues of cloud computing have been proposed in numerous ways. But they do not propose a quantitative approach to analyze and evaluate privacy and security in cloud computing systems. In this research, we try to introduce top security concerns of cloud computing systems, analyze the threats and propose some countermeasures for them. We use a quantitative security risk assessment model to present a multilayer security framework for the solution of the security threats of cloud computing systems. For evaluating the performance of the proposed security framework we have utilized an Own-Cloud platform using a 64-bit quad-core processor based embedded system. Own-Cloud platform is quite literally as any analytics, machine learning algorithms or signal processing techniques can be implemented using the vast variety of Python libraries built for those purposes. In addition, we have proposed two algorithms, which have been deployed in the Own-Cloud for mitigating the attacks and threats to cloud-like reply attacks, DoS/DDoS, back door attacks, Zombie, etc. Moreover, unbalanced RSA based encryption is used to reduce the risk of authentication and authorization. This framework is able to mitigate the targeted attacks satisfactorily.

Concepts of Safety Critical Systems Unification Approach &Security Assurance Process

The security assurance of computer-based systems that rely on safety and security assurance, such as consistency, durability, efficiency and accessibility, require or need resources. This targets the System-of-Systems (SoS) problems with the exception of difficulties and concerns that apply similarly to subsystem interactions on a single system and system-as-component interactions on a large information system. This research addresses security and information assurance for safety-critical systems, where security and safety are addressed before going to actual implementation/development phase for component-based systems. For this purpose, require a conceptual idea or strategy that deals with the application logic security assurance issues. This may explore the vulnerability in single component or a reuse of specification in existing logic in component-based system. Keeping in view this situation, we have defined seven concepts of security assurance and security assurance design strategy for safety-critical systems.

Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

With the widespread use of the internet,there is an increasing need to ensure the security and privacy of transmitted data.This has led to an intensified focus on the study of video steganography,which is a technique that hides data within a video cover to avoid detection.The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency.This paper proposes a new method to video steganography,which involves utilizing a Genetic Algorithm(GA)for identifying the Region of Interest(ROI)in the cover video.The ROI is the area in the video that is the most suitable for data embedding.The secret data is encrypted using the Advanced Encryption Standard(AES),which is a widely accepted encryption standard,before being embedded into the cover video,utilizing up to 10%of the cover video.This process ensures the security and confidentiality of the embedded data.The performance metrics for assessing the proposed method are the Peak Signalto-Noise Ratio(PSNR)and the encoding and decoding time.The results show that the proposed method has a high embedding capacity and efficiency,with a PSNR ranging between 64 and 75 dBs,which indicates that the embedded data is almost indistinguishable from the original video.Additionally,the method can encode and decode data quickly,making it efficient for real-time applications.

基于TEE的机载嵌入式数据安全技术研究

针对机载嵌入式系统实时性要求高、硬件资源受限、数据与任务安全防护薄弱的特点,对基于可信执行环境(TEE)的机载嵌入式数据安全技术展开研究。安全加固防护的对象为机载嵌入式系统中数据全生命周期的3个阶段,即数据存储、数据传输和数据使用的全过程。基于TEE环境特有的数据隔离特性,所提算法将数据存储中的加密算法、数据传输中的签名验签程序、数据使用过程中的敏感数据和敏感应用等与通用执行环境隔离起来,保证了不同任务之间能安全可靠地处理关键数据,并对其中用到的加密算法进行精简,在硬件资源受限的前提下保证了较好的实时性。仿真结果证明,所提算法安全性高,可靠性强,较以往方法效率更优化。

基于STM32的智能安防报警系统设计

该文设计一款STM32的智能安防报警系统。系统以STM32F103C8T6芯片为控制系统,利用烟雾检测传感器、火焰传感器、温湿度传感器检测室内的实时情况,通过OLED显示器显示室内实时监控信息,同时利用ESP8266WiFi模块将检测到的信息实时发送到手机APP上,使得用户能够在连接WiFi时实时接收到室内的相关信息。在系统检测到室内环境出现异常时,能够激发蜂鸣器响应发生警报。根据现行安防报警系统的市场要求,在未来,便宜、功能可靠丰富的安防报警系统将会受到人们的青睐,其所使用的技术或者功能并不需要特别尖端或者深奥,但是其功能和作用应当是做到值得用户的信赖。

基于函数调用指令特征分析的固件指令集架构识别方法

不同的固件常采用不同的指令集架构,固件指令集架构的识别是对嵌入式固件进行逆向分析和漏洞挖掘的基础。现有研究和相关工具在针对特定类型的嵌入式设备固件指令集架构识别时存在识别正确率低、误报率高的情况。针对上述问题,提出了一种基于函数调用指令特征分析的固件指令集架构识别方法,通过同时利用指令中操作码和操作数所包含的信息识别目标固件中的函数调用指令,将其作为关键特征实现对不同指令集架构的分类,并基于该方法开发了原型系统EDFIR(Embedded Device Firmware Instruction set Recognizer)。实验结果表明,相比IDAPro,Ghidra,Radare2,Binwalk以及ISAdetect这些当前应用最广泛和最新的工作,该方法具有更高的识别正确率、更低的误报率并具备更强的抗干扰能力,其对1000个真实设备固件的识别正确率高达97.9%,比目前识别效果最好的ISAdetect提升了42.5%。此外,相关实验还证明,即使将分析规模缩小至完整固件的1/50,所提方法仍能保持95.31%的识别正确率,具有良好的识别性能。

Secure Digital Card(SD卡)与LPC2210的接口设计

本文基于一款ARM7芯片LPC2210实现对SD卡数据存储,并使用RAM作为数据的暂存区,当达到一个块的大小即512字节时,一次存入SD卡。首先对SD卡的特点作了简单的介绍,然后从接口设计和软件两个方面予以说明。

嵌入式软件安全性测试研究

安全性测试作为一种常见的测试类型,在嵌入式软件测试中发挥着重要作用,可以有效保证嵌入式软件稳定、安全运行。本文对常见的安全性测试要点和测试方法进行研究和介绍,为软件开发人员和测试人员提供参考。

嵌入式软件安全性测试技术方法分析

本文以嵌入式软件安全性测试技术方法为重点展开分析,对嵌入式软件发展历程和特点进行简述,在此基础上研究其安全性测试的要求、方法,包括故障模型分析法、故障树分析法等。以故障模型分析法为例,就嵌入式软件安全性测试的流程进行论述,分析系统功能描述和定位、潜在安全问题评估、安全问题破坏性评估、风险监控等重点环节实践方式,为未来嵌入式软件安全性测试工作提供参考。

基于OPC技术的电力监控系统网络安全风险预警研究

为了从技术管理方面提高电力监控系统的安全性,避免发生无意与恶意破坏事件,面向电力监控系统的实时数据信息存储与处理,提出将用于过程控制的对象连接与嵌入(Object Linking and Embedding for Process Control,OPC)技术用于网络安全风险预警。概述设计所用的OPC服务器结构,设计基于OPC技术的电力监控系统,结合防火墙与入侵侦测技术,提高整个电力监控系统的安全管理水平,提取正常时隙预警信息为正常样本。结果发现,基于OPC技术的电力监控系统安全预警,在准确度方面具有优越性,证实了设计的基于OPC技术的电力监控系统在电力日常监管工作中的安全适用性。

Research on Embedding Capacity and Efficiency of Information Hiding Based on Digital Images

Generally speaking, being an efficient information hiding scheme, what we want to achieve is high embedding capacity of the cover image and high visual quality of the stego image, high visual quality is also called embedding efficiency. This paper mainly studies on the information hiding technology based on gray-scale digital images and especially considers the improvement of embedding capacity and embedding efficiency. For the purpose of that, two algorithms for information hiding were proposed, one is called high capacity of information hiding algorithm (HCIH for short), which achieves high embedding rate, and the other is called high quality of information hiding algorithm (HQIH for short), which realizes high embedding efficiency. The simulation experiments show that our proposed algorithms achieve better performance.

Transmission network expansion planning with embedded constraints of short circuit currents and N-1 security

An approach of transmission network expan-sion planning with embedded constraints of short circuit currents and N-1 security is proposed in this paper.The problem brought on by the strong nonlinearity property of short circuit currents is solved with a linearization method based on the DC power flow.The model can be converted to a mixed-integer linear programming problem,realizing the optimization of planning model that considers the constraints of linearized short circuit currents and N-1 security.To compensate the error caused by the assump-tions of DC power flow,the compensation factor is pro-posed.With this factor,an iterative algorithm that can compensate the linearization error is then presented.The case study based on the IEEE 118-bus system shows that the proposed model and approach can be utilized to:opti-mize the construction strategy of transmission lines;ensure the N-1 security of the network;and effectively limit the short circuit currents of the system.