基于无线传感器网络的混合混沌新分组加密算法

针对无线传感器网络(WSNS)中节点配备的能源少、节点计算能力低、存储资源 有限以及传统的加密方法不适用于WSNS中等问题, 提出了一种新的基于动态迭代的混合混沌方程及其整型数值化方法, 并结合Feistel网络结构设计了一种快速、安全且资源消耗低的适用于WSNS节点的分组加密算法. 通过对混合混沌分组加密算法进行了大量的实验测试之后, 发现该算法具有密钥空间大、严格的雪崩效应、扩散及扰乱性高以及均等的统计平衡性等优点, 同时该算法还成功地通过了SP800-22的严格测试; 算法经过仿真器平台上运行的速度、时间及所占存储空间的测试分析, 结果表明设计的混合混沌分组加密算法是完全能够适用于WSNS节点的数据加密.     

A Resiliency-Connectivity metric in wireless sensor networks with key predistribution schemes and node compromise attacks

Applications for wireless sensor networks require widespread, highly reliable communications even in the face of adversarial influences. Maintaining connectivity and secure communications between entities are vital networking properties towards ensuring the successful and accurate completion of desired sensing tasks. We examine the required communication range for nodes in a wireless sensor network with respect to several parameters. Network properties such as key predistribution schemes and node compromise attacks are modelled with several network parameters and studied in terms of how they influence global network connectivity. These networks are physically vulnerable to malicious behavior by way of node compromise attacks that may affect global connectivity. We introduce a metric that determines the resilience of a network employing a key predistribution scheme with respect to node compromise attacks. In this work,we provide the first study of global network connectivity and its relationship to node compromise attacks. Existing work considers the relationship between the probability of node compromise and the probability of link compromise and the relationship of the probability of secure link establishment and overall network connectivity for the Erdős network model. Here, we present novel work which combines these two relationships to study the relationship between node compromise attacks and global network connectivity. Our analysis is performed with regard to large-scale networks; however, we provide simulation results for both large-scale and small-scale networks. First, we derive a single expression to determine the required communication radius for wireless sensor networks to include the effects of key predistribution schemes. From this, we derive an expression for determining required communication range after an adversary has compromised a fraction of the nodes in the network. The required communication range represents the resource usage of nodes in a network to cope with key distribution schemes and node compromise attacks. We introduce the Resiliency-Connectivity metric, which measures the resilience of a network in expending its resources to provide global connectivity in adverse situations.     

A new image cipher in time and frequency domains

Recently, various encryption techniques based on chaos have been proposed. However, most existing chaotic encryption schemes still suffer from fundamental problems such as small key space, weak security function and slow performance speed. This paper introduces an efficient encryption scheme for still visual data that overcome these disadvantages. The proposed scheme is based on hybrid Linear Feedback Shift Register (LFSR) and chaotic systems in hybrid domains. The core idea is to scramble the pixel positions based on 2D chaotic systems in frequency domain. Then, the diffusion is done on the scrambled image based on cryptographic primitive operations and the incorporation of LFSR and chaotic systems as round keys. The hybrid compound of LFSR, chaotic system and cryptographic primitive operations strengthen the encryption performance and enlarge the key space required to resist the brute force attacks. Results of statistical and differential analysis show that the proposed algorithm has high security for secure digital images. Furthermore, it has key sensitivity together with a large key space and is very fast compared to other competitive algorithms.     

Blind estimation of number of motion multi-human targets in wireless pyroelectric infrared sensor networks

Due to the features of low energy consumption and flexible networking, nowadays the pyroelectric sensor has been applied widely in areas such as network instruction detection or human body target tracking recognition. Moreover, accurate estimation and judgment about the number of human targets moving in the networks is the foundation of tracking and recognition. This paper, under the condition of being lack of relevant prior knowledge, presents a novel method which selects the maximum likelihood function of the Bayesian network models as the independent criterion. In addition, the objective function is optimally solved by the Laplace estimation. The results of numerous experiments on both simulation and hardware experimental platforms are shown that this method has capability to blindly estimate the number of motion multiple human targets in wireless pyroelectric infrared sensor networks.     

Non-Linear Hopped Chaos Parameters-Based Image Encryption Algorithm Using Histogram Equalization

Multimedia wireless communications have rapidly developed over the years. Accordingly, an increasing demand for more secured media transmission is required to protect multimedia contents. Image encryption schemes have been proposed over the years, but the most secure and reliable schemes are those based on chaotic maps, due to the intrinsic features in such kinds of multimedia contents regarding the pixels’ high correlation and data handling capabilities. The novel proposed encryption algorithm introduced in this article is based on a 3D hopping chaotic map instead of fixed chaotic logistic maps. The non-linearity behavior of the proposed algorithm, in terms of both position permutation and value transformation, results in a more secured encryption algorithm due to its non-convergence, non-periodicity, and sensitivity to the applied initial conditions. Several statistical and analytical tests such as entropy, correlation, key sensitivity, key space, peak signal-to-noise ratio, noise attacks, number of pixels changing rate (NPCR), unified average change intensity randomness (UACI), and others tests were applied to measure the strength of the proposed encryption scheme. The obtained results prove that the proposed scheme is very robust against different cryptography attacks compared to similar encryption schemes.     

无线视频传感阵列低复杂度多视点视频编码方案

基于网络中心节点的运动矢量外推技术,提出了一种无线视频传感阵列的低复杂度多视点视频编码方法。该方法考虑到密集型视频传感阵列各视点间通信复杂、布线繁重、且位于各相机节点内的编码器由于计算能力、功耗等限制难以完成复杂的编码过程等特点,利用运动矢量外推逼近技术将大量的运动估计运算从视频编码端移到了网络中心节点,使得新编解码框架下编码器的运动估计的计算复杂度只有传统全搜索运动估计运算的0.3%,降低了系统传感阵列编码端功耗。实验结果表明,该方法的率失真性能比H.264-I帧高出4 dB以上,接近H.264-P帧编码,优于基于Wyner-Ziv理论的分布式多视点视频编码方法。     

A novel chaos-based bit-level permutation scheme for digital image encryption

Confidentiality is an important issue when digital images are transmitted over public networks, and encryption is the most useful technique employed for this purpose. Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional algorithms. Recently, chaos-based encryption has suggested a new and efficient way to deal with the intractable problems of fast and highly secure image encryption. This paper proposes a novel chaos-based bit-level permutation scheme for secure and efficient image cipher. To overcome the drawbacks of conventional permutation-only type image cipher, the proposed scheme introduced a significant diffusion effect in permutation procedure through a two-stage bit-level shuffling algorithm. The two-stage permutation operations are realized by chaotic sequence sorting algorithm and Arnold Cat map, respectively. Results of various types of analysis are interesting and indicate that the security level of the new scheme is competitive with that of permutation-diffusion type image cipher, while the computational complexity is much lower. Therefore the new scheme is a good candidate for real-time secure image communication applications.     

Single Neuronal Dynamical System in Self-Feedbacked Hopfield Networks and Its Application in Image Encryption

Image encryption is a confidential strategy to keep the information in digital images from being leaked. Due to excellent chaotic dynamic behavior, self-feedbacked Hopfield networks have been used to design image ciphers. However, Self-feedbacked Hopfield networks have complex structures, large computational amount and fixed parameters; these properties limit the application of them. In this paper, a single neuronal dynamical system in self-feedbacked Hopfield network is unveiled. The discrete form of single neuronal dynamical system is derived from a self-feedbacked Hopfield network. Chaotic performance evaluation indicates that the system has good complexity, high sensitivity, and a large chaotic parameter range. The system is also incorporated into a framework to improve its chaotic performance. The result shows the system is well adapted to this type of framework, which means that there is a lot of room for improvement in the system. To investigate its applications in image encryption, an image encryption scheme is then designed. Simulation results and security analysis indicate that the proposed scheme is highly resistant to various attacks and competitive with some exiting schemes.     

Adaptive multimode transmission in wireless sensor networks with energy harvesting

Limited energy has always been an important factor restricting the development of wireless sensor networks. The unbalanced energy consumption of nodes will accelerate the death of some nodes. To solve the above problems, an adaptive routing algorithm for energy collection sensor networks based on distributed energy saving clustering (DEEC) is proposed. In each hop of data transmission, the optimal mode is adaptively selected from four transmission modes: single-hop cooperative, multi-hop cooperative, single-hop non-cooperative and multi-hop non-cooperative, so as to reduce and balance the energy consumption of nodes. The performance of the proposed adaptive multi-mode transmission method and several benchmark schemes are evaluated and compared by computer simulation, where a few performance metrics such as the network lifetime and throughput are adopted. The results show that, the proposed method can effectively reduce the energy consumption of the network and prolong the network lifetime; it is superior to various benchmark schemes.     

基于CC2530的无线温度传感器网络的设计

传统的有线温度测量由于线路复杂常存在造价昂贵、信噪比低等问题,为解决这些弊端,设计了一种基于 CC2530和 ZigBee 协议的无线温度传感器网络,硬件结构非常简单,更有利于狭小空间下的温度监测。该系统使用DS18B20数字温度传感器对环境进行温度测量;以射频芯片CC2530为核心,使用其标准的增强型8051 CPU对数据进行处理与控制;使用ZigBee协议建立无线通信网络,将测得的环境温度通过LCD显示。最后,通过实验测试证明该系统可以有效地测量不同地点的温度并无线组网,能够实现低功耗、高精度、远距离的无线传输。     

A novel image encryption scheme based on improved hyperchaotic sequences

This paper proposes a novel image encryption scheme based on the improved hyperchaotic sequences. Firstly, the hyperchaotic sequences are modified to generate chaotic key stream that is more suitable for image encryption. Secondly, the final encryption key stream is generated by correlating the chaotic key stream and plaintext which result in both key sensitivity and plaintext sensitivity. The scheme can achieve high key sensitivity and high plaintext sensitivity through only two rounds diffusion operation. The performance test and security analysis has been performed using the histograms, correlation coefficients, information entropy, peak signal-to-noise ratio, key sensitivity analysis, differential analysis, key space analysis, decryption quality and speed analysis. Results suggest that the proposed image encryption scheme is secure and reliable, with high potential to be adopted for the secure image communication applications.     

Relay selection scheme based on deep reinforcement learning in wireless sensor networks

Cooperative communication technology has realized the enhancement in the wireless communication system’s spectrum utilization rate without resorting to any additional equipment; additionally, it ensures system reliability in transmission, increasingly becoming a research focus within the sphere of wireless sensor networks (WSNs). Since the selection of relay is crucial to cooperative communication technology, this paper proposes two different relay selection schemes subject to deep reinforcement learning (DRL), in response to the issues in WSNs with relay selection in cooperative communications, which can be summarized as the Deep-Q-Network Based Relay Selection Scheme (DQN-RSS), as well as the Proximal Policy Optimization Based Relay Selection Scheme (PPO-RSS); it further compared the commonly used Q-learning relay selection scheme (Q-RSS) with random relay selection scheme. First, the cooperative communication process in WSNs is modeled as a Markov decision process, and DRL algorithm is trained in accordance with the outage probability, as well as mutual information (MI). Under the condition of unknown instantaneous channel state information (CSI), the best relay is adaptively selected from multiple candidate relays. Thereafter, in view of the slow convergence speed of Q-RSS in high-dimensional state space, the DRL algorithm is used to accelerate the convergence. In particular, we employ DRL algorithm to deal with high-dimensional state space while speeding up learning. The experimental results reveal that under the same conditions, the random relay selection scheme always has the worst performance. And compared to Q-RSS, the two relay selection schemes designed in this paper greatly reduce the number of iterations and speed up the convergence speed, thereby reducing the computational complexity and overhead of the source node selecting the best relay strategy. In addition, the two relay selection schemes designed and raised in this paper are featured by lower-level outage probability with lower-level energy consumption and larger system capacity. In particular, PPO-RSS has higher reliability and practicability.     

A novel image block cryptosystem based ona spatiotemporal chaotic system and a chaotic neural network

In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network (CNN). The employed CNN comprises a 4-neuron layer called a chaotic neuron layer (CNL), where the spatiotemporal chaotic system participates in generating its weight matrix and other parameters. The spatiotemporal chaotic system used in our scheme is the typical coupled map lattice (CML), which can be easily implemented in parallel by hardware. A 160-bit-long binary sequence is used to generate the initial conditions of the CML. The decryption process is symmetric relative to the encryption process. Theoretical analysis and experimental results prove that the block cryptosystem is secure and practical, and suitable for image encryption.     

Chaotic encryption and decryption of JPEG image

According to encrypting principles of digital images, integrating the characteristic of JPEG image, and using discrete chaotic sequence, this paper has studied encryption and decryption of JPEG image, and has compared and analyzed the corresponding relations between the encryption and decryption effects and their security of two different encrypting schemes of the JPEG image chaotic encryption studied by this paper. In a basic unit of an 8 × 8 data block, image encryption and decryption not only are fast, but also match with JPEG format. The JPEG image encryption can meet the security requirement of the storage and transmission of JPEG images in some common application occasions, and provides an effective and feasible way of encrypting JPEG images.     

微小型无线光电传感网络的实验系统设计

基于nRF905低功耗、高灵敏度无线收发的一体芯片实现了一种微小型无线光电传感网络实验系统。讨论了实验系统的硬件节点、网络通信协议及软件的设计。实验结果表明,在19.2kbit/s速率下,系统中任意两节点可实现30m(室内)至150m(室外空旷地带)范围内的无线通信。该系统具有硬件设计简单、软件及其协议编程方便等优点,可微型化、低成本的应用于无线光电传感器网络系统。     

Lightweight secure image encryption scheme based on chaotic differential equation

The ultimate secure choice for block cryptosystem until now is advanced encryption standard (AES). It is very difficult to implement AES for the constrained situations such as sensor networks, image encryption and RFID tags. In this article, a chaotic oscillator generated by a second order differential equation is used to produce confusion and diffusion in the plaintext message to achieve the desired secrecy. The produced chaotic sequence of random numbers from dynamical system is utilized to scramble the pixels of an image to obtain an encrypted image. Chaos based encryption technique is found secure enough to tackle chosen plaintext attacks and brute force attacks. The specific attributes of chaotic system like, sensitivity to initial conditions, randomness and uncertainty make it suitable for the design of cryptosystem. The dominance of the proposed scheme is acknowledged due to the fact of better cryptographic properties when compared with the algorithms already developed in the literature.     

事件驱动的无线传感器网络嵌入式操作系统研究

针对无线传感器网络节点能量敏感和多任务的特点,提出了基于事件驱动的嵌入式实时操作系统;采用分层结构的设计思想,构建模块化的系统组件,利用内存控制块链表,实现简易高效的内存管理;基于事件驱动和任务优先级,实现系统低功耗和抢占式的任务调度;实验结果表明,系统功耗低,实时性好。     

A New Algorithm for Digital Image Encryption Based on Chaos Theory

In recent decades, image encryption, as one of the significant information security fields, has attracted many researchers and scientists. However, several studies have been performed with different methods, and novel and useful algorithms have been suggested to improve secure image encryption schemes. Nowadays, chaotic methods have been found in diverse fields, such as the design of cryptosystems and image encryption. Chaotic methods-based digital image encryptions are a novel image encryption method. This technique uses random chaos sequences for encrypting images, and it is a highly-secured and fast method for image encryption. Limited accuracy is one of the disadvantages of this technique. This paper researches the chaos sequence and wavelet transform value to find gaps. Thus, a novel technique was proposed for digital image encryption and improved previous algorithms. The technique is run in MATLAB, and a comparison is made in terms of various performance metrics such as the Number of Pixels Change Rate (NPCR), Peak Signal to Noise Ratio (PSNR), Correlation coefficient, and Unified Average Changing Intensity (UACI). The simulation and theoretical analysis indicate the proposed scheme’s effectiveness and show that this technique is a suitable choice for actual image encryption.     

A novel chaotic image encryption algorithm based on water wave motion and water drop diffusion models

This paper will put forward a novel chaotic image encryption algorithm with confusion–diffusion architecture. First of all, secret keys will be processed by key generator before they can really be used in the encryption scheme, and in this stage this paper associates plain image with secret keys; Secondly, by imitating the trajectory of water wave movement, encryption algorithm will do scrambling operations to the image. Thirdly, this paper combines water drop motion and dynamic look up table to realize diffusion operations. For an 8 bits pixel, this algorithm will just dispose the higher 4 bits, which is because the higher 4 bits contain the vast majority of information of the image. At last, the experiment results and security analysis show that this proposed algorithm has a desirable encryption effect. Its key space is large enough, it is sensitive to keys and plain image, its encryption speed is fast and it can resist cryptanalysis such as brute attack, differential attack, etc.     

一种基于势博弈的无线传感器网络拓扑控制算法

在实际的应用中,无线传感器网络常常由大量电池资源有限的传感器节点组成.如何降低网络功耗,最大化网络生存时间,是传感器网络拓扑控制技术的重要研究目标.随着传感节点的运行,节点的能量分布可能越来越不均衡,需要在考虑该因素的情况下,动态地调整节点的网络负载以均衡节点的能耗,达到延长网络生存时间的目的.该文引入博弈理论和势博弈的概念,综合考虑节点的剩余能量和节点发射功率等因素,设计了一种基于势博弈的拓扑控制模型,并证明了该模型纳什均衡的存在性.通过构造兼顾节点连通性和能耗均衡性的收益函数,以确保降低节点功耗的同时维持网络的连通性.通过提高邻居节点的平均剩余能量值以实现将剩余能量多的节点选择作为自身的邻居节点,提高节点能耗的均衡性.在此基础上,提出了一种分布式的能耗均衡拓扑控制算法.理论分析证明了该算法能保持网络的连通性.与现有基于博弈理论的DIA算法和MLPT算法相比,本算法形成的拓扑负载较重、剩余能量较小的瓶颈节点数量较少,节点剩余能量的方差较小,网络生存时间更长.