A Dual-Channel Secure Transmission Scheme for Internet-Based Networked Control Systems

Two significant issues in Internet-based networked control systems （ INCSs）, transport performance of different protocols and security breach from Internet side, are investigated. First, for improving the performance of data transmission, user datagram protocol （UDP） is adopted as the main stand for controllers and plants using INCSs. Second, a dual-channel secure transmission scheme （DCSTS）based on data transmission characteristics of INCSs is proposed, in which a raw UDP channel and a secure TCP （transmission control protocol） connection making use of SSL/TLS （secure sockets layer/transport layer security） are included. Further, a networked control protocol （NCP） at application layer for supporting DCSTS between the controllers and plants in INCSs is designed, and it also aims at providing a universal communication mechanism for interoperability of devices among the networked control laboratories in Beijing Institute of Technology of China, Central South University of China and Tokyo University of Technology of Japan. By means of a networked single-degree-of-free- dom robot arm, an INCS under the new protocol and security environment is created. Compared with systems such as IPSec or SSL/TLS, which may cause more than 91% network throughput deduction, the new DCSTS protocol may yield results ten times better, being just 5.67%.

Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent years.The mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all things.The variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication environments.Ensuring data secure transmission is critical for mobile IIoT networks.This paper investigates the data secure transmission performance prediction of mobile IIoT networks.To cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first derived.Then,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction algorithm.For mobile signals,the important features may be removed by the pooling layers.This will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is designed.Out of the input and output layers,it removes the pooling layer and contains six convolution layers.Elman,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed algorithm.Through simulation analysis,good prediction accuracy is achieved by the CNN algorithm.The prediction accuracy obtains a 59%increase.

Enabling Efficient Data Transmission in Wireless Sensor Networks-Based IoT Application

The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.

Dynamic Spectrum Control-Assisted Secure and Efficient Transmission Scheme in Heterogeneous Cellular Networks

Heterogeneous cellular networks(HCNs)are envisioned as a promising architecture to provide seamless wireless coverage and increase network capacity.However,the densified multi-tier network architecture introduces excessive intra-and cross-tier interference and makes HCNs vulnerable to eavesdropping attacks.In this article,a dynamic spectrum control(DSC)-assisted transmission scheme is proposed for HCNs to strengthen network security and increase the network capacity.Specifically,the proposed DSC-assisted transmission scheme leverages the idea of block cryptography to generate sequence families,which represent the transmission decisions,by performing iterative and orthogonal sequence transformations.Based on the sequence families,multiple users can dynamically occupy different frequency slots for data transmission simultaneously.In addition,the collision probability of the data transmission is analyzed,which results in closed-form expressions of the reliable transmission probability and the secrecy probability.Then,the upper and lower bounds of network capacity are further derived with given requirements on the reliable and secure transmission probabilities.Simulation results demonstrate that the proposed DSC-assisted scheme can outperform the benchmark scheme in terms of security performance.Finally,the impacts of key factors in the proposed DSC-assisted scheme on the network capacity and security are evaluated and discussed.

Dual-Threshold Based Secure On-Off Transmission Scheme for Dense HCNs with Imperfect CSI

In this paper, we propose a dual-threshold based secure On-Off transmission scheme, where signals are transmitted only if the channel condition can guarantee secure and reliable communication. First, we present a dynamic access strategy to increase access efficiency, which provides an access region for the intended user. Then, we propose an emission control policy to transmit signals according to the current channel condition, which declines the influence of channel estimation errors and guarantees qualities of communication links. Furthermore, we give a comprehensive performance analysis for the proposed scheme in terms of connection outage probability(COP) and secrecy outage probability(SOP), and present a dual-threshold optimization model to further support the performance. Numerical results verify that the secure On-Off transmission scheme can increase the system secure energy efficiency and guarantee reliable and secure communication.

A Quantum Key Re-Transmission Mechanism for QKD-Based Optical Networks

Due to the vulnerability of fibers in optical networks, physical- layer attacks targeting photon splitting, such as eavesdrop- ping, can potentially lead to large information and revenue loss. To enhance the existing security approaches of optical networks, a new promising technology, quantum key distribu- tion （QKD）, can securely encrypt services in optical networks, which has been a hotspot of research in recent years for its characteristic that can let clients know whether infomlation transmission has been eavesdropped or not. In this paper, we apply QKD to provide secret keys for optical networks and then introduce the architecture of QKD based optical net- work. As for the secret keys generated by QKD in optical net- works, we propose a re-transmission mechanism by analyzing the security risks in QKD-based optical networks. Numerical results indicate that the proposed re-transmission mechanism can provide strong protection degree with enhanced attack protection. Finally, we illustrated some future challenges in QKD-based optical networks.

Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

SecureGuard-Solaris环境下VPN的设计与实现

1引言VPN(Virtual Private Network)具体实现是采用隧道技术,将企业网的数据封装在隧道中进行传输.因此,VPN技术的复杂性首先建立在隧道协议复杂性的基础之上.隧道协议中最为典型的有CRE、IPSec、L2TP、PPTP、L2F等.其中GRE、IPSEC属于第三层隧道协议,L2TP、PPTP、L2F属于第二层隧道协议.第二层隧道和第三层隧道的本质区别在于用户的IP数据包是被封装在何种数据包中在隧道中传输的.

Data Stream Subspace Clustering for Anomalous Network Packet Detection

As the Internet offers increased connectivity between human beings, it has fallen prey to malicious users who exploit its resources to gain illegal access to critical information. In an effort to protect computer networks from external attacks, two common types of Intrusion Detection Systems (IDSs) are often deployed. The first type is signature-based IDSs which can detect intrusions efficiently by scanning network packets and comparing them with human-generated signatures describing previously-observed attacks. The second type is anomaly-based IDSs able to detect new attacks through modeling normal network traffic without the need for a human expert. Despite this advantage, anomaly-based IDSs are limited by a high false-alarm rate and difficulty detecting network attacks attempting to blend in with normal traffic. In this study, we propose a StreamPreDeCon anomaly-based IDS. StreamPreDeCon is an extension of the preference subspace clustering algorithm PreDeCon designed to resolve some of the challenges associated with anomalous packet detection. Using network packets extracted from the first week of the DARPA '99 intrusion detection evaluation dataset combined with Generic Http, Shellcode and CLET attacks, our IDS achieved 94.4% sensitivity and 0.726% false positives in a best case scenario. To measure the overall effectiveness of the IDS, the average sensitivity and false positive rates were calculated for both the maximum sensitivity and the minimum false positive rate. With the maximum sensitivity, the IDS had 80% sensitivity and 9% false positives on average. The IDS also averaged 63% sensitivity with a 0.4% false positive rate when the minimal number of false positives is needed. These rates are an improvement on results found in a previous study as the sensitivity rate in general increased while the false positive rate decreased.

A Data Driven Security Correction Method for Power Systems with UPFC

The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.

Chaotic Pigeon Inspired Optimization Technique for Clustered Wireless Sensor Networks

Wireless Sensor Networks(WSN)interlink numerous Sensor Nodes(SN)to support Internet of Things(loT)services.But the data gathered from SNs can be divulged,tempered,and forged.Conventional WSN data processes manage the data in a centralized format at terminal gadgets.These devices are prone to attacks and the security of systems can get compromised.Blockchain is a distributed and decentralized technique that has the ability to handle security issues in WSN.The security issues include transactions that may be copied and spread across numerous nodes in a peer-peer network system.This breaches the mutual trust and allows data immutability which in turn permits the network to go on.At some instances,few nodes die or get compromised due to heavy power utilization.The current article develops an Energy Aware Chaotic Pigeon Inspired Optimization based Clustering scheme for Blockchain assisted WSN technique abbreviated as EACPIO-CB technique.The primary objective of the proposed EACPIO-CB model is to proficiently group the sensor nodes into clusters and exploit Blockchain(BC)for inter-cluster communication in the network.To select ClusterHeads(CHs)and organize the clusters,the presented EACPIO-CB model designs a fitness function that involves distinct input parameters.Further,BC technology enables the communication between one CH and the other and with the Base Station(BS)in the network.The authors conducted comprehensive set of simulations and the outcomes were investigated under different aspects.The simulation results confirmed the better performance of EACPIO-CB method over recent methodologies.

Effective and Extensive Virtual Private Network

A Virtual Private Network (VPN) allows the provisioning of private network services for an organization over a public network such as the Internet. In other words a VPN can transform the characteristics of a public which may be non-secure network into those of a private secure network through using encrypted tunnels. This work customized a standard VPN to a newly one called EEVPN (Effective Extensive VPN). It transmits a small data size in through a web based system in a reasonable time without affecting the security level. The proposed EEVPN is more effective where it takes small data transmission time with achieving high level of security. Also, the proposed EEVPN is more extensive because it is not built for a specific environment.

基于电网线路传输安全的电力市场分布式交易模型研究

电力市场分布式交易模型可有效缓解传统集中模型下市场主体的隐私安全等问题,但难以在保障市场主体收益和电力系统安全稳定运行的同时,实现社会福利最大化.因此,基于电网线路传输安全,首先以社会福利最大化为目标,构建集中式交易模型,并采用拉格朗日乘子法和对偶定理,将其等价分解为各市场主体自身利益最大化的分布式交易模型.在此基础上,设计2种适用于不同情形的分布式交易方法及其求解算法,并构造电网安全成本影响市场主体的决策,从而保证电网线路传输安全.最后,基于算例分析,验证了2种交易方法的有效性.

基于SIR模型的无线网络安全威胁态势量化评估算法

为确保网络安全,及时掌控安全状况,以易感者、感染者和免疫者(SIR:Susceptible Infected Recovered)模型为基础,面向无线网络提出安全威胁态势量化评估算法。选取资产价值性,系统脆弱性与威胁性作为量化评估指标,分别根据信息资产的安全属性与主机劣势的Agent检测值,得到价值性量化值与脆弱性量化值。基于病毒的传播特性,改进SIR模型,分析病毒传播特征,获得威胁性量化值。结合3个指标量化值,建立无线网络安全威胁态势的量化评估算法,用所得态势值评估网络安全状况。测试结果表明,该方法评估出的主机与整个无线网络的安全威胁态势值均与期望值高度拟合,且评估时间更短。所提算法具备良好的评估准确性与实时性,能为网络安全状况分析提供有效的数据依据,及时给予管理员可靠的决策支持。

基于局部差分隐私的通信网络敏感数据安全传输控制

当前通信网络敏感数据安全传输控制方法存在节点布设合理性不佳,传输控制效率较低,控制配准度较低等问题.为此,提出基于局部差分隐私的通信网络敏感数据安全传输控制方法.依据实际的传输控制需求,设定初始传输控制指标;采用多阶方式,提升整体的传输控制效率,利用局部差分隐私方法对多阶传输控制节点进行部署,并计算控制可信度,构建通信网络敏感数据传输控制模型,采用自适应通频对传输控制结果进行修正,实现传输控制处理.实验结果表明,设计方法的敏感数据传输控制配准度均可达70%,说明此种方法对数据传输质量较高,针对性更强,传输控制效果更佳,具有实际的应用价值.

面向AI安全的深度伪造视频检测技术

针对实际应用伪造类型多样化,而检测过程中只检测单一伪造数据类型等问题,提出了一种新的数据预处理方法,解决了视频中运动图像容易连续重叠的问题;针对人脸模糊伪造,侧面人脸伪造和遮挡人脸伪造问题,利用小卷积核代替大卷积核的方法训练出自己的Deeper网络;针对帧插入、帧复制、帧修改、帧内篡改四种常见的深度视频伪造,尤其是在测试领域差距较大的情况下,容易产生泛化性不足的问题,设计了一种改进的基于双流分析的深度伪造视频检测模型。

电力通信网络敏感信息传输路由安全优化设计

优化电力通信网络敏感信息传输节点选取过程,可避免链路拥挤,高消耗的传输能量导致簇首分布不合理的问题。因此,为了提高敏感信息传输安全性和网络覆盖率,设计电力通信网络敏感信息传输路由安全优化方案。结合PageRank算法迭代更新连接节点,构建路由连接函数,综合考虑节点负荷容量和等级选取节点。构建路由安全优化协议整体框架,依据链路ETX值改善电力通信网络中能量损耗。计算目标节点分布概率密度,设计路由优化数据分发机制,实现敏感信息传输路由安全优化。由实验结果可知,所设计方法簇1、2、3、4的簇首中心坐标分别为(-1,2)、(1,1.8)、(0.95,-2.2)、(-1,-2),与实际簇首所在中心一致;最高网络覆盖率为96%,有效提高了网络连接安全性。

变拓扑结构下无线网络节点数据同态加密传输算法设计

由于无线网络在传输过程中,节点拓扑结构处于变化过程中,很容易被攻击,导致网络在数据传输过程中,被恶意攻击发生数据泄露。提出基于同态加密的无线网络节点数据安全传输算法。利用信道损耗模型确定无线网络的变化拓扑结构。通过遍历网络节点规划出数据的最优动态传输路径。在按照规划路径进行数据传输的过程中,设计一种同态加密算法对传感数据加密,实现无线网络节点数据的安全传输。实验结果表明:在不同类型的网络攻击下,设计数据传输技术的丢包率仅0.6%,证实了该技术可以保障无线网络节点数据的传输安全。

云计算背景下通信网络安全传输控制技术的研究

随着云计算技术的快速普及和应用,该技术已成为信息技术领域的重要发展方向之一。在云计算背景下,大量数据和信息需要通过网络进行传输和访问,而传统的网络安全控制技术已经不能完全满足云计算环境下的安全需求,因此需要加强对通信网络安全传输控制技术的研究。文章简要分析了通信网络安全传输控制技术的核心和通信网络安全遭受的威胁,并从加强通信网络安全传输控制的重要性出发,提出通信网络安全传输控制技术的具体要点和应用策略。

视频监控数据跨域安全共享传输控制系统设计与实现

随着视频监控网络技术的不断发展,实现监控数据的跨域传输十分必要,视频监控网络的流数据在跨域传输中对传输的速率与数据安全提出了较高要求,因此如何实现视频监控数据的跨域安全共享传输成为高性能安全传输领域的研究重点。针对这一需求,文章设计了视频监控数据跨域安全共享传输控制系统,结合PF_RING零拷贝模型、信道任务管理、单向光传输机制等相关技术,从硬件和软件两个方面论证实现视频流数据的高性能跨域安全传输与共享的方法,并通过实验证明设计系统的可行性与科学性,以确保视频监控数据跨域传输的安全性与效率。