Efficient Protocol-Proving Algorithm Based on Improved Authentication Tests

A new efficient protocol-proving algorithm was proposed for verifying security protocols. This algorithm is based on the improved authentication tests model, which enhances the original model by formalizing the message reply attack. With exact causal dependency relations between messages in this model, the protocol-proving algorithm can avoid the state explosion caused by asynchronous. In order to get the straight proof of security protocols, three authentication theorems are exploited for evaluating the agreement and distinction properties. When the algorithm terminates, it outputs either the proof results or the potential flaws of the security protocol. The experiment shows that the protocol-proving algorithm can detect the type flaw attack on Neuman-Stubblebine protocol, and prove the correctness of NSL protocol by exploring only 10 states.

TESLA-Based Authentication for BeiDou Civil Navigation Message

Due to the civil BeiDou navigation system is open,unauthenticated,and non-encrypted,civilian BeiDou navigation signals may have great security loopholes during transmission or reception.The main security loophole here is spoofing attacks.Spoofing attacks make the positioning or timing results of BeiDou civilian receivers wrong.Such errors may cause a series of security problems,which lays a serious hidden danger for Bei-Dou satellite information security.This article proposes an anti-spoofing method for BeiDou navigation system based on the combination of SM commercial cryptographic algorithm and Timed Efficient Stream Loss-tolerant Authentication(TESLA)for spoofing attacks.In this solution,we use the SM3 algorithm to generate a TESLA key chain with time information,and then use the key in the key chain to generate the message authentication code for the BeiDou D2 navigation message.The message authentication code is inserted into a reserved bit of the D2 navigation message.In addition,this solution uses the SM2 algorithm to protect and encrypt time information in the TESLA key chain to prevent key replay attacks in TESLA.The experimental results tested on the experimental platform built in this paper show that this scheme reduces the possibility of the BeiDou navigation system being deceived and enhances the safety of the BeiDou navigation system.

Fingerprint Recognition on Various Authentication Sensors

Fingerprint is a very popular and an ancient biometric technology to uniquely identify a person. In this paper, a fingerprint matcher is proposed which uses the global and local adaptive binarization and global minutia features. The fingerprint data is collected using three different authentication devices based on optical sensors. The experimental results are compared with the National Institute of Standards and Technology （NIST） Bozorth algorithm and various authentication fingerprint sensors. The accuracy of the proposed algorithm has been improved significantly compared with that of the NIST Bozorth algorithm.

MULTI-BLOCK CHAINING-BASED AUTHENTICATION MODE

A fast authentication mode based on Multi-Block Chaining (MBC) is put forward; and its security is proved. The MBC mode is for new generation block cipher algorithms. Its speed is about 13% faster than that of the authentication modes in common use (for example, cipher block chaining-message authentication code mode). The dependence test results meet the requirement. The MBC mode is complete; its degree of ava-lanche effect is about 0.9993; its degree of strict avalanche criterion is 0.992 or so. The frequency test results indicate that the output generated by the MBC mode has uniformity. The binary matrix rank test results imply that it is linear independent among disjoint sub-matrices of the output. Maurer’s universal statistical test results show that the output could be significantly compressed without loss of information. Run test, spectral test, non-overlapping template matching test, overlapping template matching test, Lempel-Ziv compression test, linear complexity test, serial test, approximate entropy test, cumulative sums test, random excursions test and random excursions variant test results fulfill the requirements of all. Therefore the MBC mode has good pseudo-randomness. Thus the security of MBC mode is verified by the way of statistical evaluation.

Biometric Finger Vein Recognition Using Evolutionary Algorithm with Deep Learning

In recent years,the demand for biometric-based human recog-nition methods has drastically increased to meet the privacy and security requirements.Palm prints,palm veins,finger veins,fingerprints,hand veins and other anatomic and behavioral features are utilized in the development of different biometric recognition techniques.Amongst the available biometric recognition techniques,Finger Vein Recognition(FVR)is a general technique that analyzes the patterns of finger veins to authenticate the individuals.Deep Learning(DL)-based techniques have gained immense attention in the recent years,since it accomplishes excellent outcomes in various challenging domains such as computer vision,speech detection and Natural Language Processing(NLP).This technique is a natural fit to overcome the ever-increasing biomet-ric detection problems and cell phone authentication issues in airport security techniques.The current study presents an Automated Biometric Finger Vein Recognition using Evolutionary Algorithm with Deep Learning(ABFVR-EADL)model.The presented ABFVR-EADL model aims to accomplish bio-metric recognition using the patterns of the finger veins.Initially,the presented ABFVR-EADL model employs the histogram equalization technique to pre-process the input images.For feature extraction,the Salp Swarm Algorithm(SSA)with Densely-connected Networks(DenseNet-201)model is exploited,showing the proposed method’s novelty.Finally,the Deep-Stacked Denoising Autoencoder(DSAE)is utilized for biometric recognition.The proposed ABFVR-EADL method was experimentally validated using the benchmark databases,and the outcomes confirmed the productive performance of the proposed ABFVR-EADL model over other DL models.

Security Test Case Prioritization through Ant Colony Optimization Algorithm

Security testing is a critical concern for organizations worldwide due to the potential financial setbacks and damage to reputation caused by insecure software systems.One of the challenges in software security testing is test case prioritization,which aims to reduce redundancy in fault occurrences when executing test suites.By effectively applying test case prioritization,both the time and cost required for developing secure software can be reduced.This paper proposes a test case prioritization technique based on the Ant Colony Optimization(ACO)algorithm,a metaheuristic approach.The performance of the ACO-based technique is evaluated using the Average Percentage of Fault Detection(APFD)metric,comparing it with traditional techniques.It has been applied to a Mobile Payment Wallet application to validate the proposed approach.The results demonstrate that the proposed technique outperforms the traditional techniques in terms of the APFD metric.The ACO-based technique achieves an APFD of approximately 76%,two percent higher than the second-best optimal ordering technique.These findings suggest that metaheuristic-based prioritization techniques can effectively identify the best test cases,saving time and improving software security overall.

改进PBFT算法的配电物联网接入认证方法

随着物联网与配电网深度融合,海量终端设备接入系统给配电物联网安全稳定运行带来巨大挑战。针对传统身份认证方式过于中心化且无法承载大规模终端等现状,设计一种基于区块链共识机制的配电物联网终端接入认证方法。由配电物联网网关负责对待接入终端节点登记注册,采用共识算法进行分布式认证,将合法终端上链存储。在传统PBFT算法的基础上,设计了配电物联网终端共识算法。该算法引入权重机制,根据终端节点权重选取认证节点,缩小共识规模;引入可验证随机函数增强主节点安全,避免启动视图切换协议,提高共识效率;结合实际应用场景优化一致性协议,降低通信开销。实验分析表明该方法可有效规避多种网络攻击,通信开销和吞吐量优于其他方法,系统抗攻击性较强,满足配电物联网对认证效率和系统可靠性等要求。

多维动态网络的密钥认证数学建模与仿真

多维动态网络在密钥认证过程中,若加密的密钥安全程度较低,则会被量子计算机解码,使传输的隐私数据出现泄露。为有效提升密钥的安全认证效果,提出量子攻击下多维动态网络密钥认证数学建模方法。方法建立用于多维动态网络的密钥认证模型,在建立的认证模型中,对网络中待传输数据实施冗余清洗,并使用高级加密标准(Advanced Encryption Standard,AES)算法生成密钥对待传输数据初次加密;添加一串噪声数据在加密数据中,并对其二次加密,进一步提升数据的抗量子攻击性能,建立多维动态网络的安全密钥传输模型,完成密钥的安全传输。根据解密方法结合密钥对数据安全解密,完成多维动态网络密钥的安全认证。实验结果表明,利用上述方法开展网络密钥认证时,加解密时间短,认证准确率在85%以上,且抗量子攻击能力强。

基于对称加密算法的嵌入式物联网终端访问认证方法

目前常规的嵌入式物联网终端认证方法主要通过对认证节点进行权重分配,实现认证节点安全等级分类,由于对认证请求命令的加密程度较弱,导致方法的安全性较差。对此,提出基于对称加密算法的嵌入式物联网终端访问认证方法。调整安全认证网络覆盖扩展机制,对认证网络拓扑结构进行优化;并采用对称加密算法生成密钥,对密钥系数进行优化调整,对终端访问接入信息进行认证。在实验中,对提出的方法进行了认证安全性的检验。经实验结果表明,采用提出的方法对进行终端访问认证时,认证方法被成功攻击的概率明显降低,具备较为理想的认证安全性。

拉曼光谱结合光谱特征区间筛选算法快速定量鉴别植物调和油品质

本研究提出了一种基于拉曼光谱与光谱特征区间筛选算法实现植物调和油中高价值植物油含量快速定量检测的方法。首先,将粒子群优化(particle swarm optimization,PSO)算法与灰狼优化(grey wolf optimization,GWO)算法融合构建混合智能优化算法,即PSOGWO算法。其次,将PSOGWO与组合移动窗口(combined moving window,CMW)策略结合构建新型的拉曼光谱特征区间筛选算法,即PSOGWO-CMW算法。然后,将玉米油(corn oil,CO)和特级初榨橄榄油(extra virgin olive oil,EVOO)以不同比例配制为CO-EVOO植物调和油,并采集其拉曼光谱。将拉曼光谱输入偏最小二乘回归、PSO-CMW、GWO-CMW和PSOGWO-CMW模型预测EVOO含量,并比较建模效果。结果表明,PSOGWO-CMW模型具有最佳的预测性能。采用本方法与气相色谱-质谱法分别检测真实的CO-EVOO植物调和油样本中EVOO含量,结果表明两者的检测性能无显著差异。本方法快速、准确,亦可用于其他植物调和油中高价值植物油含量的快速定量检测。

基于多生物特征感知的身份识别方法研究

随着现代社会信息技术的快速发展,用户身份认证技术在人们生活中所扮演的角色越来越重要。而生物识别技术由于其唯一性、不可复制性和无需记忆等特点已经成为最有潜力、应用最广泛的一种信息安全技术。单生物识别技术由于使用生物特征单一、收集数据易受到环境影响等原因,在实际应用中很难发挥其优势,而使用多种生物特征进行用户身份识别的方法,能够方便、快捷、安全地解决用户身份识别问题。

基于区块链的低能耗学位学历认证管理

学历、学位造假是目前就业市场的一种乱象,传统的学历学位认证系统则存在数据易被篡改、易丢失等风险.为此,本文结合区块链技术设计了一个可溯源、可监管的学位学历认证管理框架.为了解决传统区块链系统共识时存在认证时间过长、资源消耗过大的问题,提出了一种新型基于信任的低能耗权益证明算法ToS(trust of stake).以此为契机,使用以太坊框架开发了一款基于ToS底层共识的学位学历认证管理系统,实现了学位信息录入、查询、认证和撤销等主要功能.实验结果表明:该系统能够确保信息的可认证和可溯源管理,具备执行效率高、能耗低、不易受篡改和攻击等优点.

基于ECC算法的安全芯片增强双向匿名认证方法

为了解决现有芯片认证方案中,双向通信协议的合法性与唯一性无法保证,导致信息无法完整传输的问题,提出了基于ECC算法的安全芯片增强双向匿名认证方法。设计芯片安全增强结构,计算用户、权威机构密钥,验证传输信息可靠性,以此保证会话密钥分配的安全性。由发送端芯片A向接收端芯片B发送证书,实现证书交换。发送端芯片A根据一定概率推断出接收端芯片B的身份,结合字符实现双向隐匿。设计双向“挑战—应答”机制,根据响应协议,保证了双向通信协议合法性与唯一性,以及信息的完整传输。由实验结果可知,所研究方法在重放攻击情况下能完整传输信息,在口令猜测攻击情况下丢失了[2,7]、[4,5]、[5,5]、[6,6]位置的信息,不能完整传输。

语音实验室端到端即时通信认证协议设计

为保证语音实验室端到端即时通信安全,确保语音内容不被窃听和篡改,提出一种基于混合加解密的语音实验室端到端即时通信认证协议的设计方法。利用RSA方法加解密发送方传输的即时通信会话密钥,通过3DES方法将发送方发送的明文语音信息进行加解密。在加解密过程中,加密信息打包为加密包后发送至信息接收方,信息接收方获取加密包后,使用RSA方法、3DES方法进行有效的密钥解密认证、明文语音消息解密,获取语音实验室端到端的明文语音信息。实验结果显示,此协议使用下,语音实验室端到端即时通信的认证加速比提升,且仅在密钥输入内容准确的情况下,信息接收方才可得到准确的明文语音消息内容,且不存在内容失真问题。

基于Grain v1的认证加密算法研究与设计

Grain v1算法为eSTREAM项目面向硬件的优胜算法之一,在硬件实现方面极具优势。本文针对Grain v1的结构弱点对其进行细节修改,并在此基础上提出Grain v1+AE和Grain v1+AEAD两种认证加密算法。这两种算法在保证机密性和完整性的同时,为Grain系列认证加密算法在安全等级、硬件规模角度提供更多选择,拓展Grain系列算法适用范围。

基于国密算法的MQTT安全机制研究与实现

针对现有MQTT协议缺乏有效身份认证以及数据以明文形式传输的问题,提出了一种基于国密算法SM2,SM3,SM4的MQTT安全保护方案。通过SM2算法实现客户端与MQTT Broker之间的双向身份认证;通过SM4算法加密MQTT协议中用户名、密码、主题的消息内容等数据;通过SM3算法保证MQTT协议传输数据的完整性。将自主可控的国产密码技术应用到MQTT协议中,可有效提升该协议的安全防护能力。安全性分析和实验结果表明,所提方案在解决了MQTT协议安全问题的同时,也可以满足实际的应用需求。

超高清显示接口芯片的软件及认证算法设计

针对超高清显示接口芯片产业应用时客户提出的内容保护需求,该文通过研究HDCP所涉及到的加解密算法,分析HDCP1.4、HDCP2.2认证流程,结合具体的高清接口转换芯片应用方案,设计了MCU软件的下载及调试方法,采用软硬件结合并主要由软件实现的方式,设计了认证算法。通过搭建系统测试平台并使用专用的协议分析工具,对HDCP认证过程进行试验,抓取通信协议过程,结果显示,复杂计算的响应时间在100 ms以内,通过I2C下载32k程序用时在32 s以内,满足了规范和客户需求。

基于共识算法的换流站无线传感网安全接入身份认证机制

为了确保换流站无线传感网的安全性和可靠性,文章在换流站无线传感网中构建安全接入身份认证机制,提出了一种基于加权投票的共识算法,对接入换流站无线传感网的无线感知设备进行身份认证和授权,确保接入设备对无线传感网络资源的访问合法性。所提出的共识算法采用了加权投票的思想,根据感知设备拥有的资源和性能2个方面综合考虑并决定权重,通过权重值衡量节点在共识过程中的影响力,从而提高共识过程的公正性和可信度,并有效避免网络中的恶意攻击行为。从平均耗时、吞吐量、出错率和通信量开销等方面进行仿真验证,结果表明所提算法能够更好地适应不同接入终端之间的差异,提高了共识算法的效率和可靠性,为换流站无线传感网提供了有效的安全保障。

结合ECC算法的电力监控网络智能接入协议

为了进一步降低电力监控网络遭受攻击的风险,基于ECC公钥加密算法,提出了具有较高安全性能的智能接入协议。通过研究电力监控网络的基本架构和安全体系,总结了电力监控终端所面临的多种攻击方式。并在此基础上,利用ECC公钥加密算法,深度改进适用于电力监控网络的智能接入协议,进而优化协议的加密耗时、解密耗时及安全强度等多项参数。仿真结果表明,与基于RSA算法的协议相比,基于ECC算法的智能接入协议具备更高的安全强度。

基于对称加密算法的企业电子邮件权限安全管理

进行企业电子邮件权限安全管理时,主要采用非对称加密算法,导致企业电子邮件权限的安全管理效果较差,权限安全管理的时间开销较大。为此,设计一种融合对称加密算法的企业电子邮件权限安全管理方法。根据电子邮件实际内容定义标签和标识,明确电子邮件的安全级别。基于邮件发送人在企业内充当的角色,设计一种对称加密算法对电子邮件内容进行加密。运用PMI+PKI技术,结合身份认证特性和权限分配特性,建立邮件权限控制机制。从发送者和接收者两方面入手,认证电子邮件安全访问权限,实现企业电子邮件安全管理。实验结果显示,所提方法的邮件权限安全管理效果较好,整体时间开销为0.38 s,相比基于区块链、基于差分隐私的方法,时间开销分别减少了68.07%、39.11%。