Research and Implementation of Time Synchronous Dynamic Password Based on SM3 Hash Algorithm

With the rapid development of information technology, demand of network & information security has increased. People enjoy many benefits by virtue of information technology. At the same time network security has become the important challenge, but network information security has become a top priority. In the field of authentication, dynamic password technology has gained users’ trust and favor because of its safety and ease of operation. Dynamic password, SHA (Secure Hash Algorithm) is widely used globally and acts as information security mechanism against potential threat. The cryptographic algorithm is an open research area, and development of these state-owned technology products helps secure encryption product and provides safeguard against threats. Dynamic password authentication technology is based on time synchronization, using the state-owned password algorithm. SM3 hash algorithm can meet the security needs of a variety of cryptographic applications for commercial cryptographic applications and verification of digital signatures, generation and verification of message authentication code. Dynamic password basically generates an unpredictable random numbers based on a combination of specialized algorithms. Each password can only be used once, and help provide high safety. Therefore, the dynamic password technology for network information security issues is of great significance. In our proposed algorithm, dynamic password is generated by SM3 Hash Algorithm using current time and the identity ID and it varies with time and changes randomly. Coupled with the SM3 hash algorithm security, dynamic password security properties can be further improved, thus it effectively improves network authentication security.

Novel Block Chain Technique for Data Privacy and Access Anonymity in Smart Healthcare

The Internet of Things (IoT) and Cloud computing are gaining popularity due to their numerous advantages, including the efficient utilization of internetand computing resources. In recent years, many more IoT applications have beenextensively used. For instance, Healthcare applications execute computations utilizing the user’s private data stored on cloud servers. However, the main obstaclesfaced by the extensive acceptance and usage of these emerging technologies aresecurity and privacy. Moreover, many healthcare data management system applications have emerged, offering solutions for distinct circumstances. But still, theexisting system has issues with specific security issues, privacy-preserving rate,information loss, etc. Hence, the overall system performance is reduced significantly. A unique blockchain-based technique is proposed to improve anonymityin terms of data access and data privacy to overcome the above-mentioned issues.Initially, the registration phase is done for the device and the user. After that, theGeo-Location and IP Address values collected during registration are convertedinto Hash values using Adler 32 hashing algorithm, and the private and publickeys are generated using the key generation centre. Then the authentication is performed through login. The user then submits a request to the blockchain server,which redirects the request to the associated IoT device in order to obtain thesensed IoT data. The detected data is anonymized in the device and stored inthe cloud server using the Linear Scaling based Rider Optimization algorithmwith integrated KL Anonymity (LSR-KLA) approach. After that, the Time-stamp-based Public and Private Key Schnorr Signature (TSPP-SS) mechanismis used to permit the authorized user to access the data, and the blockchain servertracks the entire transaction. The experimental findings showed that the proposedLSR-KLA and TSPP-SS technique provides better performance in terms of higherprivacy-preserving rate, lower information loss, execution time, and Central Processing Unit (CPU) usage than the existing techniques. Thus, the proposed method allows for better data privacy in the smart healthcare network.

Modified Elliptic Curve Cryptography Multi-Signature Scheme to Enhance Security in Cryptocurrency

Internet of Things(IoT)is an emerging technology that moves the world in the direction of smart things.But,IoT security is the complex problem due to its centralized architecture,and limited capacity.So,blockchain technology has great attention due to its features of decentralized architecture,transparency,immutable records and cryptography hash functions when combining with IoT.Cryptography hash algorithms are very important in blockchain technology for secure transmission.It converts the variable size inputs to a fixed size hash output which is unchangeable.Existing cryptography hash algorithms with digital signature have issues of single node accessibility and accessed up to 128 bytes of key size only.As well as,if the attacker tries to hack the key,it cancels the transaction.This paper presents the Modified Elliptic Curve Cryptography Multi Signature Scheme(MECC-MSS)for multiple node accessibility by finding nearest path for secure transaction.In this work,the input key size can be extended up to 512 bytes to enhance the security.The performance of the proposed algorithm is analyzed with other cryptography hash algorithms like Secure Hashing Algorithms(SHAs)such as SHA224,SHA256,SHA384,SHA512,SHA3-224,SHA3-256,SHA3-384,SHA3-512 and Message Digest5 by one-way analysis of variance test in terms of accuracy and time complexity.Results show that the MECC-MSS achieves 90.85%of accuracy and time complexity of 1.4 nano seconds with significance less than 0.05.From the statistical analysis,it is observed that the proposed algorithm is significantly better than other cryptography hash algorithms and also having less time complexity.

Forensics: Collection of Sound Digital Evidence

This summary paper will discuss the concept of forensic evidence and evidence collection methods. Emphasis will be placed on the techniques used to collect forensically sound digital evidence for the purpose of introduction to digital forensics. This discussion will thereafter result in identifying and categorizing the different types of digital forensics evidence and a clear procedure for how to collect forensically sound digital evidence. This paper will further discuss the creation of awareness and promote the idea that competent practice of computer forensics collection is important for admissibility in court.

基于FPGA集群的Office口令恢复优化实现

口令恢复是口令找回和电子取证的关键技术,而加密的Office文档被广泛使用,实现Office加密文档的有效恢复对信息安全具有重要的意义。口令恢复是计算密集型任务,需要硬件加速来实现恢复过程,传统的CPU和GPU受限于处理器结构,大大限制了口令验证速度的进一步提升。基于此,文中提出了基于FPGA集群的口令恢复系统。通过详细分析Office加密机制,给出了各版本Office的口令恢复流程。其次,在FPGA上以流水线结构优化了核心Hash算法,以LUT(Look Up Table)合并运算优化改进了AES(Advanced Encryption Standard)算法,以高速并行实现了口令生成算法。同时,以多算子并行设计了FPGA整体架构,实现了Office口令的快速恢复。最后,采用FPGA加速卡搭建集群,配合动态口令切分策略,充分发掘了FPGA低功耗高性能的计算特性。实验结果表明,无论在计算速度还是能效比上,优化后的FPGA加速卡都是GPU的2倍以上,具有明显的优势,非常适合大规模部署于云端,以缩短恢复时间找回口令。

An IoT Based Secure Patient Health Monitoring System

Internet of things(IoT)field has emerged due to the rapid growth of artificial intelligence and communication technologies.The use of IoT technology in modern healthcare environments is convenient for doctors and patients as it can be used in real-time monitoring of patients,proper administration of patient information,and healthcare management.However,the usage of IoT in the healthcare domain will become a nightmare if patient information is not securely maintainedwhile transferring over an insecure network or storing at the administrator end.In this manuscript,the authors have developed a secure IoT healthcare monitoring system using the Blockchainbased XOR Elliptic Curve Cryptography(BC-XORECC)technique to avoid various vulnerable attacks.Initially,thework has established an authentication process for patient details by generating tokens,keys,and tags using Length Ceaser Cipher-based PearsonHashingAlgorithm(LCC-PHA),EllipticCurve Cryptography(ECC),and Fishers Yates Shuffled Based Adelson-Velskii and Landis(FYS-AVL)tree.The authentications prevent unauthorized users from accessing or misuse the data.After that,a secure data transfer is performed using BC-XORECC,which acts faster by maintaining high data privacy and blocking the path for the attackers.Finally,the Linear Spline Kernel-Based Recurrent Neural Network(LSK-RNN)classification monitors the patient’s health status.The whole developed framework brings out a secure data transfer without data loss or data breaches and remains efficient for health care monitoring via IoT.Experimental analysis shows that the proposed framework achieves a faster encryption and decryption time,classifies the patient’s health status with an accuracy of 89%,and remains robust comparedwith the existing state-of-the-art method.

A Robust Watermarking Scheme Based on ROI and IWT for Remote Consultation of COVID-19

In the current dire situation of the corona virus COVID-19,remote consultations were proposed to avoid cross-infection and regional differences in medical resources.However,the safety of digital medical imaging in remote consultations has also attracted more and more attention from the medical industry.To ensure the integrity and security of medical images,this paper proposes a robust watermarking algorithm to authenticate and recover from the distorted medical images based on regions of interest(ROI)and integer wavelet transform(IWT).First,the medical image is divided into two different parts,regions of interest and non-interest regions.Then the integrity of ROI is verified using the hash algorithm,and the recovery data of the ROI region is calculated at the same time.Also,binary images with the basic information of patients are processed by logistic chaotic map encryption,and then the synthetic watermark is embedded in the medical carrier image using IWT transform.The performance of the proposed algorithm is tested by the simulation experiments based on the MATLAB program in CT images of the lungs.Experimental results show that the algorithm can precisely locate the distorted areas of an image and recover the original ROI on the basis of verifying image reliability.The maximum peak signal to noise ratio(PSNR)value of 51.24 has been achieved,which proves that the watermark is invisible and has strong robustness against noise,compression,and filtering attacks.

Vitality evaluation of the waterfront space in the ancient city of Suzhou

With a history spanning thousands of years,the water system of Suzhou is an indispensable carrier of urban space and civil culture.Quantificational model analysis of the waterfront in the ancient city of Suzhou has significant implications for the future design of waterfront space and the establishment of an evaluation method to determine the vitality of such space.In this study,a vitality evaluation model was first constructed using river attributes,the spatial type of waterfront areas,vision accessibility,transportation accessibility,and combined new data extracted using spatial factor analysis.Second,a vitality evaluation matrix was established using the analytic hierarchy process to simulate the vitality of waterfront spaces.Third,a hash algorithm was employed to determine the fitting degree between the vitality model of Suzhou’s waterfront space and crowd activity.The different areas between them were found and then the factor evaluation process was adjusted on this basis of analyzing the causes.Thus,this study identified the factors influencing the vitality of Suzhou’s waterfront.Furthermore,this research constructed a model for evaluating the vitality of waterfront spaces.Finally,some guidelines were presented regarding the design and implementation of waterfront spaces in urban design.