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An efficient signed SSL/TLS-based data security in the cloud using LTT-DDBM and TECC

International Journal of Information Technology (Singapore) 2024年 1-16页

作者： Tiwari, Chandra Sekhar Jha, Vijay Kumar Department of Computer Science and Engineering Birla Institute of Technology Mesra Ranchi India

Cloud Data Security (CDS) is a set of strategies for securing data from security threats. However, the previous works ignored the prevention of multiple cloud security attacks. To tackle this problem, an efficient security framework using Signed Secure Socket Layer/Transport Layer Security (SSL/TLS) with Log Triangular Transfer function-based Deep Drop Boltzmann Machines (LTT-DDBM) and Rivest-Shamir-Adleman Session Key-centric Twisted Edwards Curve Cryptography (RSASK-TECC) techniques is proposed in this paper. The process begins with the web owner who requests an SSL/TLS certificate from the Certificate Authority Centre (CAC) for establishing a website. After meeting CAC requirements, the web owner uploads files to the server. The Data Owner (DO) logs in and the signed SSL/TLS certificate is sent to the CAC for verification using LTT-DDBM. After the successful verification, a public key and session key are generated to encrypt the data. The data is further encrypted within 1124 ms using Advanced Encryption Standard Session key-based Twisted Edwards Curve Cryptography (AESS-TECC) for enhanced security. Before downloading, the data user checks the hash codes for integrity. If the codes match, then the access is granted;or else, it is denied. Hence, the proposed work outperformed the traditional methodologies. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Advanced encryption standard session key based twisted Edwards curve cryptography (AESS-TECC) Cloud data security Digital signature algorithm (DSA) hashing algorithm Log triangular transfer function based deep drop Boltzmann machines (LTT-DDBM) Secure socket layer/transport layer security (SSL/TLS)

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Performance of Computing Hash-Codes with Chaotically-Trained Artificial Neural Networks 22nd

Performance of Computing Hash-Codes with Chaotically-Trained...

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22nd Annual International Conference on Computational Science (ICCS)

作者： Tchorzewski, Jacek Byrski, Aleksander Cracow Univ Technol Krakow Poland AGH Univ Sci & Technol Krakow Poland

ISBN: (纸本)9783031087547;9783031087530

The main goal of the research presented in this paper was to estimate the performance of applying neural networks trained with the usage of a chaotic model, that may serve as hashing functions. The Lorenz Attractor chaotic model was used for training data preparation, and Scaled Conjugate Gradient was used as a training algorithm. Networks consisted of two layers: a hidden layer with sigmoid neurons and an output layer with linear neurons. The method of bonding the input message with chaotic formula is presented. Created networks could return 256 or 512 bits of hash, however, this parameter can be easily adjusted before the training process. The performance analysis of networks is discussed (that is the time of hash computation) in comparison with popular standards SHA-256 and SHA-512 under the MATLAB environment. Further research may include analysis of networks' training parameters (like mean squared error or gradient) or analysis of results of the statistical tests performed on networks output. The presented solution may be used as a security algorithm complementary to a certificated one (for example for additional data integrity checking).

关键词： hashing algorithm Artificial Neural Networks Scalable cryptography algorithm hashing efficiency

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Blockchain technology development and implementation for global logistics operations: a reference model perspective

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JOURNAL OF GLOBAL OPERATIONS AND STRATEGIC SOURCING 2021年第2期14卷 360-382页

作者： Kamran, Rukshanda Khan, Nasreen Sundarakani, Balan SZABIST Dubai Dept Informat Technol Dubai U Arab Emirates Univ Wollongong Dubai Fac Business Dubai U Arab Emirates

Purpose - Blockchain technology offers a lot of potential benefits in supply chain management. However, there is a need of a reference model which addresses the gaps in existing frameworks. This paper aims to propose a blockchain technology-based reference model which can be applied to global logistics operations. Design/methodology/approach - The researchers have integrated the fit-for-purpose theoretical framework and prototyping methodology to design the reference model, a blockchain-based logistics, tracking and traceability system (BLTTS). The researchers demonstrated the application of the reference model through a health-care supply chain case study. The proposed BLTTS can be implemented across global logistics operations for business performance improvement. Findings - The research provides a framework and recommendations for global companies to consider when adopting the blockchain technology for implementation. The researchers found that the Ethereum blockchain technology improves security of the data shared within the block through the secure hashing algorithm 1. The hash algorithm ensures anonymity of the involved parties. The model integrates blockchain with supply chain thus creating transparent process, efficiency and real-time communication. Research limitations/implications - The reference model will offer a better solution to global logistics operations challenges. It provides recommendations to key stakeholders involved in logistics operations segment of the logistics industry while adopting blockchain technology. Apart from the methodological limitation of the study, the system compatibility and the layer configuration aspects might be posing potential challenges while upscaling the implementation. Originality/value - The proposed reference model overcomes the drawbacks of existing models as it integrates Ethereum technology. In addition, the researchers have applied the model to demonstrate its functioning in real-time environment, which could g

关键词： Blockchain Decentralized applications Supply chain management hashing algorithm Transparency and security Qualitative

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Authentication and Authorization in Modern Web Apps for Data Security Using Nodejs and Role of Dark Web

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Procedia Computer Science 2022年 215卷 781-790页

作者： Piyush Pant Anand Singh Rajawat S.B. Goyal Pradeep Bedi Chaman Verma Maria Simona Raboaca Florentina Magda Enescu School of Computer Sciences and Engineering Nashik Sandip University India Faculty of Information Technology City university Petaling Jaya 46100 Malaysia ICSI Energy Department National Research and Development Institute for Cryogenics and Isotopic Technologies 240050 Ramnicu Valcea Romania Department of Electronics Communications and Computers University of Pitesti Pitesti Romania

Authentication and Authorization are the base of security for all the Technologies present in this world today. Starting from your smartphone where a user authenticates himself before he could access the data inside to Entering into the White House, you must authenticate yourself, and based on that you are authorized. In this digital world where every Business, MNC, Government Body, Companies, Users, etc. needs a website to inform the world about their presence on the internet, provide services online and become a “Brand”, the risk of leaking user's sensitive information increases. It could be dangerous to the users of the hacked website because their sensitive information like a credit card, bank account details, etc. could be sold in the black market of the “dark web”. The role of the dark web is described in the paper and how the data is sold there and what becomes of it. The paper helps to understand how a secure website is developed that promises the user to keep the sensitive information safe, increases the bond of trust between a client and server which results in a long-term relationship. The aim behind developing an authentication system is to keep users’ sensitive information safe so that hackers cannot steal and sell the information on the dark web's back market. To perform this, the developer needs to understand how to implement authentication. NodeJS, with the help of its framework expressJS and some other packages, is used to develop the authentication and authorization system of the website by the research. Previous papers on this field covered the authentication topic in general. This paper overcame that by going deeper into the field and being server-side language specific. The common types of authentication methods used in different types of websites are discussed in detail and the best methods are purposed for the developer to be implemented for a more secure website. This research put light on Artificial Intelligence and blockchain as the future

关键词： Artificial Intelligence Authentication Authorization Blockchain NodeJS hashing algorithm Dark Web MongoDB

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Deep Learning Triplet Ordinal Relation Preserving Binary Code for Remote Sensing Image Retrieval Task

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REMOTE SENSING 2021年第23期13卷 4786-4786页

作者： Wang, Zhen Wu, Nannan Yang, Xiaohan Yan, Bingqi Liu, Pingping Shandong Univ Technol Sch Comp Sci & Technol Zibo 255000 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ Changchun 130012 Peoples R China Jilin Univ Sch Comp Sci & Technol Changchun 130012 Peoples R China

As satellite observation technology rapidly develops, the number of remote sensing (RS) images dramatically increases, and this leads RS image retrieval tasks to be more challenging in terms of speed and accuracy. Recently, an increasing number of researchers have turned their attention to this issue, as well as hashing algorithms, which map real-valued data onto a low-dimensional Hamming space and have been widely utilized to respond quickly to large-scale RS image search tasks. However, most existing hashing algorithms only emphasize preserving point-wise or pair-wise similarity, which may lead to an inferior approximate nearest neighbor (ANN) search result. To fix this problem, we propose a novel triplet ordinal cross entropy hashing (TOCEH). In TOCEH, to enhance the ability of preserving the ranking orders in different spaces, we establish a tensor graph representing the Euclidean triplet ordinal relationship among RS images and minimize the cross entropy between the probability distribution of the established Euclidean similarity graph and that of the Hamming triplet ordinal relation with the given binary code. During the training process, to avoid the non-deterministic polynomial (NP) hard problem, we utilize a continuous function instead of the discrete encoding process. Furthermore, we design a quantization objective function based on the principle of preserving triplet ordinal relation to minimize the loss caused by the continuous relaxation procedure. The comparative RS image retrieval experiments are conducted on three publicly available datasets, including UC Merced Land Use Dataset (UCMD), SAT-4 and SAT-6. The experimental results show that the proposed TOCEH algorithm outperforms many existing hashing algorithms in RS image retrieval tasks.

关键词： remote sensing image retrieval hashing algorithm binary code triplet ordinal relation preserving cross entropy

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Complexification of eukaryote phenotype: Adaptive immuno-cognitive systems as unique Gödelian blockchain distributed ledger

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BioSystems 2022年 220卷 104718页

作者： Markose, Sheri M. University of Essex Wivenhoe Park Colchester Essex CO4 3SQ United Kingdom

The digitization of inheritable information in the genome has been called the ‘algorithmic take-over of biology’. The McClintock discovery that viral software based transposable elements that conduct cut-paste (transposon) and copy-paste (retrotransposon) operations are needed for genomic evolvability underscores the truism that only software can change software and also that viral hacking by internal and external bio-malware is the Achilles heel of genomic digital systems. There was a paradigm shift in genomic information processing with the Adaptive Immune System (AIS) 500 mya followed by the Mirror Neuron System (MNS), latterly mostly in primate brains, which reaches its apogee in human social cognition. The AIS and MNS involve distinctive Gödelian features of self-reference (Self-Ref) and offline virtual self-representation (Self-Rep) for complex self-other interaction with prodigious open-ended capacity for anticipative malware detection and novelty production within a unique blockchain distributed ledger (BCDL). The role of self-referential information processing, often considered to be central to the sentient self with origins in the immune system ‘Thymic self’, is shown to be part of the Gödel logic behind a generator-selector framework at a molecular level, which exerts stringent selection criteria to maintain genomic BCDL. The latter manifests digital and decentralized record keeping where no internal or external bio-malware can compromise the immutability of the life's building blocks and no novel blocks can be added that is not consistent with extant blocks. This is demonstrated with regard to somatic hypermutation with novel anti-body production in the face of external non-self antigen attacks. © 2022 The Author

关键词： Adaptive immune system Blockchain distributed ledger Complexification Gödel sentence hashing algorithm Mirror neuron system Self-reference Self-representation

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Multi-copy Cuckoo hashing 35

Multi-copy Cuckoo Hashing

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IEEE 35th International Conference on Data Engineering (ICDE)

作者： Li, Dagang Du, Rong Liu, Ziheng Yang, Tong Cui, Bin Peking Univ Shenzhen Grad Sch SECE Shenzhen Peoples R China Shenzhen Key Lab Info Theory&Future Net Arch Shenzhen Peoples R China Peking Univ Dept Comp Sci Beijing Peoples R China

ISBN: (纸本)9781538674741

Cuckoo hashing is widely used for its worst-case constant lookup performance even at very high load. However at high load, collision resolution will involve lots of probes on item relocation and may still fail in the end. To address the problem, we propose an efficient Cuckoo hashing scheme called Multi-copy Cuckoo or McCuckoo. Different from the blind kick-outs of standard Cuckoo hashing during a collision, we can foresee which way to successfully kick items by using multiple copies. Furthermore, with the knowledge of how many copies each item has in the table, we can identify impossible buckets and skip them during a lookup. In order to avoid expensive rehashing during insertion failures, McCuckoo also supports more efficient stash strategy that minimizes stash checking. McCuckoo uses simple logic and simple data structure, so it is suitable for both software and hardware implementation on platforms where intensive access to the slow and bandwidth limited off-chip external memory is the main bottleneck.

关键词： Cuckoo hashing hashing algorithm Multi-copy

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An Improved hashing Method for Image Retrieval Based on Deep Neural Networks 18

An Improved Hashing Method for Image Retrieval Based on Deep...

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International Conference on Signal Processing and Machine Learning (SPML)

作者： Chen, Qiu Wang, Weidong Lee, Feifei Kogakuin Univ Tokyo Japan Univ Shanghai Sci & Technol Shanghai Peoples R China

ISBN: (纸本)9781450366052

hashing algorithm projects the vector of features onto the binary space that generate the binary codes to reduce calculating time. Thus hashing algorithm is widely used to improve retrieval efficiency in traditional image retrieval methods based on Deep neural networks (DNNs). In this paper, we extract the feature vectors whose elements between 0 and 1 by DNNs and linear scaling method, then we define the mean of each column vector of the matrix consisted of these feature vectors as threshold to create corresponding hashing codes after two-stages binarization. Since threshold brings major effect to the preservation of the similarity between images, during this process, the two-stages binarization play two important roles: 1) optimizing thresholds;2) optimizing hash codes. The promising experimental results on public available Cifar-10 database show that the proposed approach achieve higher precision compared with the state-of-the-art hashing algorithms.

关键词： Deep neural networks (DNNs) hashing algorithm Image retrieval

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Man-machine dialogue system optimization based on cloud computing

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PERSONAL AND UBIQUITOUS COMPUTING 2018年第5-6期22卷 937-942页

作者： Jin, Maozhu Wang, Hua Song, Lijun Li, Yuxue Zeng, Yucheng Sichuan Univ Business Sch Chengdu 610065 Sichuan Peoples R China Chengdu Univ Informat Technol Coll Commun Engn Chengdu 610065 Sichuan Peoples R China Sichuan Univ Sci & Engn Management Sch Zigong 643000 Peoples R China

This paper studies the optimization and implementation of human-machine dialog system based on cloud computing technology. Firstly, the coarse-perceived hash generation based on the formant frequency is studied, and the detail-aware hash generation based on the energy difference in the time domain is studied. Then, the combination of coarse-perceived hash and detail-aware hash is elaborated. Secondly, the algorithm is tested and emulated. The algorithm matches the coarse-perceived hash sequence with fewer bits, and returns the voice number with similar rough features to the index voice after matching successfully, and matches the detail-aware hash sequence of the corresponding number voice. Then, the exact match of the result is gotten. Finally, it is concluded that the algorithm in this paper can effectively recognize the human voice.

关键词： Cloud computing Man-machine conversation hashing algorithm

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The Normalized Distance Preserving Binary Codes and Distance Table

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2017年第2期33卷 499-515页

作者： Zhao, Hongwei Wang, Zhen Liu, Pingping Wu, Bin Jilin Univ Sch Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Ministy Educ Changchun 130012 Peoples R China

In the Euclidean space, the approximate nearest neighbors (ANN) search measures the similarity degree through computing the Euclidean distances, which owns high time complexity and large memory overhead. To address these problems, this paper maps the data from the Euclidean space into the Hamming space, and the normalized distance similarity restriction and the quantization error are required to satisfy. Firstly, the encoding centers and their binary labels are obtained through a lookup-based mechanism. Then, the candidate hashing functions are learnt under supervision of the binary labels, and the ones which satisfy the entropy criterion are selected to boost the distinctiveness of the learnt binary codes. During the training procedure, multiple groups of the hashing functions are generated based on different kinds of centers, which can weaken the inferior influence of the initial centers. The data with minimal average Hamming distances are returned as the nearest neighbors. In the Hamming space, different Euclidean distances may be substituted by one identical value, thus a distance table is predefined to distinguish the similarity degrees among the data pairs with the same Hamming distance. The final experimental results show that our algorithm is superior to many state-of-the-art methods.

关键词： approximate nearest neighbors search binary codes hashing algorithm semi supervised learning entropy

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