MB File Research Articles

The key security management scheme of cloud storage based on blockchain and digital twins

As a secure distributed ledger technology, blockchain has attracted widespread attention from academia and industry for its decentralization, immutability, and traceability characteristics. This paper proposes a cloud storage key security management scheme based on blockchain. To resist brute-force attacks launched by adversaries on ciphertexts, the scheme uses an oblivious pseudo-random function (OPRF) to generate randomized convergent keys and improve data confidentiality. Second, the scheme enhances the reliability of concurrent key management through a secret sharing mechanism, where convergent keys are split into key fragments and distributed on blockchain for storage. Even if a certain number of key fragments are lost or damaged, users can still recover complete key information through block transaction records. In addition, the scheme effectively supports file-level and block-level data security deduplication. Security analysis and experimental performance evaluation indicate that this scheme can ensure the security of keys and the confidentiality of data, and it has a low computational overhead for generating file-level encryption keys under this scheme. Even for a 100 MB file, the computational overhead required for generating encryption keys is less than 2 s, which improves computational efficiency.

Discontinuity-Aware 2D Neural Fields

Neural image representations offer the possibility of high fidelity, compact storage, and resolution-independent accuracy, providing an attractive alternative to traditional pixel- and grid-based representations. However, coordinate neural networks fail to capture discontinuities present in the image and tend to blur across them; we aim to address this challenge. In many cases, such as rendered images, vector graphics, diffusion curves, or solutions to partial differential equations, the locations of the discontinuities are known. We take those locations as input, represented as linear, quadratic, or cubic Bézier curves, and construct a feature field that is discontinuous across these locations and smooth everywhere else. Finally, we use a shallow multi-layer perceptron to decode the features into the signal value. To construct the feature field, we develop a new data structure based on a curved triangular mesh, with features stored on the vertices and on a subset of the edges that are marked as discontinuous. We show that our method can be used to compress a 100, 000 2 -pixel rendered image into a 25MB file; can be used as a new diffusion-curve solver by combining with Monte-Carlo-based methods or directly supervised by the diffusion-curve energy; or can be used for compressing 2D physics simulation data.

Blockchain-Enabled NextGen Service Architecture for Mobile Internet Offload

The amalgamation of heterogeneous generations of mobile cellular networks around the globe has resulted in diverse data speed experiences for end users. At present, there are no defined mechanisms in place for subscribers of a mobile network operator (MNO) to use the services of third-party WiFi providers. MNOs also have no standardized procedures to securely interact with each other, and allow their subscribers to use third-party services on a pay-as-you-go basis. This paper proposes a blockchain-enabled offloading framework that allows a subscriber of a mobile operator to temporarily use another MNO or WiFi provider’s higher-speed network. A smart contract is employed to allow diverse entities, such as MNOs, brokers and WiFi providers, to automatically execute mutual agreements, to enable the utilization of third-party infrastructure in a secure and controlled manner. The proposed framework is tested using Ethereum’s testnet on the Goerli network using Alchemy and Hardhat. The analysis of the results obtained shows that the proposed technique helps mobile operators to offer improved user experience in the form of average speed and latency. The experiments show that the average time taken to deliver a 500 MB file is reduced from 10.23 s to 0.91 s for the global average scenario, from 6.09 s to 0.50 s for 5G, from 13.50 s to 0.50 s for 4G-LTE, from 41.11 s to 0.49 s for 4G, and from 339.11 s to 0.49 s for the 3G scenario. The results also show that, with WiFi offloading, users from all cellular generations can enjoy a similar quality of services, because delivery time ranges from 0.49 s to 0.91 s for offloaded experiments whereas for the non-offloaded scenario it ranges from 6.09 s to 339.11 s.

A Virtual Cloud Storage Architecture for Enhanced Data Security

The sensitive data stored in the public cloud by privileged users, such as corporate companies and government agencies are highly vulnerable in the hands of cloud providers and hackers. The proposed Virtual Cloud Storage Architecture is primarily concerned with data integrity and confidentiality, as well as availability. To provide confidentiality and availability, the file to be stored in cloud storage should be encrypted using an auto-generated key and then encoded into distinct chunks. Hashing the encoded chunks ensured the file integrity, and a newly proposed Circular Shift Chunk Allocation technique was used to determine the order of chunk storage. The file could be retrieved by performing the operations in reverse. Using the regenerating code, the model could regenerate the missing and corrupted chunks from the cloud. The proposed architecture adds an extra layer of security while maintaining a reasonable response time and storage capacity. Experimental results analysis show that the proposed model has been tested with storage space and response time for storage and retrieval. The VCSA model consumes 1.5x (150%) storage space. It was found that total storage required for the VCSA model is very low when compared with 2x Replication and completely satisfies the CIA model. The response time VCSA model was tested with different sized files starting from 2 to 16 MB. The response time for storing and retrieving a 2 MB file is 4.96 and 3.77 s respectively, and for a 16 MB file, the response times are 11.06 s for storage and 5.6 s for retrieval.

Brain Computer Interface Based Thought Recognition System Using a Hybrid Deep Learning Model

ABSTRACT Brain-Computer Interface (BCI) connects the human brain with computers and electronic devices. The signals from human brain are processed using several deep-learning techniques to convert them into a comprehensible form. Among these techniques, the convolutional neural network (CNN) model has excellent performance in BCI recognition. However, the existing CNN model is prone to over-fitting and has limitations with accuracy. The model complexity must be increased to achieve better accuracy. To address these concerns, a novel hybrid R-CNN model for BCI thought recognition is proposed in this work. The convolution layer of CNN and the Long short-term memory (LSTM) layer of recurrent neural network (RNN) is utilized for this purpose. A batch normalization layer is also instigated to reduce over-fitting. Further, a rectified linear unit (ReLU) is engaged to speed up training under as low as five epochs, along with a custom optimizer which optimizes some default values within the optimizer. Experiments are performed with BCI datasets of two different file sizes with different records. The first dataset size is 6.5 MB having 60684 records with three classes, and the second dataset size is 10.1 MB having 94119 records with five classes. Consequently, the proposed hybrid model exhibits a higher average accuracy of 95% for 6.5 MB file size and 98% for 10.1 MB file size, which is superior compared to the accuracy of existing deep learning models. Furthermore, the efficiency of the proposed novel hybrid R-CNN model is evaluated with some other performance measures such as F1-score, recall and precision.

Hybrid load-balancing algorithm for distributed fog computing in internet of things environment

Fog computing is a novel idea created by Cisco that provides the same capabilities as cloud computing but close to objects to improve performance, such as by minimizing latency and reaction time. Packet failure can happen on a single fog server across a large number of messages from internet of things (IoT) sensors due to several variables, including inadequate bandwidth and server queue capacity. In this paper, a fog-to-server architecture based on the IoT is proposed to solve the problem of packet loss in fog and servers using hybrid load balancing and a distributed environment. The proposed methodology is based on hybrid load balancing with least connection and weighted round robin algorithms combined together in fog nodes to take into consideration the load and time to distribute requests to the active servers. The results show the proposed system improved network evaluation parameters such as total response time of 131.48 ms, total packet loss rate of 15.670%, average total channel idle of 99.55%, total channel utilization of 77.44%, average file transfer protocol (FTP) file transfer speed (256 KB to 15 MB files) of 260.77 KB/sec, and average time (256 KB to 15 MB) of 19.27 sec.

Throughput Analysis and Data Sharing Technique to Assess the Impact of Blockchain Technology using Cryptographic Algorithm

Blockchain is a data structure made up of chronologically ordered data blocks. Research revealed that traditional blockchains have constrained throughput. It is ideal for blockchain technology to achieve higher throughput by increasing the block size and lessening the block interval. The methodology used in this paper is of two parts. The first approach uses the cryptographic protocol to ensure the authenticity and integrity of the information using an Ethereum blockchain type. This means that transactions are recorded in write-only mode and contributes to transaction trust and transparency. Our methodology automates smart and secure evaluations and provides credentials using an Improved Elliptic Curve Cryptography Algorithm (IECCA). It is implemented using encryption and decryption algorithms and is demonstrated using analytical and content neutrality. We also demonstrate operation from back-end to end-users application including student and faculty members. The Level of security performance of the proposed scheme is compared with another scheme for a 20MB file size. The proposed schemes achieve 83% IECCA, 78 percent DES, 76% RSA, and 70% AES respectively. The second approach identifies the boundary for conventional block sizes and block intervals. Security of blockchain using stale block rate is identified in the network by conducting a realistic experiment. This enables the realization of optimal block parameters like size and interval. Results presents achieve a rate of transmission for a blockchain platform to be deployed in other activities beyond cryptocurrency, like electronic voting.

Hidden Addressing Encoding for DNA Storage.

DNA is a natural storage medium with the advantages of high storage density and long service life compared with traditional media. DNA storage can meet the current storage requirements for massive data. Owing to the limitations of the DNA storage technology, the data need to be converted into short DNA sequences for storage. However, in the process, a large amount of physical redundancy will be generated to index short DNA sequences. To reduce redundancy, this study proposes a DNA storage encoding scheme with hidden addressing. Using the improved fountain encoding scheme, the index replaces part of the data to realize hidden addresses, and then, a 10.1 MB file is encoded with the hidden addressing. First, the Dottup dot plot generator and the Jaccard similarity coefficient analyze the overall self-similarity of the encoding sequence index, and then the sequence fragments of GC content are used to verify the performance of this scheme. The final results show that the encoding scheme indexes with overall lower self-similarity, and the local thermodynamic properties of the sequence are better. The hidden addressing encoding scheme proposed can not only improve the utilization of bases but also ensure the correct rate of DNA storage during the sequencing and decoding processes.

Enterprise Data Sharing with Privacy-Preserved Based on Hyperledger Fabric Blockchain in IIOT's Application.

Internet of Things (IoT) technology is now widely used in energy, healthcare, services, transportation, and other fields. With the increase in industrial equipment (e.g., smart mobile terminals, sensors, and other embedded devices) in the Internet of Things and the advent of Industry 4.0, there has been an explosion of data generated that is characterized by a high volume but small size. How to manage and protect sensitive private data in data sharing has become an urgent issue for enterprises. Traditional data sharing and storage relies on trusted third-party platforms or distributed cloud storage, but these approaches run the risk of single-node failure, and third parties and cloud storage providers can be vulnerable to attacks that can lead to data theft. To solve these problems, this paper proposes a Hyperledger Fabric blockchain-based secure data transfer scheme for enterprises in the Industrial Internet of Things (IIOT). We store raw data in the IIoT in the InterPlanetary File System (IPFS) network after encryption and store the Keyword-index table we designed in Hyperledger Fabric blockchain, and enterprises share the data by querying the Keyword-index table. We use Fabric’s channel mechanism combined with our designed Chaincode to achieve privacy protection and efficient data transmission while using the Elliptic Curve Digital Signature Algorithm (ECDSA) to ensure data integrity. Finally, we performed security analysis and experiments on the proposed scheme, and the results show that overall the data transfer performance in the IPFS network is generally better than the traditional network, In the case of transferring 5 MB file size data, the transmission speed and latency of IPFS are 19.23 mb/s and 0.26 s, respectively, and the IPFS network is almost 4 times faster than the TCP/IP network while taking only a quarter of the time, which is more advantageous when transferring small files, such as data in the IIOT. In addition, our scheme outperforms the blockchain systems mainly used today in terms of both throughput, latency, and system overhead. The average throughput of our solution can reach 110 tps (transactions are executed per second), and the minimum throughput in experimental tests can reach 101 tps.

A New Hybrid Automated Security Framework to Cloud Storage System

The need for cloud storage grows day after day due to its reliable and scalable nature. The storage and maintenance of user data at a remote location are severe issues due to the difficulty of ensuring data privacy and confidentiality. Some security issues within current cloud systems are managed by a cloud third party (CTP), who may turn into an untrustworthy insider part. This paper presents an automated Encryption/Decryption System for Cloud Data Storage (AEDS) based on hybrid cryptography algorithms to improve data security and ensure confidentiality without interference from CTP. Three encryption approaches are implemented to achieve high performance and efficiency: Automated Sequential Cryptography (ASC), Automated Random Cryptography (ARC), and Improved Automated Random Cryptography (IARC) for data blocks. In the IARC approach, we have presented a novel encryption strategy by converting the static S-box in the AES algorithm to a dynamic S-box. Furthermore, the algorithms RSA and Twofish are used to encrypt the generated keys to enhance privacy issues. We have evaluated our approaches with other existing symmetrical key algorithms such as DES, 3DES, and RC2. Although the two proposed ARC and ASC approaches are more complicated, they take less time than DES, DES3, and RC2 in processing the data and obtaining better performance in data throughput and confidentiality. ARC outperformed all of the other algorithms in the comparison. The ARC’s encrypting process has saved time compared with other algorithms, where its encryption time has been recorded as 22.58 s for a 500 MB file size, while the DES, 3DES, and RC2 have completed the encryption process in 44.43, 135.65, and 66.91 s, respectively, for the same file size. Nevertheless, when the file sizes increased to 2.2 GB, the ASC proved its efficiency in completing the encryption process in less time.

Lightweight Public/Private Auditing Scheme for Resource-Constrained End Devices in Cloud Storage

Data integrity protection, an important feature in cloud storage services, can be achieved using auditing schemes. However, existing public and private auditing schemes are somewhat inefficient in practice. For example, in private auditing schemes, the trusted third-party is generally not able to settle disputes between users and the cloud storage server. In most existing public auditing schemes, it takes a user tens of seconds to generate data tags for every MB of file outsourced, which is clearly impractical particularly on resource-constrained end devices. Since the user is likely to have information than the auditor, we divide the verification phase into private verification and public verification phases. Then, we propose a public/private auditing model and a security model for public/private auditing. In our public/private auditing model, the user uses private verification phase to audit outsourced data promptly in most cases, and the auditor uses public verification phase to audit outsourced data only when dispute occurs or the user is not available to audit. Then, we propose a public/private auditing scheme, and present its security proof in the random oracle model under the discrete logarithm assumption. Experimental findings demonstrate that our scheme only need tens of microseconds to generate data tags for every MB file outsourced. In other words, the efficiency of our scheme is almost as high as existing high-performing private auditing schemes, and our scheme is more effective in comparison to existing efficient public auditing schemes.

Signal with Blake2, Chacha20 and Poly1305

Messaging applications are now adopting the concept of end to end encryption. Signal uses the Signal Protocol which has no known vulnerabilities for its end to end encryption. The protocol was explained in this work and possibilities of improvements were explored. It was discovered that the protocol implementation uses the SHA-512 hash, AES in CBC mode for encryption and HMAC for authentication. These Cryptographic Primitives were replaced with more efficient alternatives, Blake2, Chacha20 and Poly1305 respectively. An application was created to test the running time of the proposed cryptographic primitives against the existing one. From the results, Blake2b performs better than SHA-512 when hashing keys, short text, and 1.4 MB file. Similarly, Chacha20/Poly1305 performs better than AES/CBC/HMAC-sha256 in both encrypting and decrypting short text as well as 1.4 MB file. The proposed changes were implemented in the Signal Application. Automatic test in the Signal application was used to ensure that changes made to the code did not cause any logic errors. To further test the application, it was installed on another phone and messages were sent. The security code was also verified. . Keywords: Signal, Blake2, Chacha20, Poly1305

Implementasi Virtual Private Network Pada Jaringan Multi Protocol Label Switching Traffic Engineering

Along with the development of telecommunications technology, we need a network that provides traffic services to send data to distant places quickly but does not forget about security, some solutions are the Multi Protocol Label Switching method, Virtual Private Network, and Traffic Engineering. MPLS VPN TE is a combination of several methods that can be used for this problem. In this research, simulation is carried out using GNS3 software and the results of the analysis are carried out using a Wireshark software. This scenario uses the measurement load using FTP and HTTP. The measurement parameters of QoS are transfer time, throughput, delay, and packet loss ratio. The measurement results show that QoS value for transfer time of 25 MB file is 16.94s, and transfer time for HTTP is 4.2 s. The Throughput of 25 MB file is 1.606MB/s, and throughput for HTTP is 5.6 MB/s. The Delay of 25MB file is 1.22 ms, and delay HTTP is 105.37 ms

Leveraging DICE (Discretely-Integrated Condition Event) Simulation to Simplify the Design and Implementation of Hybrid Models

Using an example of an existing model constructed by the National Institute for Health and Care Excellence (NICE) to inform a real health technology assessment, this study seeks to demonstrate how a discretely integrated condition event (DICE) simulation can improve the implementation of Markov models. Using the technical report and spreadsheet, the original model was translated to a standard DICE simulation without making any changes to the design. All original analyses were repeated and the results were compared. Aspects that could have improved the original design were then considered. The original model consisted of 32 copies (8 risk strata× 4 treatments) of the Markov structure, containing more than 6000 Microsoft Excel® formulas (18 MB files). Three aspects (nonadherence, scheduled treatment stop, and end of fracture risk) were handled by incorporating weighted averages into the cycle-specific calculations. The DICE implementation used 3 conditions to represent the states and a single transition event to apply the probabilities; 3 additional events processed the special aspects, and profiles handled the 8 strata (0.12 MB file). One replication took 16 seconds. The original results were reproduced but extensive additional sensitivity analyses, including structural analyses, were enabled. Implementing a real Markov model using DICE simulation both preserves the advantages of the approach and expands the available tools, improving transparency and ease of use and review.

Terror of 10 MB, a cross-sectional study investigates the regulation to the prospective of medical device

An instrument, apparatus, implement, machine, implant, in vitro reagent, a component part or accessory which Intended for use in diagnosis of disease or other condition, or in the cure, mitigation and treatment or prevention of disease is called medical devices. Medical devices under new rule classified as Class A (low risk), Class B (low moderate risk), Class C (moderate high risk), and Class D (high risk) commemorating the notification of January 31, 2017 of Ministry of Health and Family Welfare which is conformity with Global Harmonisation Task Force framework. As per make in India program, the industry of medical devices is USD 5.2 billion and is contributing 4%–5% to the USD 96.7 billion Indian health-care industry. A total of 750–800 medical device manufacturers in India, an average investment of Rs 170–200 million and an average turnover of Rs 450–500 million. An online licensing portal of the Central Drugs Standard Control Organization (CDSCO) called “Sugam portal” has been launched on November 14, 2015, to file application and grant permission of registration exclusively for Medical Device CDSCO MD Online portal. By making the document submission easier, there are lot of challenges also present in “Sugam-online Portal.” One of the main challenges in Sugam Portal is that there is no provision to upload files greater than 10MB file size. The current study addresses the issues and challenges faced by medical device industry and regulators with their potential solutions and recommendations.

The Development of Plant Encyclopedia Based on Datebase in Adiwiyata Senior High School

SMA Negeri 1 Cawas does not have a digital inventory of plants. Digital inventory can be stored for long time and updated. The study aims to develop an encyclopedia of-based plants database in adiwiyata schools. Research design with Research and Development (RnD). The steps include analysis of potential and problems; data collection; product design; design validation by media experts (lecturers and media experts BPMPK) and material experts (expert classification lecturers); revision 1; small-scale trials (for biology teachers, Wakakur and responses by class XI MIA students 2); revision 2; large-scale trials (all students of class XI MIA); revision 3; and the final product. Based on the results of the study there were 46 plant species. Encyclopedia design (Ensiya) includes templates, systems coding, and finalization program. Ensiya is used to facilitate the management of plant inventories. Revision 1, carried out on the program name, label, motivation, and location of the outbox. Revision 2 of the program name; label box size; motivation box and outbox. The results of a large-scale trial, Ensiya obtained a very feasible assessment by students and received positive responses. Revision 3, program name font; picture box; motivation, and the location of the outbox. Conclusion of this study, that the plant encyclopedia (Ensiya) in the database-based adiwiyata school was successfully developed using Microsoft Visual Basic Express. Ensiya digital documents, 165 MB file size, accessed offline, transferred between computers with data transfer, and can be changed by studying Microsoft Visual Basic Express programming, is very valid and very feasible.

Study of E-mail Data Services based on Delay Tolerant Network in The Riau Province Border Region

Indonesia is an archipelagic country that is geographically unique, where most of the land has uneven land contours because it consists of mountains and valleys. This condition is one of the causes of the inequality of information dissemination even though the ICT infrastructure has supported and internet services are also available. Topographical factors and inequality of information dissemination pose digital deviations in the community, especially border areas in Riau Province which have not been able to enjoy internet services in some of the regions. Even though the process of data transmission to other regions is needed by both government agencies placed in border areas and the general public who need internet services for data transmission (text, audio, and video). Delay Tolerant Network (DTN) technology is a network protocol that allows communication networks to be applied in extreme environments that have long delay characteristics, high loss rates, and low connectivity levels. With DTN, internet services can be implemented and presented cheaply using only DTN Router which will move to areas that are not reachable by the internet and collect email data digitally. Furthermore, DTN Router and processes every transmission request from/to the border regions with extreme topography. By using the Flooding method applied to the DTN protocol, testing of e-mail data packet transmission from simulations at several locations in Riau is considered to have high data loss. Testing modeled by several computers with DTN, doing a bundle of data packages, transmitting to destinations and assessing the efficiency of their success. The test results show that the data transmission process in extreme areas using DTN protocol, Indicates that the larger the size of the file sent. So, the greater the time needed for data transmission. Approximate of time is needed of transmission data of the 95MB file that is 4,1 second..

THE AUDIO VIDEO OF WEB-BASED COMPRESSION WITH FFMPEG

In general, video compression only compresses video files without compressing the audio files in them. This results in the compression process not being maximized.This study discusses the process of compressing video and audio files to get maximum compression. The application built is a web-based video compression software utilizing FFmpeg to do the compression process by breaking down the original video which has a resolution of 720 to 4 files, namely 720, 480, 360, and 240 resolutions. The test is done by comparing the compression results only to video files and compressing to video and audio and there is a 1-2 MB file size difference, whereas when compared to the original file, there is a 5-20 MB size difference. In addition to conducting this test also performed compression testing on different devices and obtained relatively similar results on all devices. Test the image quality on the compressed file obtained the image quality results in the standard video compression below 30dB results.

Cluster-to-cluster data transfer with data compression over wide-area networks

The recent emergence of ultra high-speed networks up to 100 Gb/s has posed numerous challenges and has led to many investigations on efficient protocols to saturate 100 Gb/s links. However, end-to-end data transfers involve many components, not only protocols, affecting overall transfer performance. These components include disk I/O subsystem, additional computation associated with data streams, and network adapters. For example, achievable bandwidth by TCP may not be implementable if disk I/O or CPU becomes a bottleneck in end-to-end data transfer. In this paper, we first model all the system components involved in end-to-end data transfer as a graph. We then formulate the problem whose goal is to achieve maximum data transfer throughput using parallel data flows. We also propose a variable data flow GridFTP XIO stack to improve data transfer with data compression. Our contributions lie in how to optimize data transfers considering all the system components involved rather than in accurately modeling all the system components involved. Our proposed formulations and solutions are evaluated through experiments on the ESnet 100G testbed and a wide-area cluster-to-cluster testbed. The experimental results on the ESnet 100G testbed show that our approach is several times faster than Globus Online—8 × faster for datasets with many 10 MB files and 3–4 × faster for other datasets of larger size files. The experimental results on the cluster-to-cluster testbed show that our variable data flow approach is up to 4 × faster than a normal cluster data transfer.

Performance Metrics of Multipath State Aware Concurrent Multipath Transfer using Redundant Transfer in Stream Control Transmission Protocol Multihoming for Symmetric Paths

Problem statement: In multihomed host, if data transfer starts using CMT, unaware of paths status causes delay in data transfer or packet loss due to path failure. Transmission Path (one or more paths) failures result in out-of-order data delivery causing receiver buffer blocking and preventing sender from transmitting further data. Approach: Multipath State Aware Concurrent Multipath Transfer using Redundant Transfer (MSACMT-RT), status of multipath is determined, initially and periodically before transmission. Data transfer begins immediately after determining the path status, for a particular interval of time and later transfers with CMT only for predefined period. Results: We discuss MSACMT-RT performance in symmetric paths with the constrained receiver buffer (rbuf) value of 128 and 256KB’s. Our simulation result shows Percentage of throughput Increase between 5-15% for transfer of 20 and 40MB file sizes. Conclusion: By using MSACMT-RT we infer that our algorithm outperforms on par or better but never worse than Concurrent Multipath Transfer Potentially Failed (CMT-PF). MSACMT-RT mechanism in alternate paths increases the throughput during aggressive failures and Non-failure scenarios. Larger the file sizes of file transfer, greater the degree of throughput with less transfer time is achieved.