Bytes Of Data Research Articles

Bead-Based DNA Synthesis and Sequencing for Integrated Data Storage Using Digital Microfluidics.

DNA is considered as a prospective candidate for the next-generation data storage medium, due to its high coding density, long cold-storage lifespan, and low energy consumption. Despite these advantages, challenges remain in achieving high-fidelity, fully integrated, and cost-efficient DNA storage system. In this study, a homemade digital microfluidic (DMF)-based compact DNA data storing pipeline is orchestrated to complete the entire process from the synthesis to the sequencing. The synthetic half employs phosphoramidite chemistry on 200 nm magnetic beads (MBs), where the dimethyltrityl protecting group is removed by droplet manipulation of trichloroacetic acid. The sequencing counterpart relies on pyrophosphate releasing originated from polymerase-catalyzed primer extension, which leads to photon-countable chemiluminescence (CL) signal in 2.5-μL drops of trienzyme cascading reactions. Further by DNA denaturation, repeated pyrosequencing plus plurality voting can improve the nucleobase accuracy beyond 95 %. As a proof-of-concept trial, semantic information is saved in DNA via the Huffman coding algorithm plus the Reed-Solomon error-correction, and then robustly retrieved from this streamlined platform. As a result, it took a net total of approximately 6.5 h to writing and reading 8 bytes of data, that equal to a storaging speed of 49 min/byte, much quicker than the previously reported 2.8-4.2 h/byte. This bead-based miniaturized device promises an unattended protocol for achieving high-throughput, full-packaged, and above all, neatly precision DNA storage.

Implementation of Least Significant Bit Steganography to Secure Text Messages in Images

Steganography is a technique of securing secret messages in other messages that are not known. Simulation of the steganography method using the Least Significant Bit technique is used to change the last bit in one byte of data by using a text message as the container medium. This study aims to implement the security of text messages in images using the Least Significant Bit technique which is supported by the steganography method. Simulation techniques are used to conduct studies using Cryptool2 which can describe the concept of cryptography. The results obtained from this study regarding the security of text message insertion into an image in *.jpg and *.png format with 5 sampling trials are (1) the encrypted image cannot be distinguished directly through human eyes, (2) there is an increase in file size the image after being encrypted with an average for five trials is 0.31%, this increase depends on the length of the text message and a key to be inserted, the longer the insertion, the larger the resulting file size, (3) The higher the resolution of the image where the description encryption is inserted, the longer the process required, (4) The simulation time of steganographic decryption is faster than steganographic encryption. The decryption simulation process is the same as 50% of the encryption process.

Internet of Things Security Design Based on Blockchain and Identity Re-encryption

With the development of IoT technology, IoT devices have penetrated various fields, such as smart homes, industrial automation, healthcare, etc. However, the security issues of IoT devices have always troubled people. Attackers can use various means to attack IoT devices, such as stealing data, tampering with programs, malware infection, etc. These attack methods will bring great losses to users. In response to the above issues, this study uses proxy re-encryption technology to transform data collected by IoT devices into ciphertext. Then, it stores the encrypted IoT data on the blockchain. The combination of blockchain and proxy re-encryption technologies offers a method for the secure sharing of IoT data. The experimental results show that whether the algorithm encrypts a small or large amount of data, the encryption time is relatively short, and the time consumption does not exceed 15 ms. When encrypting 8196 bytes of data, its encryption time is 50% lower than the Attribute-Based Encryption (ABE) algorithm. The proposed IoT data security sharing method has the advantages of high security, fast encryption speed, and good stability, which helps to improve the security performance of the IoT and provides a new approach to IoT security.

A Literature Review for Detection and Projection of Cardiovascular Disease Using Machine Learning

The heart is a vital organ that is indispensable in ensuring the general health and welfare of individuals. Cardiovascular diseases (CVD) are the major health concern worldwide and a leading cause of death, leaving behind diabetes and cancer. To deal with the problem, it is essential for early detection and prediction of CVDs, which can significantly reduce morbidity and mortality rates. Computer-aided techniques facilitate physicians in the diagnosis of many heart disorders, such as valve dysfunction, heart failure, etc. Living in an "information age," every day million bytes of data are generated, and we can turn these data into knowledge for clinical investigation using the technique of data mining. Machine learning algorithms have shown promising results in predicting heart disease based on different risk parameter. In this study, for the purpose of predicting CVDs, our aim is to appraise and examine the outputs generated by machine learning algorithms including support vector machines, artificial neural network, logistic regression, random forest and decision trees.This literature survey highlights the correctness of different machine learning algorithms in forecasting heart problem and can be used as a basis for building a Clinical decision-making aid to detect and prevent heart disease at an early stage.

Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System.

As the number of Internet of Things (IoT) devices continues to rise dramatically each day, the data generated and transmitted by them follow similar trends. Given that a significant portion of these embedded devices operate on battery power, energy conservation becomes a crucial factor in their design. This paper aims to investigate the impact of data compression on the energy consumption required for data transmission. To achieve this goal, we conduct a comprehensive study using various transmission modules in a severely resource-limited microcontroller-based system designed for battery power. Our study evaluates the performance of several compression algorithms, conducting a detailed analysis of computational and memory complexity, along with performance metrics. The primary finding of our study is that by carefully selecting an algorithm for compressing different types of data before transmission, a significant amount of energy can be saved. Moreover, our investigation demonstrates that for a battery-powered embedded device transmitting sensor data based on the STM32F411CE microcontroller, the recommended transmission module is the nRF24L01+ board, as it requires the least amount of energy to transmit one byte of data. This module is most effective when combined with the LZ78 algorithm for optimal energy and time efficiency. In the case of image data, our findings indicate that the use of the JPEG algorithm for compression yields the best results. Overall, our research underscores the importance of selecting appropriate compression algorithms tailored to specific data types, contributing to enhanced energy efficiency in IoT devices.

DEVELOPMENT OF NOVEL COMPARISON BASED STEGANOGRAPHY ALGORITHMS ON MULTIMEDIA TO HIDE PRIVATE DATA

Throughout history, humanity has had secrets to safeguard, information that needed to be conveyed to allies in a way that enemies couldn't decipher. To achieve this goal of safeguarding important and valuable information, cryptography and steganography have been frequently used methods both in the past and in today's world. This article introduces a steganographic algorithm designed for hiding data in the color images, along with two different algorithm designs derived from this method. The bits of the hidden message are embedded sequentially into each pixel using the bit comparison. The comparison method works by matching the bits of the image and the message. The least significant bits (LSB) of the carrier (cover) image bytes change depending on the number of matching bits between the carrier image and the hidden message. The proposed method has the potential to hide 1 byte of data within 5 bytes under optimal conditions. The designed algorithms have been tested on a series of color images, and satisfactory results have been achieved in terms of embedding a sufficient amount of data into the images without compromising image quality. The results have been compared with the results of the LSB technique and similar methods based on various performance criteria.

A comparative analysis of big data processing paradigms: Mapreduce vs. apache spark

The paper addresses a highly relevant and contemporary topic in the field of data processing. Big data is a crucial aspect of modern computing, and the choice of processing framework can significantly impact performance and efficiency. The technical revolution of big data has changed how organizations handle and value large databases. As data quantities expand quickly, effective and scalable data processing systems are essential. MapReduce and Apache Spark are two of the most popular large data processing techniques. This study compares these two frameworks to determine their merits, shortcomings, and applicability for big data applications. Nearly quintillion bytes of data are created daily. Approximately 90% of data was produced in the previous two years. At this stage, data comes from temperature sensors, social media, movies, photographs, transaction records (like banking records), mobile phone conversations, GPS signals, etc. In this article, all key big data technologies are introduced. This document compares all big data technologies and discusses their merits and downsides. Run trials using multiple data sets of varying sizes to validate and explain the study. Graphical depiction shows how one tool outperforms others for given data. Big Data is data generated by the rapid usage of the internet, sensors, and heavy machinery, with great volume, velocity, variety, and veracity. Numbers, photos, videos, and text are omnipresent in every sector. Due to the pace and amount of data generation, the computing system struggles to manage large data. Data is stored in a distributed architectural file system due to its size and complexity. Big distributed file systems, which must be fault-tolerant, adaptable, and scalable, make complicated data analysis dangerous and time-consuming. Big data collection is called ‘datafication’. Big data is ‘datafied’ for productivity. Organisation alone does not make Big Data valuable; we must choose what we can do with it.

Double graph correlation encryption based on hyperchaos.

Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been proposed to meet this requirement, among which encryption can be considered as one of the first and most effective solutions. The continuous increase in the computational power of computers and the rapid development of artificial intelligence techniques have made many previous encryption solutions not secure enough to protect data. Therefore, there is always a need to provide new and more efficient strategies for encrypting information. In this article, a two-way approach for information encryption based on chaos theory is presented. To this end, a new chaos model is first proposed. This model, in addition to having a larger key space and high sensitivity to slight key changes, can demonstrate a higher level of chaotic behavior compared to previous models. In the proposed method, first, the input is converted to a vector of bytes and first diffusion is applied on it. Then, the permutation order of chaotic sequence is used for diffusing bytes of data. In the next step, the chaotic sequence is used for applying second diffusion on confused data. Finally, to further reduce the data correlation, an iterative reversible rule-based model is used to apply final diffusion on data. The performance of the proposed method in encrypting image, text, and audio data was evaluated. The analysis of the test results showed that the proposed encryption strategy can demonstrate a pattern close to a random state by reducing data correlation at least 28.57% compared to previous works. Also, the data encrypted by proposed method, show at least 14.15% and 1.79% increment in terms of MSE and BER, respectively. In addition, key sensitivity of 10-28 and average entropy of 7.9993 in the proposed model, indicate its high resistance to brute-force, statistical, plaintext and differential attacks.

A novel package of key generation and integrity validation in symmetric key cryptography

In this paper we presents a new cryptography method on symmetric key Cryptography along with that it will ensure the integrity of the data during the transmission. Here encryption and decryption operation is performed on bit stream of data. It is suitable for any type of text files. This method of encryption is simple and powerful to secure data in network against passive attack like traffic analysis to provide data confidentiality. The Cryptography package deals with generating a simple encryption key by choosing a byte of data in the plaintext. By using that secure encryption key Plain text is converted to cipher text and in the destination Cipher text is converted to plain text by performing basic XOR and other operation. To ensure integrity of data available parity bit methods are applied.

Child drowning prevention: GPS and LoRa based emergency alert system

UNICEF recently published in the "Country Office Report 2021" about the mortality of children in Bangladesh, "Every day, 30 children die from drowning – Bangladesh's second leading cause of under-five mortality. Drowning is preventable, and most cases occur within a child's home community." Bangladesh is a country of rivers, which means Bangladesh called a riverine country located in South Asia. The Center for Injury Prevention and Research conducted a survey, Around 19000 people of (all types of ages) drown every year in Bangladesh. Among them, 14500 which mean 77% are children. In our research, the emergency alert system is designed to be cost-effective and user-friendly for village communities in Bangladesh. The system is divided into two components: the kid is equipped with the transmitter, and the receiver is placed at home. The transmitter and receiver both use a LoRa transmission module that can communicate accurately within a 300-meter range (coverage up to 10 Kilometers) and can transmit 256 bytes of data. The transmitter collects geolocation data using a GPS module and sends the data to the receiver using the LoRa module. The receiver module is configured by setting up the geolocation of risky places. The receiver will send SMS or buzzing the receiver to alert the parents when the transmitter or kid is nearby risky places. The Equirectangular approximation method calculates the distance between children's positions from risky areas. Additionally, the transmitter and receiver may communicate encrypted messages using AES 128-bit symmetric encryption technology compatible with Arduino Nano controller. Thus, our emergency alert system can save children from drowning in the home environment.

Enhancing Data Security: A Cutting-Edge Approach Utilizing Protein Chains in Cryptography and Steganography

Nowadays, with the increase in cyber-attacks, hacking, and data theft, maintaining data security and confidentiality is of paramount importance. Several techniques are used in cryptography and steganography to ensure their safety during the transfer of information between the two parties without interference from an unauthorized third party. This paper proposes a modern approach to cryptography and steganography based on exploiting a new environment: bases and protein chains used to encrypt and hide sensitive data. The protein bases are used to form a cipher key whose length is twice the length of the data to be encrypted. During the encryption process, the plain data and the cipher key are represented in several forms, including hexadecimal and binary representation, and several arithmetic operations are performed on them, in addition to the use of logic gates in the encryption process to increase encrypted data randomness. As for the protein chains, they are used as a cover to hide the encrypted data. The process of hiding inside the protein bases will be performed in a sophisticated manner that is undetectable by statistical analysis methods, where each byte will be fragmented into three groups of bits in a special order, and each group will be included in one specific protein base that will be allocated to this group only, depending on the classifications of bits that have been previously stored in special databases. Each byte of the encrypted data will be hidden in three protein bases, and these protein bases will be distributed randomly over the protein chain, depending on an equation designed for this purpose. The advantages of these proposed algorithms are that they are fast in encrypting and hiding data, scalable, i.e., insensitive to the size of plain data, and lossless algorithms. The experiments showed that the proposed cryptography algorithm outperforms the most recent algorithms in terms of entropy and correlation values that reach −0.6778 and 7.99941, and the proposed steganography algorithm has the highest payload of 2.666 among five well-known hiding algorithms that used DNA sequences as the cover of the data.

Self-powered arctic satellite communication system by harvesting wave energy using a triboelectric nanogenerator

Previous studies reported that the electrical output of triboelectric nanogenerator (TENG) materials is higher at low temperatures (below −20 °C) than at room temperature, indicating that a TENG device may be suitable in low-temperature environments such as the Arctic Ocean. However, research on TENG systems for extreme weather conditions (temperatures as low as) −40 °C is lacking. This paper presents the design of Arctic-TENG, which efficiently generates electricity to power a satellite communication system in Arctic Ocean conditions. Arctic-TENG was designed for low-temperature operations and performs better at cold temperatures than at room temperature. Using an out-of-water wave simulator at 0.2 Hz, the peak power density of Arctic-TENG reached 21.4 W/m3. Realistic energy requirements were obtained by implementing a satellite communication system, and the available energy from Arctic-TENG was measured and evaluated considering the available wave energy in the Arctic Ocean. The total energy generated per year from Arctic-TENG is 8.59 kJ. One Arctic-TENG can transmit 540 bytes of data per day over a year, which demonstrates the power supply capability of Arctic-TENG for long-term operation of a satellite communication system.

Image Watermarking Using Least Significant Bit and Canny Edge Detection.

With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today's world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB's high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks.

Smart Laboratory Using Radio Frequency Identification (RFID) Based on The Internet of Things

In Indonesia, traditional methods are still commonly used for managing laboratories. This has resulted in various issues, such as the loss of keys, and has hindered the efficiency of these laboratories. However, the integration of technology has the potential to improve laboratory management by up to 33%. A modernized laboratory system, known as an "Innovative Laboratory", combines technology with traditional management techniques. The proposed Internet of Things-based tool aims to assist laboratories in improving their management services, including a registration system, a locker system, and a desk system. This tool utilizes a Keypad 4x4 and PCF8574 to select desks and lockers, Node MCU as a microcontroller to publish identification data from an MQTT broker, and RFID technology to access and activate electronic locks and sockets. To ensure that data is successfully transferred and the selected locker and desk are available, the system requires a certain delivery time for a maximum of 251 bytes of data that can be sent at different signal strengths. Only registered users with valid identification are able to access the locker and desk systems, and users must unregister before switching to a new locker or desk. The goal of this system is to streamline and improve the management of laboratories.

A Dark (Blue) Horse Emerges to Speed Up Computing: Avicena's blue microLEDs are in a race with Ayar Lab's laser-based system

If a CPU in Seoul sends a byte of data to a processor in Prague, the information covers most of the distance as light, zipping along with no resistance. But put both those processors on the same motherboard, and they'll need to communicate over energy-sapping copper, which slows the communication speeds possible within computers. Two Silicon Valley startups, Avicena and Ayar Labs, are doing something about that longstanding limit. If they succeed in their attempts to finally bring optical fiber all the way to the processor, it might not just accelerate computing-it might also remake it.

Distributed Intelligence in Wireless Networks

The cloud-based solutions are becoming inefficient due to considerably large time delays, high power consumption, and security and privacy concerns caused by billions of connected wireless devices and typically zillions of bytes of data they produce at the network edge. A blend of edge computing and Artificial Intelligence (AI) techniques could optimally shift the resourceful computation servers closer to the network edge, which provides the support for advanced AI applications (e.g., video/audio surveillance and personal recommendation system) by enabling intelligent decision making on computing at the point of data generation as and when it is needed, and distributed Machine Learning (ML) with its potential to avoid the transmission of the large dataset and possible compromise of privacy that may exist in cloud-based centralized learning. Besides, the deployment of AI techniques to redesign end-to-end communication is attracting attention to improve communication performance. Therefore, the interaction of AI and wireless communications generates a new concept, named native AI wireless networks. In this paper, we conduct a comprehensive overview of recent advances in distributed intelligence in wireless networks under the umbrella of native AI wireless networks, with a focus on the design of distributed learning architectures for heterogeneous networks, on AI-enabled edge computing, on the communication-efficient technologies to support distributed learning, and on the AI-empowered end-to-end communications. We highlight the advantages of hybrid distributed learning architectures compared to state-of-the-art distributed learning techniques. We summarize the challenges of existing research contributions in distributed intelligence in wireless networks and identify potential future opportunities.

IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database.

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.

Cybersecurity and Mental Health in the Digital Age

More than half of the world population is connected through the Internet and end users and professionals alike spend many hours on it to communicate, research, work, collaborate and socialize, generating millions of bytes of data daily. Cybercriminals are also taking the advantage to hack systems and steal or corrupt data, disrupt operations and the level and intensity cyber-attacks have increased tremendously, since the Russia invasion of Ukraine. Individuals who have been affected by cybersecurity breaches have been known to develop increased anxiety levels, fear of others online, leading to depression. Cybersecurity professionals are also under pressure to perform and continually prevent attacks and protect information assets. Many of these incident responders have experienced workplace stress, burnout, depression, suicidal thoughts and some quitting the cybersecurity industry due to pressures to keep away all cyber- attacks. All these scenarios of cybersecurity breaches have implications on mental health. This paper did a systematic review to find correlations between cybersecurity and mental health. The findings revealed that as a result of cybersecurity breaches, both users and professionals have developed mental health conditions including anxiety, stress, burnout, depression, suicide thoughts and some professionals quitting the industry and further increasing the skills shortage. The paper concluded that there is a positive correlation between cybersecurity breaches and mental health and we should all be conscious of this and balance our work-life lifestyle; employers should encourage discussions around mental health, provide counselling services and invest in cybersecurity resources and further education to motivate professional staff and reduce cybersecurity skills shortage. Keywords — Cybersecurity, Mental Health, Digital Age, Industry, Cyberspace, Lifestyle

Reconfigurable data encoding schemes for on-chip interconnect power reduction in deep submicron technology

With technology scaling, size of both transistor and interconnects are reduced. Power dissipation due to dynamic switching is high in the interconnects. Suitable encoding schemes that reduces transition between data bits are used to minimize interconnect power dissipation. In this paper transition between data bits is minimized based on three novel data encoding schemes identifying the novel methods estimates bit transitions in a pair of data bits and performs half inversion or full inversion on one byte of data thus reducing the switching activity by 50%. The encoder and decoder for the three encoding schemes are modelled in verilog hardware description language (HDL) and implemented using application specefic integrates circuit (ASIC) flow targeting 32 nm. Technology over all power dissipation of encoding scheme is 1.04 μW in addition over head area of 210 cells with encoding delay of 340 ps. Encoder decoder register transfer logic (RTL) code is implemented and the total area required is 34980 units. The data encoding and decoding schemes are suitable for low power applications.

Energy consumption of an internet of things development board

Internet of Things is a highly applicable technology due to its versatility in areas such as agronomy, health applications, and industry. Besides, portability makes these devices affordable. IoT development boards communicate through Wi-Fi transmitted messages via the Internet, depending on the inner workings of the IoT development board, energy consumption can vary in such transmission. Furthermore, this consumption could change if the board is powered by different power supplies and the quantity of Wi-Fi transmitted messages. This paper provides a methodology to acquire an energy profile when sending data (byte) using Message Queue Telemetry Transport (MQTT) protocol on DEVKIT V1 NodeMCU-32 (ESP32) development board. Three different power supplies were used for the board, a 3.7 LiPo Battery, 5v usb Power bank and 9V NiMh rechargeable battery. The higher current consumption obtained was using a 3.7 battery, followed by 5v and the lowest current consumption was when using 9v. However, results demonstrate that when using the 9v power supply the energy consumption is two times higher than using 3.7v. Therefore, the best voltage source for transmission and energy consumption using a NodeMCU-32 development board will be 3.7 volts.