The Internet of Things (IoT) is a rapidly growing network of interconnected devices that collect and exchange data. While IoT devices offer many benefits, they also pose unique security and energy management challenges. One promising approach to addressing these challenges is to develop new hashing algorithms that are both secure and energy-efficient. This paper proposes a new hashing algorithm for IoT devices based on multi-level hashing and the SHA family, called the Multi-Level Hashing Algorithm (MLHA). The MLHA consists of eight levels, starting from a lightweight level to a heavy level. Each level is based on a different modified SHA function, with the heavier levels using more complex SHA functions. The output of each level is then produced and represents the final hash value. The use of multiple levels provides several advantages. First, it makes the algorithm more resistant to brute-force attacks. Second, it allows the algorithm to be tailored to the specific security requirements of the IoT device. For example, a device with limited resources may use a lower of level, while a device with more resources may use upper levels for increased security. The use of SHA functions also provides several advantages. First, SHA functions are well-studied and well-respected. Second, SHA functions are relatively efficient to implement in hardware. The number of levels can be easily adjusted to meet the specific needs of the IoT device. The MLHA can also be used to create different types of hash functions. For example, a collision-resistant hash function can be created by using a large number of levels and complex SHA functions. The MLHA is a promising new approach to hashing for IoT devices. The algorithm is efficient, secure, and energy-saving. It is also flexible and scalable, making it suitable for a wide range of IoT devices, from devices with limited resources to devices with complex resources such as supercomputers. The MLHA was evaluated on a variety of IoT devices, including Raspberry Pi 4B hardware, and on two different operating systems, Windows and Ubuntu. The results showed that the MLHA is both secure and energy-efficient. The fact that the MLHA was tested on two different operating systems and on a variety of IoT devices, including a Raspberry Pi 4B, demonstrates the algorithm's portability and versatility. This is important because it means that the MLHA can be used in a wide range of IoT applications.

The Internet of Things (IoT) has grown dramatically in recent years, it is due to its big impact on people's daily life in critical applications like healthcare, smart homes, smart cities, and smart everything. It also attracts industries and researchers to work on this technology. IoT devices are susceptible to be compromised because of their network capacities, very low computing power, limited battery life, and data storage. The biggest obstacle to the adoption of IoT systems has been recognized as the requirement for lightweight and energy-efficient security solutions to secure smart devices and stored data. In this paper we have reviewed fourty five papers that are related to IoT hashing algorithms and its optimizations, and the papers were published from 2018 and 2022. The papers were then filtered and analyzed. After filtration process, fourteen papers were removed from the list, since they were not totally pertinent to the problem and thirty one papers left for analysis. Among these papers. Among of these thirty one papers, eighteen studies (58%) are focusing on Application layer security, more specifically they focused on Authentication in IoT System.

The internet is referred to as cloud computing, is the process of using computing technologies to carry out all of our everyday activities. As a result, we may define Cloud computing as internet-based computing. With cloud hosting, many end-users may access the database without caring about the database's structure or the database's storage and maintenance. As a result, having a fault-free machine is essential. As the market for cloud storage grows, it's more critical than ever to deliver accurate resources even though they're broken. Cloud storage resources may be dynamically scaled while being cost-effective. The method of detecting flaws and defects in a device is known as fault tolerance. If a problem happens, such as hardware or a program malfunction, the device can function normally. For dependable Cloud Computing, failures must be effectively handled. It would also guarantee availability and reliability. This paper seeks to provide readers a greater understanding of fault tolerance strategies for cloud fault management. It also discusses some of the latest fault-tolerance models.

There have been a growing number of academics and developers who have appeared in recent years, and they have spent a significant amount of their time and attention to researching GPU, as well as the numerous sectors in which it plays an essential and successful function. This is in part due to the immense progress that the world is seeing on a daily basis, which includes a variety of disciplines of study such as medical, engineering, space, and precise sciences that demand high-resolution visual representation and vast graphic processing power. This article acts as a review and provides a condensed description of the development, applications, problems, and related research into GPU across a wide number of various industries. It should not come as a surprise, given all of these benefits, that cloud computing has become the standard practice in its business in such a short length of time. The movement of corporate operations to the cloud, which is being done by a growing number of companies, is being done in an effort to minimize the amount of time spent on infrastructure maintenance. This migration is taking place for the following reasons: As a consequence of this, preserving a cloud environment in such a manner that it continues to operate normally is a tremendously challenging endeavor. If you want to increase cloud performance and minimize the amount of administrative stress you suffer, you need a reliable cloud monitoring solution. The cloud monitoring service is an investment that is well worth making since there is a possibility that it will boost performance and minimize the amount of time that is spent managing. One of the most important roles of cloud monitoring is the management of Quality of Service (QoS) metrics for cloud-hosted, virtualized, and physical services and applications.

Cloud Computing is one of the most common methods of distributed computing because it can reduce computing costs as data processes are improved in scalability and versatility. However, as a consequence of the continued influx in knowledge, many companies drowned in data and the resultant" data deficit" or failure to process and efficiently use this information was growing at an unprecedented pace. Consequently, computer systems are getting more data-intensive due to the proliferation of data and the need to process the data and storage management of such data-intensive computing systems is crucial to the application efficiency. In this paper, we explain what cloud computing is, its types, characteristics, and challenges that cloud computing faces. Then we review what data-intensive technology is, what the architecture of data-intensive systems is, what the characteristics of these systems are, and what are the requirements of data-intensive technology for cloud computing. Then, we reviewed 20 of the related work on data intensive in cloud computing. Finally, we compared and discuss compare the most important techniques and algorithms and the results obtained from number of previous works.

The Internet of Things (IoT) has developed as a disruptive technology with wide-ranging applications across several sectors, enabling the connecting of devices and the acquisition of substantial volumes of data. Nevertheless, the rapid expansion of networked gadgets has generated substantial apprehensions pertaining to security and energy administration. This survey paper offers a detailed examination of the present state of research and advancements in the field of Internet of Things (IoT) security and energy management. The work places special emphasis on the use of hashing algorithms in this context. The security of the Internet of Things (IoT) is a crucial element in safeguarding the confidentiality, integrity, and availability of data inside IoT environments. Hashing algorithms have gained prominence as a fundamental tool for enhancing IoT security. This survey reviews the state of the art in cryptographic hashing techniques and their application in securing IoT devices, data, and communication. Furthermore, the efficient management of energy resources is essential to prolong the operational lifespan of IoT devices and reduce their environmental impact. Hashing algorithms are also instrumental in optimizing energy consumption through data compression, encryption, and authentication. This survey explores the latest advancements in energy-efficient IoT systems and how hashing algorithms contribute to energy management strategies. Through a comprehensive analysis of recent research findings and technological advancements, this survey identifies key challenges and open research questions in the fields of IoT security and energy management based on hashing algorithms. It provides valuable insights for researchers, practitioners, and policymakers to further advance the state of the art in these critical IoT domains.

The Internet of Things (IoT) has emerged as a significant technological advancement in recent years. Its development has garnered global attention from many organisations, industries and researchers. The IoT is responsible for collecting and processing data from remote areas, significantly enhancing productivity for distributed systems and individuals. Secure hash algorithms (SHAs) are critical to ensuring enhanced security levels within IoT ecosystems. These algorithms generate fixed-size hash values from input data, making them useful for various security applications. This paper proposes a new multi-level hashing algorithm (MLHA) that could overcome challenges and significantly impact IoT security. The proposed MLHA was carefully considered and managed to effectively enhance IoT security without compromising the performance and efficiency of IoT devices. The new hashing algorithm is suitable for all IoT devices, ranging from small devices with limited processing power fuelled by batteries to larger devices with constant electrical power and vast resources. This study’s main objective is to develop a new hashing algorithm specifically designed for IoT devices. This research strives to enhance IoT devices’ data protection and security measures using improved hashing algorithms. This objective will be achieved by examining various IoT devices, analysing current algorithms and developing strategies that effectively balance efficiency and security. Furthermore, the suggested algorithm presents a novel methodology for enhancing data security in IoT devices. The algorithms examined in this paper are from the SHA family, which are based on bitwise operations. However, these algorithms were modified to enhance their efficiency and scalability for IoT devices. The proposed algorithm comprises eight levels, each accommodating a particular IoT device. The first level is characterised by its basic nature and is specifically tailored for devices with limited resources, including low RAM and CPU and battery capacity. As the process of iterative evolution progresses, each level demonstrates adaptability to the capabilities of various IoT devices. Moreover, the algorithm progresses towards its higher levels, which are characterised by complex equations, functions, output lengths, more words, increased arithmetic and logical operations and iterations. These advanced levels of the proposed algorithm were designed to cater to larger, more complex IoT devices than the initial-stage devices.

The pandemic of COVID-19 obliges citizens to follow the “work from home “scheme. The Internet is also a powerful channel for social connections. The huge dependency of people on digital media opens doors to fraud. Phishing is a form of cybercrime that is used to rob users of passwords from online banking, e-commerce, online schools, digital markets, and others. Phishers create bogus websites like the original and deliver users spam mails. When an online user visits fake web pages via spam, phishers steal their credentials. As a result, it is important to identify these forms of fraudulent websites until they do any harm to victims. Inspired by the ever-changing existence of phishing websites. This paper reviews the work on Phishing attack detection and aims to examine techniques that mainly detect and help in preventing phishing attacks rather than mitigating them. Here we offered a general overview of the most effective phishing attack detection strategies focused on deep learning.

Web servers and service-oriented architectures have become critical technologies in the growth of loosely coupled and distributed applications. Web services present new research problems, owing to the fact that they are used to execute mission-critical and complex enterprise process structures. The architecture and infrastructure approaches are needed in this context to ensure service quality. This paper presents the most current survey on different web service frameworks, such as REST web services, standard DICOM archive, web pathology viewer, GeoFog4Health, E-mobility architecture, and so on. The aforementioned services have been used to solve issues like performance, fog availability, privacy, multimedia services, web service efficiency, and so on. Aside from that, the author used explanations of the Methods/Tools, goals; challenges, applied field, and significant outcomes, as well as the findings obtained using this methodology.

Given how recent cloud computing is and how rapidly it is becoming more widespread, doing research on this topic is almost certainly going to be a very fruitful experience. We explore and compare the use of highperformance cloud computing in a variety of business contexts as part of the scope of this research project. In addition to this, we provide a method for the descriptive assessment and classification of previous work in the field of cloud computing research. The articles and the findings they reach are structured in accordance with a set of criteria that includes the objective, applications, proposed approach, and technical instrument. This set of criteria is used to organize the articles and the conclusions they reach. The papers and the conclusions that they reach were arranged according to this set of criteria that was applied. The findings of this study suggest that it will serve as a reference source for the utilization of high performance cloud computing, which has been utilized in a variety of industries. Even though the primary focus of cloud computing research at the present time is still on technical issues such as performance, network, and data management, the findings of this study suggest that it will serve as a reference source for the utilization of high performance cloud computing. Despite the fact that the findings of this study suggest that it will serve as a reference source for the utilization of high performance cloud computing, which has been utilized in a variety of industries, this is the case regardless of the fact that the findings of this study suggest that it will serve as a reference source for the utilization of high performance cloud computing.

It is possible that the utilization of an Enterprise Architecture Framework (EAF), which describes each of the software development processes as well as the ways in which they are integrated with one another, would be of assistance to a company in achieving the goals that it has established for itself. These goals include maximizing profits, enhancing customer satisfaction, and increasing employee productivity. To put it another way, it helps companies detect defects within their systems and determine the degree to which such issues are present in the company. There have been several Enterprise Architecture Frameworks developed, and many of them are in use today. Some of these frameworks focus on very particular aspects, while others give users greater leeway in how they put them to use. The outcomes of this study present a broad range of options from which to choose an Enterprise Architecture Framework that is able to fulfill the fundamental criteria. These options can be found by clicking here. In this research, a literature review of publications associated to Enterprise Architecture Framework that have been published in a range of academic fields is presented. These articles have been published throughout the course of the last few years. Throughout the course of this study, these articles were written and published. The general public has had access to these publications throughout the course of the last several years thanks to the dissemination of information via various channels.

As the usage of ICT rises and power costs rise along with it, energy efficiency is becoming a critical factor in the development of ICT. The world's most pressing issue is the exponential growth of the global need for energy. Increased energy demands resulted from the proliferation of complex data-intensive applications, which in turn necessitated the construction of massive data centers. Cloud computing is a new method of delivering metered services to end users. Cloud computing is a method of delivering IT services and resources through virtualization over the internet. The data center is the nerve center of cloud computing, housing thousands of servers on which data and programs are stored and run. The infrastructure of a data center (the network, the servers, the air conditioning, the connections, etc.) consumes a lot of power and releases a lot of carbon dioxide. Optimizing energy consumption and developing green cloud computing systems are two of the most pressing issues in the cloud computing industry. In this article, we highlight the significance of energy efficiency by analyzing cloud computing's dual role as both a major cause of rising energy use and a method to prevent energy waste. Known energy efficiency strategies in cloud computing are compared and contrasted, and taxonomies are provided for classifying and assessing the present state of the art. The article concludes with a summary and some suggestions.

The Internet of Things (IoT) is the most common research subject. IoT is concerned with the creation of smart devices that assist people in performing a variety of tasks. Embedded systems are used to build smart devices. Embedded systems are miniature computers that allow sensor devices to collaborate to build an electronic system. In this paper, IoT in embedded systems in the various area are reviewed. Some of the major IoT technology and protocol (IoT Communication Protocols) are Bluetooth, Wifi, Radio Protocols, LTE-A, and WiFi-Direct. These IoT communication protocols cater to and meet the specific functional requirement of an IoT system. Opting for the wrong IoT communication technology will drain your connected devices of power, cause delays in data transfer, open security loopholes, and render the whole setup a failure. According to IoT Analytics, a market research company, there were 11.7 billion IoT connections in 2020 globally, and this number could swell to over 30 billion by 2025. As the Internet of Things adoption continues to grow, it’s important to carefully consider how to connect cyber-physical systems in an optimal way and avoid signal interference. There are many IoT communication protocols out there, and it can be overwhelming to sift through their specifications and determine which technology is right for your application. This article clarifies the basic terminology around IoT connectivity and introduces the most popular IoT protocols. After reading it, you will have the knowledge you need to discuss your project with IoT software development service providers and select the protocol that will help you get the most out of your Internet of Things product.

Since the beginning of this century, there has been a growing interest in the concept of Enterprise Architecture (EA), which stands for" enterprise architecture," as a means to improve and encourage strategic alignment between businesses and their IT infrastructure. EA is an abbreviation that stands for" enterprise architecture." There has been an increase in both the level of complexity and the accessibility of information collecting and processing technologies, which has led to the creation of information systems (IS) that are capable of simultaneously monitoring several elements of the operations of an organization. This was made possible as a result of the increase in both the level of complexity and the accessibility of information collecting and processing technologies. In this article, we take a look at a body of work that covers Enterprise Architecture and the effect that it has on a firm as a whole. This work focuses on the positive effects that Enterprise Architecture may have. The results were quite encouraging in that they pointed to higher productivity, decreased costs, and improved access to information for individuals tasked with decision-making.

The Internet of Things introduces rapid growth in hardware and software-based communications systems (IoT). IoT has gained a tremendous popularity in recent years and is widely used in several applications. IoT is a modern way of communication between objects and people. IoT ideas are now very influential because they create a new layer in the world of the internet. Intelligent Big Data processing and analysis is the key to intellectual IoT applications growth; logistics, transport, agriculture, health, and climate being such applications. Dynamic changes in the IoT system are caused by increasing usage of the internet and external environmental factors. To have an intellectual environment, IoT with machine learning has to be implemented. In the previous years, machinery has been widely used to recognize, extract, classify, regress, and forecast its technology. Machine learning is used to explore historical camera and sensor data and to implement network life-enhancing techniques. This article provides an insight into current research for several IoT machine learning applications. We summarize IoT strategies and tools. Additionally, we will take a look at various potential problems using summarized data. This review aims to investigate multiple IoT technologies and the impact of integrating Machine Learning into them to assist people in living in an intelligent environment.

Cloud Computing is one of the most common methods of distributed computing because it can reduce computing costs as data processes are improved in scalability and versatility. However, as a consequence of the continued influx in knowledge, many companies drowned in data and the resultant "data deficit" or failure to process and efficiently use this information was growing at an unprecedented pace. Consequently, computer systems are getting more data-intensive due to the proliferation of data and the need to process the data and storage management of such data-intensive computing systems is crucial to the application efficiency. In this paper, we explain what cloud computing is, its types, characteristics, and challenges that cloud computing faces. Then we review what data-intensive technology is, what the architecture of data-intensive systems is, what the characteristics of these systems are, and what are the requirements of data-intensive technology for cloud computing. Then, we reviewed 20 of the related work on data intensive in cloud computing. Finally, we compared and discuss compare the most important techniques and algorithms and the results obtained from number of previous works.

Many analysis technologies are being incorporated into IoT in order to make it smarter; one of the most significant technologies is data mining. Data mining is the process of extracting hidden information from big data sets and identifying new, interesting, and potentially relevant patterns. Connecting everything on the planet through the internet may seem unattainable, but the “IoT” will drastically alter our lives in the near future by making many impossible attainable. In this paper the Internet of Things (IoT) is discussed first in this article. The features of data from IoT and data mining for IoT which is consists of classification, clustering and frequent patterns are then briefly reviewed. Finally, this article discussed and concluded the data mining applications with internet of things (IoT).

With new-generation technology, the volume of data used is increasing every day. Users are encouraged to conduct day-to-day and analysis tasks in the field of data processing through technologies, which increases the automation of certain human-machine interactions around the world. The only infrastructure house proposed in today's scenario to accommodate the expanded data population is cloud data storage. With numerous services and implementation configurations, the cloud infrastructure platform aids in the management and maintenance of records. Data backup on local servers is greatly aided by outsourcing data to the cloud. However, the protection of outsourced data remains a challenge. The lack of consumer data privacy has an effect on cloud service reliability. The majority of researchers have suggested several security mechanisms that help to ensure privacy in the cloud for a specific standard. According to a study conducted by different scholars, there is currently no full privacy preservation scheme accessible in the world. A comparative analysis of cloud privacy protection strategies is presented in this article, which gives a good picture of the privacy problems and approaches for preserving privacy in cloud data storage.

In spite of the benefits afforded by wireless communications networks, maintaining the confidentiality and safety of wireless networks remains a significant obstacle and source of worry. The principal uses of wireless communication networks are found in the military, commercial, retail, transportation, healthcare, and many other fields; these systems utilise wired, cellular, or ad hoc networks. Other applications of wireless communication networks include: In recent years, a substantial amount of research attention has been focused on the Internet of Things (IoT). Looking forward, the IoT will play an important role and will affect our lives as well as the standards and business models that we now use. It is anticipated that the usage of IoT in a variety of applications would significantly rise during the next several years. The Internet of Things makes it possible for billions of different individuals, equipment, and services to connect with one another and share information. IoT networks are becoming more vulnerable to a wide variety of security threats as their usage continues to grow. In order to provide identification, secrecy, access control, and integrity, among other things, effective security and privacy protocols are an absolute need for Internet of Things (IoT) networks. This article presents a research that is both extensive and comprehensive on the topic of privacy and security in IoT.

In spite of the benefits afforded by wireless communications networks, maintaining the confidentiality and safety of wireless networks remains a significant obstacle and source of worry. The principal uses of wireless communication networks are found in the military, commercial, retail, transportation, healthcare, and many other fields; these systems utilise wired, cellular, or ad hoc networks. Other applications of wireless communication networks include: In recent years, a substantial amount of research attention has been focused on the Internet of Things (IoT). Looking forward, the IoT will play an important role and will affect our lives as well as the standards and business models that we now use. It is anticipated that the usage of IoT in a variety of applications would significantly rise during the next several years. The Internet of Things makes it possible for billions of different individuals, equipment, and services to connect with one another and share information. IoT networks are becoming more vulnerable to a wide variety of security threats as their usage continues to grow. In order to provide identification, secrecy, access control, and integrity, among other things, effective security and privacy protocols are an absolute need for Internet of Things (IoT) networks. This article presents a research that is both extensive and comprehensive on the topic of privacy and security in IoT

— Steganography science is one of the most popular field in security direction. In this research an algorithm will be adopted to embed a compressed speech inside a gray image using discrete wavelet (Haar transformation). In the beginning the speech was compressed up to its half original size then convert the speech data from decimal code to binary code and embed it inside Haar coefficients of the cover _image using the Four sub bands (LL,LH,HL,HH) which got by applying the wavelet on the cover_ image. Measuring Peak Signal to Noise Ratio (PSNR) to determine the accuracy of the stego_image with respect to the original image, MSE and the correlation factors were checked show that the proposed algorithm has positive effect in field of speech hiding.The proposed technique in this research turned out to be able to hide speech data (audio) in the cover image and then extract the hidden data with storage rate (1) bits per pixel. Hiding capacity can be achieved using this method proportionally depends on cover_image size.