Lightweight Encryption Model for IOT Security and Privacy Protection

This study aims to explore how big data and the Internet of Things can improve the economic benefits of enterprises in online marketing. We first introduced the concept and development trend of big data, Internet of Things, and Internet marketing and then collected a large number of empirical data through the design and implementation of questionnaire survey. Our data analysis results show that the level of use of big data and the Internet of Things has a significant positive impact on business sales. However, there are also some problems and challenges in the implementation of big data and the Internet of Things, such as resource and technology limitations, and legal and ethical issues such as data security and privacy protection. Therefore, we suggest that enterprises should reasonably plan the use of big data and the Internet of Things according to their own resources and capabilities, while constantly upgrading their own technical level, focusing on data security and privacy protection, and tracking the latest technology and market trends. In addition, the government and industry organizations should also formulate and improve relevant policies and standards to support the development of big data and the Internet of Things and protect the interests of consumers. In general, big data and the Internet of Things provide new opportunities and challenges for enterprise online marketing, which need further research and discussion.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

The Internet of Things (IOT) means connecting people, things, and devices in order to create an omnipresent computing world. One of the most important challenges in convincing users to adopt this kind of all-around network is the protection of security and privacy in different applications. This paper presents the results of interviews conducted in a Finnish study during 8/2012-2/2013. In this research, 11 Finnish people working with different aspects of IOT development and 11 ordinary Finnish people were interviewed. The goal was to investigate their feelings on the IOT and its applications, as well as personal opinions on security and individual privacy in the IOT. Most of the answerers in this study believed that we are heading towards the IOT in the future and many IOT applications were seen tempting. However, security and privacy issues, the lack of control, and the actual need for versatile IOT applications were questioned. The people working with the IOT were found to be more critical towards the IOT than the ordinary people. An introduction of the IOT, examples of potential applications, the conducted interviews and collected answers, as well as highlights of the collected free comments are presented in this paper.

An improvement of the Internet of Things (IoT) was forecast for changing the healthcare industry and is generating the increase of the Internet of Medical Things (IoMT). The IoT revolution was surpassed the present-day human service with promise social prospects, mechanical, and financial. During this condition, it can be essential for framing an effectual approach for guaranteeing the safety and reliability of t patient’s symptomatic information which are transmitted and received in IoT criteria. This study introduces a new data fusion model in IoT environment. The proposed model is called SSOECC-MIC model focuses on the design of effective encryption scheme with optimal key generation process for IoT environment. To achieve this, the SSOECC-MIC model designs an ECC model for the encryption and decryption of medical images effectively. To further improve the security performance of the ECC model, the optimal key generation process is carried out by the use of swallow swarm optimization (SSO) algorithm. For examining the enhanced performance of the SSOECC-MIC model, a wide ranging experimental analysis is carried out. The experimental outcomes reported the betterment of the SSOECC-MIC model over recent models.

Chapter 2 - AIoMT artificial intelligence (AI) and Internet of Medical Things (IoMT): applications, challenges, and future trends

The concept of "smart cities" The Internet of Things (IoT) is a multi-layered framework that allows cities to employ urban networks to enhance economic performance, generate innovative technological solutions, and more. Smart Cities are the result of a new age in information technology and smart economy growth, based on Internet mesh networks, communication networks, transmission networks, wireless networks, and other end-to-end sensor networks. The Internet of Things (IoT) is at the heart of it. The Internet of Things incorporates sensors into common things and links them through particular protocols for sharing data and communications over the Internet. Smart detection leads, location, monitoring, and administration are all provided by this modular architecture. A smart city of excellence must overcome three main factors: instrumented, linked, and intelligent, with the help of IoT technology. At this point of IoT development, smart cities can only arise through the interconnectedness of all of these smart elements. The goal of this essay is to learn how the Internet and sensors may assist in the development of smart cities.
 The study's main goal is to figure out how the Internet of Things, or IoT, is being used in smart cities. We also want to establish the necessity for IoT systems in these smart cities, as well as the issues that they may pose to individuals and society, via the research.
 Review secondary research papers, reviews, dissertations, and online documents from the EBSCO, Scopus, and Emerald databases to analyse and comprehend the usage of IoT in smart cities and the possible problems that its implementation may provide in order to accomplish the following goals.
 Municipal requirements are getting more complicated, necessitating the adoption of new technology like the Internet of Things to ensure that all of these cities' duties are completed. Although more cities are becoming smart via the usage of IoT in a number of businesses, the study shows that this IoT system is also creating worries about the security of citizens' data.

The Internet of Things (IoT) has witnessed rapid proliferation, revolutionizing the way we interact with technology in various domains of life. This ubiquitous network of interconnected devices, however, presents serious challenges concerning privacy and security. As IoT devices gather vast amounts of sensitive data and share it across networks, ensuring the protection of user privacy and guarding against potential security breaches becomes paramount. This abstract delves into the primary concerns surrounding IoT privacy and security, addressing issues such as data collection, user consent, data ownership, and vulnerability to cyber-attacks. Furthermore, it explores potential solutions, including encryption, blockchain technology, and the implementation of robust authentication mechanisms to safeguard IoT ecosystems. Acknowledging the significance of effective regulation and industry collaboration, this abstract concludes by emphasizing the need for continued research and proactive measures to address the evolving landscape of IoT privacy and security challenges.

As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things (IoT) has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning‐based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real‐time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password‐sized text and paragraph‐sized text—that achieves target fair results compared to the existing algorithms in real‐time deep learning networks for IoT applications.

Internet of Things (IoT) and Big Data have played a significant role in the development and sustainability of Smart Cities. They are the backbones of Smart Cities' efforts to connect human resources, social capital, and ICT infrastructure to address public challenges, achieve sustainable development and improve people's standard of life. It helps Smart Cities improve public services, such as water management, healthcare, education, security issues, transportation, energy usage, and other community to achieve a better life. Big Data helps to analyze, store and back-ups a massive amount of data generated in smart cities in seconds day by day. For this matter, different analytical tools are employed, such as data analytics, machine learning, statistics, and data mining. Even though there are many benefits offered to smart cities; the Smart Cities encounters challenges that need to be addressed. Many of these challenges focus on security and privacy, infrastructures and operational and handling massive data. This paper describes the overview of IoT, Big Data, and Smart Cities. The Applications of IoT and Smart Cities were also discussed; the features of Smart Cities and Big Data; Different challenges of IoT, Big Data, and Smart Cities are described. Also, the proposed research work has presented the relationship between IoT and Big Data to Smart Cities; the role of IoT and Big Data in smart cities was identified; finally, the future directions for IoT and Big Data regarding Smart Cities are discussed.

Big data to use JAVA, group software engineering, networking, cloud computing knowledge and technology. The purpose of this paper is Research on Wireless sensor network of the Internet of things. The Internet of things, mainly includes multicast network, ZIGBEE network, WSN network, Bluetooth network, infrared network and so on. Swarm software engineering is a way to implement cloud computing, Internet of things and big data. Cloud computing comes from big data, the Internet of things can be achieved through cloud computing. This paper mainly studies, computers, software, networks, smart cities, and the use of Excel and Matlab and Microsoft Office Visio 2003 mapping and so forth. And through the practice of research methods, including automotive networking and smart city. What is the Internet of things, objects connected to the Internet is the Internet of things, cup networking, car networking. Things better than other networks, is composed of what objects, what composition, what nature, what innovation and superiority. The four key technologies of the Internet are widely used, and these four technologies are mainly RFID, WSN, M2M, two kinds of integration. RFID can be implemented using MATLAB, NS2, and JAVA, and WSN can be implemented using NS2, and M2M can be developed using JAVA. The research results are that the Internet of things originated and developed in the Internet; on the contrary, the development of the Internet of things further promoted the Internet to a more widespread “Internet” evolution. The Internet of things and the Internet are the relationships between the parent and the child. Wireless networks are just like wireless WSN networks, but wireless nodes are fixed and moved into sensors. The Internet of things includes Internet technology, including wired and wireless networks. The research conclusion is the wireless internet of things are just like the wired internet of things, wired provides the basis for Wireless Research. Baidu Tiangong Internet of things platform, Amazon AWS platform, ERP and so on are also important applications of the Internet of things. The use of mirroring and replication software also requires Internet of things. Video is composed of multi frame images. H.264 and JM encoder are also the future directions. Where to go network Ctrip network is the application of the Internet of things. Recalling what we do today, planning tomorrow, how to spend the university stage and predicting the future of university development can be the application of the Internet of things. I visited the Tangshan Rd. Mart store in Qian’an from January 2017 to March. The feeling is that Beijing is still Carrefour and Jing Kelong and WAL-MART and Hualian. The electricity supplier which Ma Yun’s Alibaba still feels more powerful. Now Hebei province and all parts of the country have venture capital and subsidy, which will undoubtedly promote the Internet of things.

With the popularisation and development of the internet of things, big data and cloud computing, the search of data in cloud-based internet of things becomes a hot research topic. However, the sensitive data, such as the medical data collected by wearable devices, is inevitable to be stored in the cloud server. Homomorphic encryption has the ability to calculate the ciphertext without decryption. We separate the calculating and the decryption into different security domains to preserve the privacy of sensitive data, so the original plaintext would not be exposed in the cloud. Hence, we can compare two ciphertexts to get the difference of them in a privacy preserving way. In order to accelerate the search process of range query, we build an encrypted self-balancing binary index tree. Based on oblivious RAM, the searching scheme can hide the access patterns of the node of tree. The actual nodes and logic relation of tree are stored on different servers. A sample implementation of the proposed scheme is given, and the experimental results and analysis are presented to illustrate the scheme's effectiveness and security.

Internet of Things (IoT) "The smart city concept has become a dream that big cities in Indonesia want to achieve, basically the smart city concept focuses on developing the human element using technology. IoT opens up many opportunities for new services by connecting the physical world and the virtual world to various electronic devices. IoT aims to leverage cutting-edge technology to support sustainable services for governments and their citizens. Systematic Literature Review (SLR) is one method in conducting an overview of previous interrelated researchers. The purpose of the literature study in this research is to understand trending research topics, methods, and architecture in the development of smart cities with IoT. In this study, various interesting information was found in various research journals regarding the role of IoT in building a smart city that has a role to serve smart city infrastructure, identify and analyze trends, develop smart cities and become innovations for IoT. Based on the research, there are things that need to be done to improve the study to focus more on the role of IoT that can be more utilized. IoT is also one of the technologies that are widely used in several countries in the development of IoT in the future. IoT in smart cities will become an inseparable technology because humans will increasingly depend on IoT in their daily lives

Federated learning (FL) is emerging as a powerful paradigm for distributed data mining in the context of Internet of Things (IoT) big data. It addresses privacy concerns associated with data outsourcing by enabling local data training and knowledge (i.e., model) sharing. However, simplistic local knowledge sharing can inadvertently expose user privacy to advanced attacks, such as model inversion or gradient leakage. Furthermore, achieving fine-grained and personalized privacy protection for IoT users remains a challenge. In this paper, we propose a novel solution called hierarchical blockchain-empowered cloud-edge orchestrated federated learning (HBCE-FL) to address these challenges. HBCE-FL is designed to provide secure, intelligent, and distributed data analysis for IoT users. To tackle FL’s privacy issues, we develop a multi-level access control encryption and blockchain-based approach for sharing IoT knowledge within the HBCE-FL framework. Our approach classifies IoT users into different levels based on their individual privacy requirements, enabling fine-grained privacy protection. The blockchain is employed for identity authentication, key management, and message sanitization. For scenarios involving IoT users with non-IID data, we integrate federated multi-task learning into HBCE-FL to ensure fairness, robustness, and privacy. Finally, we conduct experiments using classic MNIST and CIFAR10 datasets to validate our approach. The experimental results illustrate that HBCE-FL effectively achieves personalized privacy-preserving FL without losing IoT data availability. Regardless of whether IoT data are homogeneous or heterogeneous, our approach enhances model accuracy and convergence rates by enabling secure IoT knowledge access and sharing for IoT users.

The Internet of Things (IoT) is driving the technology and advances of the Internet and every day it is becoming more popular to talk about IoT systems in multiple domains: Smart Cities, Agriculture, and Industrial Internet, etc. Increasingly, IoT systems will need to interact and be interconnected for offering the always-promoted everything-connected paradigm. Current IoT systems rely on semantic web technologies for integrating data and ensure web services interoperability. However there are yet a gap to ensure semantic interoperability among IoT systems. Most of the existing proposed (open) approaches and solutions lack on formal methodologies for interoperability in technology and standard format of the data. We studied and analyzed most available semantic-based IoT approaches to identify the main requirements hindering IoT semantic interoperability. In this paper, we present SEG 3.0 a methodology to federate, unify and provide semantic interoperability. SEG 3.0 emerges from methodologies for ontology engineering and the idea of unification and federated systems. We propose SEG 3.0 and apply it to Internet of Things (IoT) and particularly on use cases for smart cities as proof of concept. Firstly, we define characteristics required for the methodology. Secondly, we describe the processes and the different formal steps. Thirdly, we provide a proof of concept framework and architecture applying this methodology, thus the benefits of using SEG 3.0 methodology in IoT domains are described. Finally, we demonstrate that the SEG 3.0 methodology is applied to three use cases: (1) the M3 framework to assist developers in designing semantic-based IoT applications, (2) the VITAL EU project for smart cities, and (3) the FIESTA-IoT EU project for IoT semantic interoperability. SEG 3.0 is a formal methodology generic enough to be applied to other domains than IoT and smart cities, since the main benefit of the SEG 3.0 is integrating heterogeneous data and adding value to it to build innovative applications.

Privacy preserving Internet of Things: From privacy techniques to a blueprint architecture and efficient implementation