Data-Driven Mining, Learning and Analytics for Secured Smart Cities

For the accelerated development in ICT technology and computers, data mining and pattern analytics are used to reveal potential patterns for decision-making in smart city environments. Past works of pattern mining in smart cities focused on frequency constraint that cannot show the patterns involved with multi-factors for evaluation. Also, single-threshold value is mostly considered in the pattern-mining framework, which is not realistic in smart city environments since different infrastructures should have different tolerance factors for pattern analytics. In this paper, we then employ the multi-threshold constraint to evaluate the high utilization patterns that can be applied in the smart city environments. The average-utilization model is also adapted in the designed model that provides a fair and alternative criterion for pattern analytics. Based on the provided results in the experiments, the designed framework shows better effectiveness and efficiency in pattern mining task that can be deployed to analyze the utilization of the varied infrastructure in smart city environments.

The smart city emerged as a model with the rapid growth of robust information and communication technology and the development of ubiquitous sensing technology. A smart city offers enhanced social facilities, transport and accessibility while promoting sustainability by using different sensors to gather data from the surroundings. The data collected can then be used to control urban infrastructure, such as traffic congestion, water supply, environmental monitoring, food services, and more. The smart city can track people’s actions and deliver intelligent travel, intelligent healthcare, entertainment, and other services. Dynamic data change includes intelligent and systems solutions for the functioning of these networks to ensure confusion about events in smart cities. Recent advances in machine learning and artificial information allow intelligent cities to effectively deliver services through a reduction in resource consumption. Cloud-based machine learning models enable resource-restricted devices to interconnect and optimize efficiency. The emerging data collection and device designs are targeted at reducing energy savings rather than risks to privacy and security. Thus, the security and privacy concerns remain as intelligent city networks not only collect information from heterogeneous nodes which are the weakest link and susceptible to cyber-attack. In this chapter, we address security issues in smart city applications; and corresponding countermeasures using artificial intelligence and machine learning. Some attempts to address these protection and privacy problems are then presented for smart health, transport, and smart energy.

Smart cities are those that use science, engineering, artificial intelligence, digital knowledge, and other technologies to progress the well-being of residents, boost economic development, and at the same time, promote and favor sustainability, as also to improve infrastructure, optimize urban mobility, and engender solutions sustainable, to generate efficiency in urban operations, this is, improving the population’s quality of life. Smart cities are automated and more sustainable cities, considering that technology is fundamental, but it is only a means to resolve a set of urban issues and attain purpose and goals that are increasingly essentials for large urban centers. This is achieved through the employment of advanced ICT (Information and Communications Technology) to stimulate sustainable development, and improvement in the quality of life, in which everything becomes connected. Through this, for example, it is possible to count on the fastest free public WiFi, i.e., high-speed internet for all residents and visitors and the interconnected functioning of traffic, lighting, public transport systems, among others. There are also discussions on reducing public spending and transparency in the relationship between government and citizens. It is evident, especially in large cities, that something must be done to increase the quality of life, public services, and sustainability. In addition to urban planning, it is necessary to invest in technological solutions that can be accepted and used by the residents of each smart city. Therefore, this chapter aims to provide a scientific major contribution related to the current overview of Smart City, approaching its essential concepts and fundamentals, with a concise bibliographic background, addressing its evolution and relationship with other technologies, as also categorizing and synthesizing the potential of technology.

Internet-of-Things are an amalgamation of multiple devices running on a different platform. They communicate with various instruments of a different calibre. They take the help of the internet to send and receive messages. As these devices do not have enough storage, they employ a cloud to store the sensed readings. The proposal is the inclusion of both the technologies. The recommendation makes sure about correspondence in vehicular organizations. It supports an access scheme without requiring ciphertext re-sign-based encryption mystery keys generation. It doesn’t depend on an intermediary re-encryption worker to execute the strategy update framework. It presents another unquestionable protection saving redistributed ABSC plot that guarantees adaptable access control, information classification, and verification while supporting arrangement refreshes in cloud helped IoT applications. The proposal enhances the work by adding reliability by 3.31% in comparison to the previous contribution. The system provides forward and backward secrecy.

We are amidst a digital world wherein the Internet and advanced technological advancements have ushered smart solutions to our every requirement, and have imparted an interconnected environment for a hassle-free life altogether. We have become so accustomed to a smart handheld device as if it controls, manages, and records even the simplest and most straightforward task of our daily routine. The miniaturization of hardware and Internet-powered consumer appliances and services have solved diverse problems not only for an individual but also related to the community. The smart city project is effectively governing a city which was a dream a decade ago. The healthcare services, clean city drives, power and water supply departments, traffic control, surveillance, and many similar initiatives within the region of a municipal corporation have become IoT-enabled. The smart city services we enjoy may be vulnerable to attacks such as data interception over the communication channel, hacking the devices, stealing database records and consumer credentials, and financial frauds, etc. A consumer is not always aware of such attempts but can be a probable victim of such criminal activities. For a smart device manufacturer and a service provider, it is challenging to claim that their products and services are robust enough to combat all existing attacks. Since the IoT environment consists of small battery-powered devices, the security mechanisms generally employed to secure conventional devices and data within a typical Internet environment are not suitable for IoT infrastructure. Hence we have lightweight solutions to limit the security overhead of data storage and data communication between IoT nodes. The lightweight security protocols targeted towards securing IoT infrastructure are strong enough to mitigate well-known attacks while consuming less memory and resource footprint on the device. This chapter introduces the lightweight security protocols specifying their need in different smart city services. We need these protocols to perform user authentication, access control, payment mechanisms, and encrypting data during transmission, inventory management, traffic control, etc. The chapter introduces Singapore as a smart city model and aims to provide insight into existing security schemes for IoT-enabled smart city services. Lightweight cryptographic initiatives contributed significantly to assure the integrity of data in a constrained environment. We discuss lightweight primitives under block cipher, stream cipher, and hash function category. However, there are incidences where some of these schemes proved susceptible to certain cryptanalysis attempts. The chapter further presents a glimpse of such lightweight ciphers and their respective vulnerabilities. The chapter's contents will benefit the readers in having a clear vision of the security schemes explicitly designed for IoT applications in smart city projects.

Smart City is the concept for improvising the urban cities operating and services efficiency by making use of IoT (Internet of things) which is a modular approach that operates by deploying sensors with significant qualities and integrating them with ICT (Information and Communication Technologies) solutions. The application area for the IoT platform has been in smart building and office management, transportation, environmental degradation surveillance, and smart grid management, etc. However, maintaining an efficient architecture for its operation in a complex environment has been a challenge for several years. This will increase the security and privacy concerns with the increase in smart applications within smart cities. This chapter aims to study the issues related to data integrity and security and the approach used to resolve these issues using blockchain analytics algorithms and architecture. This chapter also gives the future direction towards achieving low-cost architectural management for smart cities. This chapter is mainly focused to analyze such challenges and to identify limitations of the existing secure smart cities framework and to proposes an effective blockchain-based smart city interaction framework.

In the present era of modernization, automation and intelligent systems have become an integral part of our lives. These intelligent systems extremely rely on parallel computing technology for computation. Field Programmable Gate Arrays (FPGAs) have recently become extremely popular because of its reconfigurability. FPGA, an integrated circuit designed to be configured by a customer or a designer after manufacturing, finds its application in almost every area where artificial intelligence and IoT is used. The benefits of FPGAs over Application-Specific Integrated Circuits (ASICs) and microcontrollers are emphasized in this chapter to justify our inclination towards more IoT-FPGA based applications. This Dynamic reconfigurability and in-field programming features of FPGAs as compared to fixed-function ASICs help in developing better IoT systems. Due to their remarkable features, they are being heavily explored in IoT application domains like IoT security, interfacing with other IoT devices for image processing, and so on. We would lay focus on areas which require high computational capabilities and the role of FPGAs or related System on-chip whichcan be used in such application resulting in low power designs and flexibility when compared to ASICs. We also provide our insights on how FPGAs in future will be like and what improvements need to be done.

Blockchain paves the way to fill the research gaps in terms of security, database process, cryptography, data center, etc. in the research fields like networking, big data and cloud computing in recent days. Generally, blockchain contains blocks of chain where each block is referring to the previous blocks and difficulty in the recreation of a chain. It provides a set of bitcoins, which is nothing but the digital currency utilized for cryptocurrency to manage several transactions based on a fully distributed environment. As bitcoins decentralizes for the mining process, mining processes are performed for the creation of bitcoin too. While considering the security, the bitcoin transaction has several attackers shows while making transactions. The most severe attack that we have found here is the double-spending attacks to modify and manipulate the transaction performed. Based on the blockchain framework existence, all the transactions stores into the transaction part of each block. Transactions perform a hash function which hashes each transaction and repeat it for pairing again and again based on the Merkle tree. Merkle tree is the block header that stores the hash of the previous block header. These chaining process helps the transaction to ensure no modifications done without changing the earlier blocks in the chain network. The transaction in blockchain denotes the bitcoin wallet, which tells the information about bitcoin's movement. Each spend transaction of bitcoin has the previous bitcoin transaction. Double spending attack occurs when a single transaction creates multiple output transaction while sending to several destination addresses. In the blockchain, each output transaction is provided based on one input. If any attempt of the same bitcoin uses for two or more times for a transaction, the double-spending attack is possible. Based on the existing survey related to the double-spending attack ratio, there is a possibility of a double-spending attack in the blockchain. Based on the double-spending attack problem, the modified bitcoin transaction chaining technique proposes with integrated the electronic codebook based on cryptography. As to provide more security, modes of electronic code operations are considered. Based on the block cipher of block length and in the case of multiple blocks of information are processed, security attacks are possible as block chaining added up into the transaction between the sender and receiver, which ensures authentication and confidentiality. The initial constant provides integrated with the transaction to provide maximum security and protect against unauthorized changes. To provide additional security constant number is considered as the random number which gets varied for each transaction based on output feedback mode operation.

In the past several years, Smart City has generated considerable attention as a relatively new computing model. Its accordance with social web and internet of things (IOT) standards also offers unique resources by using the intellect of human beings and the capacity to solve problems to improve relevant services and mechanisms. This paper explores the benefits and challenges of integrating persons into research engine operations—as smart agents—as part of the core position of internet and information search engines. The key objectives of the smart cities are to make policies more effective, to minimize waste and discomfort, to enhance social and economic quality and to increase social inclusion. In order to highlight the human role in machine systems, some of the fields are unique and related works are studied. Then the insights and problems are addressed through a review of emerging developments in the field of powerful search engines and an overview of current needs and requirements. As research on this subject is still at the beginning, this study is thought to be used as a guideline for potential studies on the subject. Present status and growth patterns are outlined in this regard by offering a common overview of the literature. Furthermore, numerous guidelines are provided to improve the applicability and reliability of the next generation of intelligent urban search engine. In fact, it is able to recognize the ways in which work processes are structured for important purposes, understanding the various aspects and challenges involved in the design progress of search engines. The focus of this analysis was the broader picture and possible issues of multi-powered search engines. It may be considered as a point of reference one of the first works on different aspects of the matter which provided a complete study.

Generation of smart cities that considers environmental pollution, waste management, energy consumption and human activities has become more important in recent years since it was first introduced in the 1990s. In the smart cities, most of the structures, machines, processes and products will be redesigned in terms of technological developments linked to the fourth industrial revolution, Industry 4.0. This situation introduces the need of new design models that address extended significant parameters for manufacturing. Data-driven generative design methodology is an algorithmic design approach for developing state-of-the-art designs. Generative design may give the decision-makers more sustainable optimized project solutions with the iterative algorithmic process. Many parameters and constraints can be taken into consideration during the designing process, such as lightness, illumination, solar gain, durability, cost, sustainability, mass, factor of safety, mechanical stresses, resilience etc. In the generative design, an iterative process occurs via cyclic algorithm from ideation to evaluation to reveal possible potential design solutions. The increase in design freedom and complexity boosts the importance of new generation manufacturing methods. Hybrid additive subtractive manufacturing (HASM), a key component of Industry 4.0, offers tailored and personalized production capabilities by combining additive and subtractive processes in the same production unit. In today’s digital era, there is a growing need to create an integrated data-driven digital solution which consists of a multidisciplinary functional design integrated with hybrid additive subtractive manufacturing. Generative design integrated with hybrid additive subtractive manufacturing approach offers creating functional multi-criteria-based product combinations with sustainable organic mechanisms for engineering purpose. Alternatively, this approach provides dozens of different solutions for their studies considering multi-criteria, such as determining the convenient sunlight angles for walkways, computing optimum dimensions of smart structures, enabling transportation vehicles to pass underground or bridges etc. The main objective of this chapter is to introduce the importance of generative design and hybrid additive subtractive manufacturing for smart cities and present the critical advantages of a data-driven generative design concept algorithm integrated with hybrid additive subtractive manufacturing approach that will increase the speed of transition to smart cities. This chapter discusses a concept that integrates hybrid additive subtractive manufacturing with a data-driven generative design for the reliable, cost effective and sustainable design of components that can be used for establishment of secure smart cities. After conceptual explanations, the main aim and advantages of the concept are realized by a case study which is about the design of a drone chassis. A drone chassis is selected as a case study since drones will be used extensively for mainly security and logistics purposes in smart cities and design of drone chassis can be optimized by the proposed concept.

Autonomous driving is an indispensable component in the future secured smart cities. The benefits of autonomous driving are numerous, including improving road traffic safety, reducing traffic-related economic loss, reducing traffic congestion, and enabling new vehicle applications. With the recent development of deep learning and sensor technologies, the autonomous vehicle becomes a highly complex networked system that heavily relies on sensor data to perceive the surrounding environment and make the correct decision. Such a system inevitably exposes a large attack surface and multiple attacks have been developed. It is thus crucial to protect the data and use secured machine learning algorithms to prevent, detect, and mitigate these attacks while keeping the autonomous driving system low-cost, low-latency, high-accuracy, and high-reliability. The proposed chapter presents an overview of research in autonomous driving, focusing on using end-to-end deep learning technologies for enhancing performance and security in autonomous vehicles in dynamic, adversarial environments. The chapter introduces autonomous driving paradigms, associated deep-learning methods for end-to-end learning, and the defenses against adversarial attacks. A new method utilizing temporal information for secured autonomous driving is presented; its design and implementation using CNN-LSTM include defenses against adversarial attacks. Experiments and performance demonstrating its success prediction rates are illustrated. Future research directions are described, which include both improving the autonomous driving system and enhancing its security defenses.

A smart city is a municipal area aimed at managing the expanding urbanization through a vast exchange of information using technologies. It is the concept of bringing technology, society, and government together to refine the quality of the living standards of their citizens. As the number of urban areas is increasing day by day and the citizens are becoming ambitious for a living style with a secured environment, the demand for a proper and safer healthcare system with tech connectivity is increasing rapidly. Therefore, the next-generation smarter healthcare receives considerable attention from academics, governments, businesses, and the health care sector through the growth of information and communication technology infrastructure. From the personal level to community level, information and communication technology driven healthcare is becoming the ultimate role player. In this study, we have briefly described the overview of a smart city and its components. Among all these components, smart healthcare is our target component for further studies. We presented current informative views regarding next-generation healthcare system modules such as data collection through mobile sensors and ambient sensors; usability of data processing using edge computing and cloud computing applications; privacy and security of data; and connectivity with other ‘Smart City’ services like smart infrastructure, medical waste management, health education. Finally, we discussed underlying opportunities and challenges so that a path towards the optimization of current healthcare technologies is disclosed.

The swift growth in usage of Location-based social networks (LBSNs) has driven to the availability of a large volume of check-in data of the users. This provides a great opportunity to provide various location-aware utilities in the Smart Cities. Future will be smart, each and every places/location will be connected to the network and it will make the cities smart and advanced. One such service includes the Point-of-Interest recommender that is used to recommend the venues where a person has not been before. Various methods have been lately analyzed and implemented to provide this service. By the Location based POI method in smart cities will provide ultimate recommendation based on the social network interactivity in the smart cities. This chapter aims to provide various techniques used in POI recommendation systems for LBSNs. We aim to propose the implementation of an adaptive POI recommendation algorithm in this chapter. The proposed method incorporates the spatial feature along with the user activity and social feature. This model is implemented on a large-scale check-in dataset, Foursquare.

The biggest consumers of technology in recent decades are the urban and semi-urban populace, especially in the developing economies. This integration of humans and technology has unravelled novel challenges in protecting various socio-economic rights of the people, enshrined in the United Nations Sustainable Development Goals (UNSDG). This paper tends to unravel the truth behind such promises in the Indian context, in her endeavour to bridge the digital divide in the internet of things. The paper focuses upon the current position of privacy laws in India and makes a contrast with leading democracies to unearth the challenges; technology would have to address in the coming decades. The debate involved in ‘realization and recognition’ coupled with enforcement mechanisms adopted in India would be integrated with this paper to clarify the need for protecting data privacy towards a sustainable and smart city.

In today's financial markets, the increasing volume of data poses a big challenge for investors in the stock market. On the other hand, the weaknesses of traditional mathematical methods in managing financial investments have led investors and financial institutions to apply artificial intelligence algorithms. Therefore, the main objective of this chapter is to present artificial intelligent algorithms applications in financial markets. In this regard, after a brief review of different kinds of machine learning methods, it has focused on their applications. Also, it provides fundamental insights for future machine learning-based financial research.

Today, the need for security and data protection has increased because of the increase in Internet use. In today’s era, all industries have digitally moved their data to cloud platforms that bring new data protection issues and challenges especially in IoT and Smart cities networks. Internet of Things (IoT) is a growing field in today’s world that offers reliable and consistent communication via wireless and wired connections and generate a huge amount of data. Therefore, it is essential to ensure the security and reliability of generated data. IoT systems and networks should have strong security mechanism to protect users’ private data and processed information. Internet development and usability have brought numerous challenges in term of online frauds, hacking, and phishing activities, spamming and many others. According to Cybersecurity Ventures survey, cybercrime damages could cost the world $6 trillion per annum by 2021. This information shows growing number of Internet frauds, the finances losses and cybercrime in the coming era for every industry. Without adequate awareness and comprehensive knowledge, it has become difficult to defend against such practices. Ethical Hacking allows users and businesses to scrutinize their systems and networks vulnerabilities, take proper measures to protect their network and systems against unlawful and malicious attacks. It also strengthens network and systems by identifying common vulnerabilities, scrutinize, and taking proper security measures. Kali Linux Operating System (OS) is known as the most sophisticated penetration testing tool to perform Ethical Hacking. In this chapter, we addressed latest information regarding IoT and Smart City networks worldwide in terms of financial and data losses. We have also discussed the Ethical Hacking terminologies along with various kinds of social engineering and phishing attacks could occur on IoT and smart cities networks. We have performed several social engineering experiments using Kali Tools to demonstrate identification of common mistakes in web-based applications and smart networks for the apprentices. In the end, we have proposed some appropriate solutions to strengthen against hackers.

Artificial Intelligence (AI) is a fascinating technology for the whole society, whether the citizen, science, business, education, government, among others. Machine Learning is a technique derived from AI that through neural networks and statistical methods, establishes logical rules to make decisions and automate processes, i.e., a method employed so that machines can learn from the data. A smart city aggregateICT (Information and Communication Technologies) to promote the performance and quality of urban services related to urban transportation, energy consumption, and distribution, and even public services (water treatment and supply; production of electricity, gas, and fuels; collective transport; capture and treatment of sewage and garbage; telecommunications; among others), in order to decrease resource consumption, wastage, and general costs. The administration of Smart Cities is possible to be efficient through the employment of data collected in real-time combined with the skills of computational intelligence, i.e., Machine Learning and its aspects. In this sense, this chapter intends to offer a scientific major contribution related to an overview of Machine learning, directing focus to Sustainable Future Secured Smart Cities, discussing its relationship from a concise bibliographic background, evidencing the potential of technology.