Cyber Security Aspects of Virtualization in Cloud Computing Environments

Cybercrime continues to emerge, with new threats surfacing every year. Every business, regardless of its size, is a potential target of cyber-attack. Cybersecurity in today's connected world is a key component of any establishment. Amidst known security threats in a virtualization environment, side-channel attacks (SCA) target most impressionable data and computations. SCA is flattering major security interests that need to be inspected from a new point of view. As a part of cybersecurity aspects, secured implementation of virtualization infrastructure is very much essential to ensure the overall security of the cloud computing environment. We require the most effective tools for threat detection, response, and reporting to safeguard business and customers from cyber-attacks. The objective of this chapter is to explore virtualization aspects of cybersecurity threats and solutions in the cloud computing environment. The authors also discuss the design of their novel ‘Flush+Flush' cache attack detection approach in a virtualized environment.

Security and Privacy in Big Data Computing

The rapid growth of digitization in the present era leads to an exponential increase of information which demands the need of a Big Data paradigm. Big Data denotes complex, unstructured, massive, heterogeneous type data. The Big Data is essential to the success in many applications; however, it has a major setback regarding security and privacy issues. These issues arise because the Big Data is scattered over a distributed system by various users. The security of Big Data relates to all the solutions and measures to prevent the data from threats and malicious activities. Privacy prevails when it comes to processing personal data, while security means protecting information assets from unauthorized access. The existence of cloud computing and cloud data storage have been predecessor and conciliator of emergence of Big Data computing. This article highlights open issues related to traditional techniques of Big Data privacy and security. Moreover, it also illustrates a comprehensive overview of possible security techniques and future directions addressing Big Data privacy and security issues.

Improved Methodology to Detect Advanced Persistent Threat Attacks

Cybersecurity is essentials in today's era. An increase in cyberattacks has driven caution to safeguard data. An advanced persistent attack is an attack where the intellectual property of an organization is attempted to be misused. The attacker stays on the network for a long-time intruding into confidential files. The attacker switches into sleep mode, masking himself. Hence, the attacker is quite difficult to trace. The proposed work is suggested to tackle the problem. Public key cryptography is used to encrypt the data. The hash code is affixed to the transmitted message to provide reliability to the transmitted data. The work proves to be 4.9% stronger in authenticating the received packets, provides 4.42% greater data reliability, and decreases the load of the server by 43.5% compared to work.

Quantum Internet and E-Governance

We are leaving in the era where almost everyone in the world uses internet for the communication over social media site, shopping, E-commerce, online transaction and many more. The exponential growth in usage of internet resulted in security related challenges. Since last several years, traditional cryptography algorithms are found working well. Evolution of quantum computer and its high computing capability can break existing cryptography algorithms. To handle the security constraints, this chapter provides details on evolution of quantum cryptography, components involved to design network architecture for quantum internet, quantum key exchange mechanism and functionality wise stages for quantum internet. This chapter also includes challenges involved in evolution of quantum internet. Further, chapter also contains the details on e-governance, challenges in e-governance and solution using quantum cryptography.

LFSR-Keyed MUX for Random Number Generation in Nano Communication Using QCA

Nano industries have been successful trendsetters for the past 30 years, in escalating the speed and dropping the power necessities of nanoelectronic devices. According to Moore's law and the assessment created by the international technology roadmap for semiconductors, beyond 2020, there will be considerable restrictions in manufacturing IC's based on CMOS technologies. As a result, the next prototype to get over these effects is quantum-dot cellular automata (QCA). In this chapter, an efficient quantum cellular automata (QCA) based random number generator (RNG) is proposed. QCA is an innovative technology in the nano regime which guarantees large device density, less power dissipation, and minimal size as compared to the various CMOS technologies. With the aim to maximise the randomness in the proposed nano communication, a linear feedback shift register (LFSR) keyed multiplexer with ring oscillators is developed. The developed RNG is simulated using a quantum cellular automata (QCA) simulator tool.

Critical Infrastructure Security

Cyber-physical security applied to the domain of critical infrastructure (CI) poses different challenges. To acknowledge the security concern of CI from a cyber-physical perspective becomes imperative since the failure of any one of the CI's components may not only lead to cascading effects, but also the overall services may shut-down state. The energy infrastructure is becoming the backbone in CI due to the complexity of environment, heterogeneous communication technologies, and different configurations of the energy infrastructure, so securing the communication among these devices and control centers becomes a central issue. Many significant works in the related domain has been done. The main focus of the chapter is identification of the attack vector formulation with prevention and detection mechanisms for different components, providing countermeasures cohesively against security threats.

Optimal Parameter Prediction for Secure Quantum Key Distribution Using Quantum Machine Learning Models

The advent of quantum computing is bringing threats to successful operations of classical cryptographic techniques. To conduct quantum key distribution (QKD) in a finite time interval, there is a need to estimate photon states and analyze the fluctuations statistically. The use of brute force and local search methods for parameter optimization are computationally intensive and becomes an infeasible solution even for smaller connections. Therefore, the use of quantum machine learning models with self-learning ability is useful in predicting the optimal parameters for quantum key distribution. This chapter discusses some of the quantum machine learning models with their architecture, advantages, and disadvantages. The performance of quantum convoluted neural network (QCNN) and Quantum Particle Swarm Optimization (QPSO) towards QKD is found to be good compared to all the other quantum machine learning models discussed.

IoT and Cyber Security

The Internet of Things (IoT) connects different IoT smart objects around people to make their life easier by connecting them with the internet, which leads IoT environments vulnerable to many attacks. This chapter has few main objectives: to understand basics of IoT; different types of attacks possible in IoT; and prevention steps to secure IoT environment at some extent. Therefore, this chapter is mainly divided into three parts. In first part discusses IoT devices and application of it; the second part is about cyber-attacks possible on IoT environments; and in the third part is discussed prevention and recommendation steps to avoid damage from different attacks.

Post-Quantum Cryptography and Quantum Cloning

In the last two decades, the field of post-quantum cryptography has had an overwhelming response among research communities. The ability of quantum computers to factorize large numbers could break many of well-known RSA cryptosystem and discrete log-based cryptosystem. Thus, post-quantum cryptography offers secure alternatives which are implemented on classical computers and is secure against attacks by quantum computers. The significant benefits of post-quantum cryptosystems are that they can be executed quickly and efficiently on desktops, smartphones, and the Internet of Things (IoTs) after some minor software updates. The main objective of this chapter is to give an outline of major developments in privacy protectors to reply to the forthcoming threats caused by quantum systems. In this chapter, we have presented crucial classes of cryptographic systems to resist attacks by classical and quantum computers. Furthermore, a review of different classes of quantum cloning is presented.

Cyber Security Techniques for Internet of Things (IoT)

The purpose of the cyber security policy is to provide guidelines on how to secure public and private resources from cyberattacks. IoT devices are having challenges managing the personal information they collect and helps to people understand that information is managed by a system. Digital twins enhance development by allowing developers to directly manipulate the device's abstract version using programming instructions. It is required to think about possible attack vectors when tuning cyber security for the IoT environment concerns. So, a security administrator is required to think the about possible vulnerabilities of the environment. Supervision and protocols must also be developed for suppliers, manufacturers, vendors, etc. The deployment of consumer understanding to make best use of “smart” strategy, using their own “smart” minds is required. There is a need for a framework or other types of guidance for assessing IoT cyber security to provide an informed approach to securing devices and the ecosystems in which they are set up.