Editorial

Editor - N Rama Murthy

In this omnibus issue which has been brought amidst disruption of normal activities in our physical world due to COVID19 pandemic, several articles of significant interest have been included.

In their article titled “A Comprehensive Survey on Recent Advancements in Cognitive Radio-based Internet of Things”, the authors survey two promising technologies, viz. Internet of Things (IoT) and Cognitive Radios (CR) which are though not fully mature have nevertheless potential, abundant, and practical applications that impact our present day lives significantly in not so a distant future. While the concept of Internet of Things (IoT) has been presented and discussed at length in a dedicated article of our earlier issue, the Cognitive Radio (CR) technology is being introduced in ACC through this article.

The authors survey the progress made to date and state of art of these two technologies before discussing how the combination of two technologies referred to as CR based IoT (CR-IoT) can be of use in several application domains. The main motivation for CR-IoT stems from bandwidth allocation to be made for IoT devices. The number of IoT devices is expected to grow in large numbers, and it will be very difficult to allocate spectrum bands to large number of IoT devices.

In another interesting paper, the authors discuss the science of Plant Phenotyping. It is the science of the characterization of the crops which is particularly important for decision support in agriculture. This aids plant breeders when selecting the best genotypes that will become the future cultivars well-adapted to different environments. As such, plant phenotyping helps to better understand the functioning of the crops. The knowledge gained is often used to calibrate crop models.

High throughput plant phenotyping methods have shown great promise in efficiently monitoring crops for plant breeding and agricultural crop management. Research in deep learning has accelerated the progress in plant phenotyping research. With many open problems in plant phenotyping warranting further studies, it is indeed a great time to study plant phenotyping and achieve rapid progress by utilizing the advances in deep learning.

The authors discuss various issues and challenges that are to be dealt with, application of supervised learning, and open problems associated with phenotyping with limited data.

Quantum cryptography is the science of exploiting quantum mechanical properties to perform cryptographic tasks.

Post-quantum cryptography (sometimes referred to as quantum-proof, quantum-safe or quantum-resistant) refers to cryptographic algorithms (usually public-key algorithms) that are thought to be secure against an attack by a quantum computer. As of 2019, this is not true for the most popular public-key algorithms, which can be efficiently broken by a sufficiently strong quantum computer. The problem with currently popular algorithms is that their security relies on one of three hard mathematical problems: the integer factorization problem, the discrete logarithm problem or the elliptic-curve discrete logarithm problem. All of these problems can be easily solved on a sufficiently powerful quantum computer running Shor’s algorithm. Even though current, publicly known, experimental quantum computers lack processing power to break any real cryptographic algorithm, many cryptographers are designing new algorithms to prepare for a time when quantum computing becomes a threat.

Currently post-quantum cryptography research is mostly focused on six different approaches: Lattice-based cryptography, Multivariate cryptography, Hash-based cryptography, Code-based cryptography, Supersingular elliptic curve and Isogeny cryptography.

In cryptography research, it is desirable to prove the equivalence of a cryptographic algorithm and a known hard mathematical problem. These proofs are often called “security reductions”, and are used to demonstrate the difficulty of cracking the encryption algorithm. In other words, the security of a given cryptographic algorithm is reduced to the security of a known hard problem. Researchers are actively looking for security reductions in the prospects for post quantum cryptography.

In his paper titled “A primer on Post Quantum Cryptography”, the author dwells on the current scenario in the research area of Post Quantum Cryptography and focuses on two developments made to date in the area viz. Ring Learning With Errors (R-LEW) and New Hope Key Encapsulation Mechanism (KEM).

In continuation with the series of articles, we bring you two installments of Experiential Learning of networking technologies. In the first one, the authors discuss at length on the topic of Evolution of socket programming. The second one, ‘Understanding Network Layer & IP Addressing’, delves into IP addressing and routing. As usual, the exercises at the end of the articles allows the reader to learn these concepts hands-on.

While wishing happy reading to our readers, we also wish them safe and virus-free good health in these times when the foot-print of COVID19 pandemic is growing at a fast rate.

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