IoT Device Fingerprint using Deep Learning

Device Fingerprinting (DFP) is the identification of a device without using its network or other assigned identities including IP address, Medium Access Control (MAC) address, or International Mobile Equipment Identity (IMEI) number. DFP identifies a device using information from the packets which the device uses to communicate over the network. Packets are received at a router and processed to extract the information. In this paper, we worked on the DFP using Inter Arrival Time (IAT). IAT is the time interval between the two consecutive packets received. This has been observed that the IAT is unique for a device because of different hardware and the software used for the device. The existing work on the DFP uses the statistical techniques to analyze the IAT and to further generate the information using which a device can be identified uniquely. This work presents a novel idea of DFP by plotting graphs of IAT for packets with each graph plotting 100 IATs and subsequently processing the resulting graphs for the identification of the device. This approach improves the efficiency to identify a device DFP due to achieved benchmark of the deep learning libraries in the image processing. We configured Raspberry Pi to work as a router and installed our packet sniffer application on the Raspberry Pi . The packet sniffer application captured the packet information from the connected devices in a log file. We connected two Apple devices iPad4 and iPhone 7 Plus to the router and created IAT graphs for these two devices. We used Convolution Neural Network (CNN) to identify the devices and observed the accuracy of 86.7%

Chemical Weed Management in Maize (<em>Zea mays</em> L.) under Conservation Agricultural Systems: An Outlook of the Eastern Gangetic Plains in South-Asia

Maize is a widely grown cereal after rice and wheat and contributes almost 5% to the global dietary supply. In the Eastern Gangetic Plains (EGP) including India, Bangladesh, and Nepal, maize is an emerging cash crop, because of its high yield potentiality and also the favorable climatic conditions which allow maize production round the year. In Bangladesh, area and production of maize are escalating due to the increasing demand for poultry, livestock, and fish feed, and fodder for animals and starch industries in the region. Presently, more than 90% of maize is planted by manual dibbling following 5–6 intensive tillage, which increases the cost of cultivation. The conservation agricultural (CA)-based new agricultural practices could overcome those above challenges. CA is cost-effective and environmentally friendly; however, weeds are one of the key challenges in the system. The chapter described the uses of herbicides in different ways of combinations to make effective weed control in CA-based maize to achieve potential production and profits by reducing the intensive pressure of manual weeding. The efficient and right use of pre-plant/sowing, pre- and post-emergence herbicides and their combination may be the best way for effective control of weeds in maize production

Blockchain-enabled Secure Privacy-preserving System for Public Health-center Data

Health center data implicates a large scale of individual health records and is immensely concealment sensory. In the virtual era of large-size data, the increasingly different health informatization causes it important that health data needs to be stored precisely and securely. However, daily health data transactions carry the risk of privacy leaks that make sharing difficult. Moreover, the recently permitted blockchain applications suffer from deficient performance and lack of privacy. This study presents a privacy-preserving and secure sharing and storage system for public health centers based on the blockchain method to dispose of these issues. This system utilizes a hash-256-based access controller and transaction signature with the consensus policy and provides security to share and store health data in the blockchain. In this approach, blockchain guarantees scalability, privacy, integrity, and availability for data retention. Also, this paper measures the performance of transactions with supporting confidentiality-preserving and shows the average transaction time and acceptable latency when accessing health data

EduChain: CIA-Compliant Block-chain forIntelligent Cyber Defense of Microservices inEducation Industry 4.0

This is an accepted manuscript of an article published by IEEE in IEEE Transactions on Industrial Informatics, available online: https://ieeexplore.ieee.org/document/9468408 The accepted version of the publication may differ from the final published version.Massive data handling requirement in education industry 4.0 has attracted interests in the research of microservice architectures due to their scalability, resilience and elasticity characteristics. This development has been challenged by extensive data exchange required by a set of independent microservices tobuilda complete application, which could resultin increasing risksandexposuretothe securityand privacy breaches of the data. It is imperative to see that educational data are highly sensitive, critical for ascertaining educational attainment and facilitating credentials for qualifcation verifcations. This paper puts forward a new proposal of devising a security and privacy-preserving design mechanism of data transactions in educational microservices leveraging the blockchain technology. The design comprises three phases, namely the blockchain framework, data sending-receiving and confdentiality-integrity-availability over a secured platform with each phase having detailed mechanisms for algorithm implementation. The proposal is shown to exhibit favourable performance in terms of time cost of publishing, throughput and latency, and shown to have high surveyacceptance in terms of confdentiality, integrity and availability with approximately 10% improvement from prior blockchain adoption

EduChain: CIA-compliant blockchain for intelligent cyber defense of microservices in education industry 4.0

Massive data handling requirement in education Industry 4.0 has attracted interests in the research of microservice architectures due to their scalability, resilience, and elasticity characteristics. This development has been challenged by extensive data exchange required by a set of independent microservices to build a complete application, which could result in increasing risks and exposure to the security and privacy breaches of the data. It is imperative to see that educational data are highly sensitive, critical for ascertaining educational attainment and facilitating credentials for qualification verifications. This article puts forward a new proposal of devising a security and privacy-preserving design mechanism of data transactions in educational microservices leveraging the blockchain technology. The design comprises three phases, namely the blockchain framework, data sending-receiving, and confidentiality-integrity-availability over a secured platform with each phase having detailed mechanisms for algorithm implementation. The proposal is shown to exhibit favorable performance in terms of time cost of publishing, throughput, and latency, and shown to have high survey acceptance in terms of confidentiality, integrity, and availability with approximately 10% improvement from prior blockchain adoption

Fingerprint authentication-based traffic offence control and enforcement system on smart mobile devices for smart city

The evolution of communication and information technology in today's time should not despise the various practical aspects of daily life, regardless of economic, education, health, or other government services. Various functions of smart mobile devices meet the needs of users in many ways, where different mechanisms like templates, locks, fingerprints, and passwords are used to protect those functions. Due to the increased number of vehicles in smart cities, it becomes difficult for traffic officers with less manpower to complete many of their tasks related to registration, license, and issuance of summons in time, even reviewing the traffic violation's history. In addition, existing traffic systems are not real-time, data related to traffic management can be lost at any time, leading to the wastage of money and resources. To overcome these difficulties in smart cities, this paper proposes a fingerprint authentication-based traffic offence control-and-enforcement system on smart mobile devices. This scheme introduces a security framework to facilitate many tasks related to identification, registration, licensing, and issuance of summons to traffic violators by implementing fingerprint authentication. Functionality tests and user acceptance tests related to traffic offence problems have been conducted on the proposed system by analyzing biometric data of vehicle users' fingerprints

Blockchain-enabled cybersecurity provision for scalable heterogeneous network: A comprehensive survey

Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system diversity, bandwidth diversity, node diversity, etc., for decision-making of data transactions across blockchain-based heterogeneous networks. Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems. To address these issues, today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain. The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network. This paper proposes a full-fledged taxonomy to identify the main obstacles, research gaps, future research directions, effective solutions, and most relevant blockchain-enabled cybersecurity systems. In addition, Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper to meet the goal of maintaining optimal performance data transactions among organizations. Overall, this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network

Growth and yield of five irrigated spring wheat varieties as influenced by seeding rate in Old Himalayan Piedmont Plain of Bangladesh

Farmers in Bangladesh are always seeking an optimal seed rate to reduce production costs and increase wheat yield. The Wheat Research Centre (WRC) of Bangladesh has developed new wheat varieties over several years. To reduce production costs and obtain higher grain yield (GY) from these varieties, optimum seeding rates are needed. In this context, a two-year field experiment was conducted with five newly released wheat varieties (‘BARI Gom 24’, ‘BARI Gom 25’, ‘BARI Gom 26’, ‘BARI Gom 27’ and ‘BARI Gom 28’) and three seeding rates (100, 120 and 140 kg ha─1). These treatments were performed under irrigation in the WRC research field in Northern Bangladesh to determine the optimum seeding rates for these varieties. Significantly higher GY (p≤0.05) was obtained with a seeding rate of 140 kg ha─1 for all varieties, compared to other rates. A seeding rate less than the recommended rate (120 kg ha─1) for all varieties failed to produce comparable GY in both years. Among all varieties, ‘BARI Gom 26’ had the highest GY while ‘BARI Gom 25’ had the lowest GY in both years. Although the interaction effect of variety and seeding rate on GY did not vary significantly (p≤0.05) in both years, surplus GY was 467 and 233 kg ha─1, respectively for ‘BARI Gom 24’, 63 and 75 kg ha─1 for ‘BARI Gom 25’, 81 and 93 kg ha─1 for ‘BARI Gom 26’, 23 and 66 kg ha─1 for ‘BARI Gom 27’, and 152 and 220 kg ha─1 for ‘BARI Gom 28’ in the first and second year when seeded at 140 kg ha─1. For the same seed rate, the GY of ‘BARI Gom 24’ increased by 5.3 to 9.6% and that of ‘BARI Gom 28’ increased from 2.8 to 5% over the two years. Therefore, a seeding rate of 140 kg seed ha─1 is recommended for ‘BARI Gom 24’ and ‘BARI Gom 28’, while the current recommended rate (120 kg ha─1) should be continued for the other three varieties when grown under irrigation on the Old Himalayan Piedmont Plain of Bangladesh