15,345 research outputs found

    Secured Framework for Smart Farming in Hydroponics with Intelligent and Precise Management based on IoT with Blockchain Technology

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    Hydroponics is a type of soil-free farming that uses less water and other resources than conventional soil-based farming methods. However, due to the simultaneous supervision of multiple factors, nutrition advice, and plant diagnosis system, monitoring hydroponics farming is a difficult task. Hydroponic techniques utilizing the IoT show to deliver the finest outcomes, despite the usage of various artificial culture methods. Though, the usage of smart communication technologies and IoT exposes environments for smart farming to a wide range of cybersecurity risks and weaknesses. However, the adoption of intelligence-based controlling algorithms in the agricultural industry is a good use of current technical advancements to address these issues. This paper presented a secured framework for smart farming in hydroponics system. The proposed architecture is characterized into four-layer IoT based framework, sensor, communication, fog and cloud layer. Data analytics is performed using supervised machine learning techniques with intelligent and precise management and is applied at the fog layer for efficient computation over the cloud layer. The data security over channel is protected by using Blockchain Technology. The experimental results are evaluated and analyzed for several statistical parameters in order to improve the system efficacy

    The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

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    The Internet of Things (IoT) is a dynamic global information network consisting of internet-connected objects, such as Radio-frequency identification (RFIDs), sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organisations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. More importantly, we identify the trends, opportunities and open challenges in the industry-based the IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: smart wearable, smart home, smart, city, smart environment, and smart enterprise. This survey is intended to serve as a guideline and conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201

    Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges

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    open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture

    IoT Sentinel: Automated Device-Type Identification for Security Enforcement in IoT

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    With the rapid growth of the Internet-of-Things (IoT), concerns about the security of IoT devices have become prominent. Several vendors are producing IP-connected devices for home and small office networks that often suffer from flawed security designs and implementations. They also tend to lack mechanisms for firmware updates or patches that can help eliminate security vulnerabilities. Securing networks where the presence of such vulnerable devices is given, requires a brownfield approach: applying necessary protection measures within the network so that potentially vulnerable devices can coexist without endangering the security of other devices in the same network. In this paper, we present IOT SENTINEL, a system capable of automatically identifying the types of devices being connected to an IoT network and enabling enforcement of rules for constraining the communications of vulnerable devices so as to minimize damage resulting from their compromise. We show that IOT SENTINEL is effective in identifying device types and has minimal performance overhead
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