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Quality of service (QoS)-aware data gathering in static-channel based underwater wireless sensor networks (UWSNs) is severely limited due to location and time-dependent acoustic channel communication characteristics. This paper proposes a novel cross-layer QoS-aware multichannel routing protocol called QoSRP for the internet of UWSNs-based time-critical marine monitoring applications. The proposed QoSRP scheme considers the unique characteristics of the acoustic communication in highly dynamic network topology during gathering and relaying events data towards the sink. The proposed QoSRP scheme during the time-critical events data-gathering process employs three basic mechanisms, namely underwater channel detection (UWCD), underwater channel assignment (UWCA) and underwater packets forwarding (UWPF). The UWCD mechanism finds the vacant channels with a high probability of detection and low probability of missed detection and false alarms. The UWCA scheme assigns high data rates channels to acoustic sensor nodes (ASNs) with longer idle probability in a robust manner. Lastly, the UWPF mechanism during conveying information avoids congestion, data path loops and balances the data traffic load in UWSNs. The QoSRP scheme is validated through extensive simulations conducted by NS2 and AquaSim 2.0 in underwater environments (UWEs). The simulation results reveal that the QoSRP protocol performs better compared to existing routing schemes in UWSNs.

Energy-efficient and reliable data gathering using highly stable links in underwater wireless sensor networks (UWSNs) is challenging because of time and location-dependent communication characteristics of the acoustic channel. In this paper, we propose a novel dynamic firefly mating optimization inspired routing scheme called FFRP for the internet of UWSNs-based events monitoring applications. The proposed FFRP scheme during the events data gathering employs a self-learning based dynamic firefly mating optimization intelligence to find the highly stable and reliable routing paths to route packets around connectivity voids and shadow zones in UWSNs. The proposed scheme during conveying information minimizes the high energy consumption and latency issues by balancing the data traffic load evenly in a large-scale network. In additions, the data transmission over highly stable links between acoustic nodes increases the overall packets delivery ratio and network throughput in UWSNs. Several simulation experiments are carried out to verify the effectiveness of the proposed scheme against the existing schemes through NS2 and AquaSim 2.0 in UWSNs. The experimental outcomes show the better performance of the developed protocol in terms of high packets delivery ratio (PDR) and network throughput (NT) with low latency and energy consumption (EC) compared to existing routing protocols in UWSNs.INDEX TERMS Internet of Underwater Things, bio-inspired routing, firefly mating optimization, underwater wireless sensor network, routing protocol. I. INTRODUCTIONThe oceans contain about 96.5% of all earth water is extremely important for the survivability of human life since it provides nourishment, natural resources, ways of transportation, greater defense margin and several other benefits. However, a vast portion of the oceans around 95% is still unexplored due to the lack of appropriate acoustic communication technologies. Recently, significantThe associate editor coordinating the review of this manuscript and approving it for publication was Ilsun You . advancements in the Internet of underwater things (IoUT) technology have facilitated the exploration process of the oceans by connecting various ubiquitous sensor devices to provide reliable and efficient data collection in UWSNs [1], [2]. The acoustic sensor nodes (ASNs) in underwater acoustic sensor networks (UASNs) have the potentials to monitor real-time underwater events with failure detection and self-organizing capabilities. Therefore, UASNs have received significant attention in a variety of ocean monitoring applications, such as navigation assistance, tactical surveillance, mine recognition, underwater pollution analysis and

Recently, the advences of Industry 4.0 have paved the way for a systematical deployment of the smart grid (SG) to manage continuously growing energy demand of the 21st century. This even allows the fourth stage of the industrial revolution in the power sector, which is known as the smart grid industry (SGI) 4.0. In SGI 4.0, the industrial wireless sensor networks (WSNs) and the Internet of Things are envisioned as key promising communication technologies for monitoring various SG applications due to their large-scale coverage, fault tolerance characteristics, and cost reduction. However, highly dynamic nature of the SG environments brings several unique challenges caused by systems and operating devices. This results in hampering the quality-of-service communication requirements for WSNs-based SG applications. In SGI 4.0, the routing infrastructure not only requires a reliable but also fulfills the communication requirements of diverse SG applications. Thus, a sophisticated, reliable and QoS-aware multi-hop communications network architecture enabling a real-time exchange of data for various WSNs-based SG applications is essential in SGI 4.0. Hence, this paper proposes a novel bio-inspired self-optimized butterfly mating optimization-based data gathering routing scheme called Self-optimized Intelligent routing protocol (SIRP) for WSNs-based SG applications. The extensive simulations reveal that the proposed scheme achieves its defined goals compared to existing routing schemes designed for WSNs-based applications.Trans Emerging Tel Tech. 2019;30:e3503.wileyonlinelibrary.com/journal/ett streamline management operations are connected using wired networks working over industrial protocols in traditional factories. However, compared with a wired network, the wireless networking solution plays a complementary role to empower control and management competencies of the factory elements in I 4.0. To this end, industrial wireless sensor networks (IWSNs) are envisioned as a valuable technology to realize the vision of I 4.0 because of their low-cost sensing, identifying, processing, and networking capabilities. The IWSNs provide physical industry world information to a user located in a remote location to realize distinct objectives. 10,11 The fundamental characteristics of IWSN-based networking solution in I 4.0 is to provide least maintenance cost by avoiding excessive breakdowns in a defined time interval for enabling smart production reliability and increasing economic benefits. Therefore, IWSN, with these aims, has revealed its prominence in various industrial applications, including modern agriculture, transportation, steel mills, healthcare systems, area surveillance, gas and oil industry, and many others. 12,13 The quality-of-service (QoS)-aware cooperative multihop communication in IoT-enabled smart grid (SG) is highly dependent on a number of performance metrics like coverage, scalability, stability, latency, lifetime, and complexity of the network. In IoT-enabled SG, IWSNs through IoT connect various industrial ...

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Due to the advancement in industry 4.0, cybercrimes in internet‐based business applications are rapidly increasing. To encounter such attacks, the intruders use various tools and techniques such as Phishing, Malware, SQL Injection, Ransomware, Cross‐Site Scripting (XSS), Denial of Service (DoS), Session Hijacking, and Credential Reuse. Phishing is most commonly in practice in the current digital era. Phishing is a fraudulent attempt to obtain sensitive information from deceiving users. These types of cyber‐attacks are used to harm individuals or entire businesses depending on the targeted objective of the attacker. To combat these attacks, the research community provides various phishing detection techniques. In this article, we classify state‐of‐the‐art fishing detection techniques in five major categories, that are, (1) Data Mining, Deep Learning & Machine Learning‐Based Approach, (2) Search Engine‐Based Approach, (3) URL Scan‐Based Approach, (4) Blacklisting‐Whitelisting Approach, and (5) Visual Similarity‐Based Approach. Further, a comparative analysis is provided within each category concerning their strength and weaknesses. Moreover, the article provides phishing prevention best practices to the readers to avoid such attacks.

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