Filtered orthogonal frequency division multiplexing (F-OFDM), a technology which is being considered as a promising platform for beyond 4G era is expected to help deliver the new features at millimeter wave in the new 5 th generation of cellular communication. Some of its key features notably better spectral utilization, enhanced throughput and immunity to interference can be enabling for the new cellular standards. These features of filtered OFDM comes with strict requirements of filter design, guard tone managements, and efficient channel state information harness. This paper is intended to propose an intuitive channel estimation scheme which will allow efficient acquisition of channel state information (CSI) through exploiting the redundant steps of the conventional pilot training-based algorithms and by also using an adaptive weight to expedite the minimization of the error between the estimated values and the actual values. Various simulations will follow to demonstrate the superiority of the scheme over traditional pilot-based algorithms and thus prove its utility in the current 5G cellular era.

With the rapid spread of Internet of Things (IoT) systems enhancing the development of IoT applications, the issue of designing a secure routing algorithm for IoT, including reasonable trust management, has attracted more and more research attention. The unique characteristics of IoT networks make them vulnerable to attacks due to the resource-constrained nature of IoT and the complex distribution of the network. Moreover, the sensors deployed in these kinds of networks are also energy-constrained. It is a challenging task to implement security in IoT networks when the design consideration comprises light weighted security mechanisms and routing protocols due to the insight that security is pricy regarding memory, computational power, and CPU cycles. The adoption of bio-inspired approaches contributes to discovering the optimal path for IoT routing by modeling the cognitive behavior of insect colonies to attain security cost-effectively. For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. Implemented in MATLAB, the assessment results of the proposed routing algorithm are benchmarked to demonstrate that it has minimized the average energy consumption by nearly 50% even as the number of nodes has increased compared to the existing standard and secure routing protocols.

paper presents a simplified yet innovative computational framework to enable secure routing for sensors within a vast and dynamic Internet of Things (IoT) environment. In the proposed design methodology, a unique trust evaluation scheme utilizing a modified version of Ant Colony Optimization (ACO) is introduced. This scheme formulates a manifold criterion for secure data transmission, optimizing the sensor's residual energy and trust score. A distinctive pheromone management is devised using trust score and residual energy. Concurrently, several attributes are employed for constraint modeling to determine a secure data transmission path among the IoT sensors. Moreover, the trust model introduces a dualtiered system of primary and secondary trust evaluations, enhancing reliability towards securing trusted nodes and alleviating trust-based discrepancies. The comprehensive implementation of the proposed integrates mathematical modeling, leveraging a streamlined bioinspired approach of the revised ACO using crowding distance. Quantitative results demonstrate that our approach yields a 35% improvement in throughput, an 89% reduction in delay, a 54% decrease in energy consumption, and a 73% enhancement in processing speed compared to prevailing secure routing protocols. Additionally, the model introduces an efficient asynchronous updating rule for local and global pheromones, ensuring greater trust in secure data propagation in IoT.

Blockchain technology is based on the idea of a distributed, consensus ledger, which it employs to create a secure, immutable data storage and management system. It is a publicly accessible and collectively managed ledger enabling unprecedented levels of trust and transparency between business and individual collaborations. It has both robust cryptographic security and a transparent design. The immutability feature of blockchain data has the potential to transform numerous industries. People have begun to view blockchain as a revolutionary technology capable of identifying "The Best Possible Solution" in various real-world scenarios. This paper provides a comprehensive insight into blockchains, fostering an objectual understanding of this cutting-edge technology by focusing on the theoretical fundamentals, operating principles, evolution, architecture, taxonomy, and diverse application-based manifestations. It investigates the need for decentralisation, smart contracts, permissioned and permissionless consensus mechanisms, and numerous blockchain development frameworks, tools, and platforms. Furthermore, the paper presents a novel compendium of existing and emerging blockchain technologies by examining the most recent advancements and challenges in blockchain-enabled solutions for a variety of application domains. This survey bridges multiple domains and blockchain technology, discussing how embracing blockchain technology is reshaping society's most important sectors. Finally, the paper delves into potential future blockchain ecosystems providing a clear picture of open research challenges and opportunities for academics, researchers, and companies with a strong fundamental and technical grounding.

Mobile ad hoc networks are susceptible to various security threats due to their open media nature and mobility, making them a top priority for security measures. This paper provides an in-depth examination of MANET security issues. Some of the most critical aspects of mobile ad hoc networks, including their applications, have been discussed. This is followed by a discussion of MANETs' design vulnerability to external and internal security threats caused by inherent network characteristics such as limited battery power, mobility, dynamic topology, open media, and so on. Numerous MANET-related attacks have been classified based on their sources, behaviour, participating nodes, processing capability, and layering. The many different types of misbehaviour a node can exhibit and the various ways a node can behave were investigated. Two major types of MANETs misbehaviour have been evaluated, classified and analysed. Notably, mitigating node misbehaviour in MANET is a critical issue that must be addressed to ensure network node functionality and availability. Strategies for detecting network nodes that misroute packets are also examined. Finally, the paper emphasises the need for effective solutions to secure MANETs.

This paper introduces a computational strategic game model capable of mitigating the adversarial impact of node misbehaviour in large-scale Internet of Things (IoT) deployments. This security model’s central concept is to preclude the participation of misbehaving nodes during the routing process within the ad hoc environment of mobile IoT nodes. The core of the design is a simplified mathematical algorithm that can strategically compute payoff embrace moves to maximise gain. At the same time, a unique role is given to a node for restoring resources during communication or security operations. Adopting an analytical research methodology, the proposed model uses public and private cloud systems for integrating quality service delivery with secure agreements using a Global Trust Controller and core node selection controller to select an intermediate node for data propagation. The initiation of the game model is carried out by identifying mobile node role followed by choosing an optimal payoff for a normal IoT node. Finally, the model leads to an increment of gain for selecting the regular IoT node for routing. The findings of the evaluation indicate that the proposed scheme offers 36% greater accuracy, 25% less energy, 11% faster response time, and 27% lower cost than the prevalent game-based models currently used to solve security issues. The value added by the proposed study is the simplified game model which balances both security demands and communication demands.

The Internet of Things (IoT) is the evolving paradigm of interconnectedness of objects with varied architectures and resources to provide ubiquitous and desired services.The popularization of IoT-connected devices facilitating evolution of IoT applications does come with security challenges.The IoT with the integration of wireless sensor networks possess a number of unique characteristics, so the implementation of security in such a restrictive environment is a challenging task.Due to the perception that security is expensive in terms of computation, power and user-interface components, and as sensor nodes or low-power IoT objects have limited resources, it is desired to design security mechanisms especially routing protocols that are light weighted.Bio-inspired mechanisms are shown to be adaptive to environmental variations, robust and scalable, and require less computational and energy resources for designing secure routing algorithms for distributed optimization.In IoT network, the malicious intruders can exploit the routing system of the standardized routing protocol, e.g., RPL (The Routing Protocol for Low-Power and Lossy Networks), that does not observe the node's routing behavior prior to data forwarding, and can launch various forms of routing attacks.To secure IoT networks from routing attacks, a secure trust aware ACO-based WSN routing protocol for IoT is proposed here that establishes secure routing with trustworthy nodes.The trust evaluation system, is enhanced to evaluate the node trust value, identify sensor node misbehavior, and maximize energy conservation.The performance of the proposed routing algorithm is demonstrated through MATLAB.Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT.

The rapid advancement of technologies has enabled businesses to carryout their activities seamlessly and revolutionised communications across the globe. There is a significant growth in the amount and complexity of Internet of Things devices that are deployed in a wider range of environments. These devices mostly communicate through Wi-Fi networks and particularly in smart environments. Besides the benefits, these devices also introduce security challenges. In this paper, we investigate and leverage effective feature selection techniques to improve intrusion detection using machine learning methods. The proposed approach is based on a centralised intrusion detection system, which uses the deep feature abstraction, feature selection and classification to train the model for detecting the malicious and anomalous actions in the traffic. The deep feature abstraction uses deep learning techniques of artificial neural network in the form of unsupervised autoencoder to construct more features for the traffic. Based on the availability of cumulative features, the system then employs a variety of wrapper-based feature selection techniques ranging from SVM and decision tree to Naive Bayes for selecting high-ranked features, which are then combined and fed into an artificial neural network classifier for distinguishing attack and normal behaviors. The experimental results reveal the effectiveness of the proposed method on Aegean Wi-Fi Intrusion Dataset, which achieves high detection accuracy of up to 99.95%, relatively competitive to the existing machine learning works for the same dataset.

The problem of developing effective and secure routing protocols has drawn more interest in network research with the popularization of IoT-connected devices. The perception of ensuring security is expensive in terms of computation, power and user-interface components because of low-power IoT objects or sensor nodes. Secret keys distribution schemes are computationally expensive and require more resources. Rather, bio-inspired mechanisms are considered more robust as they offer optimal and inexpensive solutions for designing secure routing algorithms for their inherent adaptable and scalable features. Moreover, trusted neighbor discovery is a crucial task. That is why a complementary security measure, trust evaluation system, is adopted here. In this paper, a secure bio-inspired WSN (Wireless Sensor Network) routing protocol based on ant colony optimization (ACO) algorithm for IoT has been proposed and analyzed to find secure and optimal path that is energy-efficient as well as aiming at providing trust in IoT environment. The performance of the proposed routing algorithm is evaluated utilizing MATLAB. The assessment results indicate that it can find the forwarding path with comparatively low cost in the premise of ensuring security and has minimized the average energy consumption by nearly 50% even as the number of nodes has increased, when compared with the traditional ACO algorithm, an existing ant colony based routing algorithm and a current routing protocol for IoT.

Mobile Adhoc Network (MANET) has been a core topic of research since the last decade. Currently, this form of networking paradigm is increasingly being construed as an integral part of upcoming urban applications of Internet-of-Things (IoT), consisting of massive connectivity of diverse types of nodes. There is a significant barrier to the applicability of existing routing approaches in conventional MANETs when integrated with IoT. This routing mismatch can lead to security risks for the MANET-based application tied with the IoT platform. This paper examines a pragmatic scenario as a test case wherein the mobile nodes must exchange multimedia signals for supporting real-time streaming applications. There exist two essential security requirements viz. i) securing the data packet and ii) understanding the unpredictable behavior of the attacker. The current study considers sophistication on the part of attacker nodes. They are aware of each other's identity and thereby collude to conduct lethal attacks, which is rarely reflected in existing security modeling statistics. This research harnesses the potential modeling aspect of game theory to model the multiple-collusion attacker scenario. It contributes towards i) modeling strategies of regular/malicious nodes and ii) applying optimization principle using novel auxiliary information to formulate the optimal strategies. The model advances each regular node's capability to carry out precise computation about the opponent player's strategy prediction, i.e., malicious node. The simulation outcome of the proposed mathematical model in MATLAB ascertains that it outperforms the game theory's baseline approach.

The 5th generation of cellular system is expected to incur a huge traffic rise which would necessitate the adoption of an estimation method that is efficient but at the same time practical through easy implementation. Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. Both of them has their own merits and limitations. While LS estimation is simple to adopt and resource-friendly, its performance is par to MMSE, which requires channel statistics and is thus more impractical for the industry. In this paper, an efficient LS estimation method is proposed by minimising relative error or difference between each estimated channel coefficient from its actual value, which is often overlooked when considering overall error. It’s in turn, reduces the error per bit and eventually induces faster processing of data. Results on the proposed algorithm are demonstrated via bit error rate and mean square error comparison.

By and large, authentication systems employed for web-based applications primarily utilize conventional username and password-based schemes, which can be compromised easily. Currently, there is an evolution of various complex user authentication schemes based on the sophisticated encryption methodology. However, many of these schemes suffer from either low impact full consequences or offer security at higher resource dependence. Furthermore, most of these schemes don't consider dynamic threat and attack strategies when the clients are exposed to unidentified attack environments. Hence, this paper proposes a secure user authentication mechanism for web applications with a frictionless experience. An automated authentication scheme is designed based on user behavior login events. The uniqueness of user identity is validated in the proposed system at the login interface, followed by implying an appropriate user authentication process. The authentication process is executed under four different login mechanisms, which depend on the profiler and the authenticator function. The profiler uses user behavioral data, including login session time, device location, browser, and details of accessed web services. The system processes these data and generates a user profile via a profiler using the authenticator function. The authenticator provides a login mechanism to the user to perform the authentication process. After successful login attempts, the proposed system updates database for future evaluation in the authentication process. The study outcome shows that the proposed system excels to other authentication schemes for an existing web-based application. The proposed method, when comparatively examined, is found to offer approximately a 10% reduction in delay, 7% faster response time, and 11% minimized memory usage compared with existing authentication schemes for premium web-based applications.

A R T I C L E I N F O A B S T R A C T Article history: Received: 31 August, 2020 Accepted: 21 December, 2020 Online: 28 December, 2020 IoT integrates and connects intelligent devices or objects with varied architectures and resources. The number of IoT devices is growing exponentially. Due to the massive wave of IoT objects, their diversity and heterogeneity among their architectures, the existing communication protocols for wireless networks become ineffective in the context of IoT. Wireless Sensor Network (WSN) has the potential to be integrated to the internet of things (IoT). The issues of the routing of WSNs impose nearly similar prerequisites for IoT routing technique. Most of the traditional routing protocols are not appropriate for WSNs and IoT because of resource constraints, computational overhead and environmental interference and do not take into account the different factors affecting energy parameter and do not accommodate node mobility. Routing algorithms must ensure the data transmission in an efficient way, having proper knowledge of the IoT system. For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network’s dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. The proposed routing algorithm is simulated using MATLAB for performance evaluations. The evaluation results have recorded an improvement in conservation of energy, of almost 50% less consumed energy even with an increase in the number of nodes, by comparing with an existing routing technique based on ant system, a current routing protocol for IoT and the conventional ACO algorithm.

Internet-banking is a crucial service offered by financial Institutions and has gained popularity at a high pace. Owing to the increasing usage of this service, it is being frequently targeted by adversaries. The login process by the user is one of the main points that are at risk of this assault. Hence, a robust security mechanism is essential for warding off those risks. Among other security solutions, a typical arrangement presently employed is the one-time password (OTP), i.e., passwords that remain valid for a single exchange or session. However, the majority of these password generation and processing mechanisms do not fulfil the requirement of usability and/or scalability and hence can be considered as less reliable/fragile. This paper reviews the security mechanisms in E-banking. The pros and con of OTP as well as other non-OTP security solutions have been presented. Finally, the prominence of open issues have been elucidated.

The Mobile Ad-Hoc Network (MANET) incorporates a collaborative networking scenario, where dynamic host movement results in frequent topology changes. In MANET, nodes cooperate during route establishment, and the data packet must travel from source to destination through multi-hop intermediate links. The nodes in a MANET can be localized in a restricted zone, where manual intervention to set-up fixed infrastructural support is practically infeasible. However, cooperative packet forwarding and data transmission is quite a common scenario in the context of MANET. Still, due to dynamic topological changes, weak, intermittent links appear within one-hop communication. This leads to a higher possibility of packet drop events and also increases the retransmission scenario, which affects the energy performance of the network. Addressing this issue, the study models a novel and intelligent packet forwarding approach based on the game theory, where trust evaluation in terms of node reputation factor also plays a very vital role. The approach also enforces an incentive modelling to stimulate the cooperation between mobile nodes during the MANET routing scenario. The system is designed and developed with evolutionary game perspectives to meet the Quality of Services (QoS) requirements. The experimental analysis supports the proposed modelling design aspects. Also, it exhibits that the reputation and trust-based game increases the utility of packet-forwarding strategy with high throughput and negligible network overhead.

The progressively ubiquitous connectivity in the present information systems pose newer challenges tosecurity. The conventional security mechanisms have come a long way in securing the well-definedobjectives of confidentiality, integrity, authenticity and availability. Nevertheless, with the growth in thesystem complexities and attack sophistication, providing security via traditional means can beunaffordable. A novel theoretical perspective and an innovative approach are thus required forunderstanding security from decision-making and strategic viewpoint. One of the analytical tools whichmay assist the researchers in designing security protocols for computer networks is game theory. Thegame-theoretic concept finds extensive applications in security at different levels, including thecyberspace and is generally categorized under security games. It can be utilized as a robust mathematicaltool for modelling and analyzing contemporary security issues. Game theory offers a natural frameworkfor capturing the defensive as well as adversarial interactions between the defenders and the attackers.Furthermore, defenders can attain a deep understanding of the potential attack threats and the strategiesof attackers by equilibrium evaluation of the security games. In this paper, the concept of game theoryhas been presented, followed by game-theoretic applications in cybersecurity including cryptography.Different types of games, particularly those focused on securing the cyberspace, have been analysed andvaried game-theoretic methodologies including mechanism design theories have been outlined foroffering a modern foundation of the science of cybersecurity.

Mastitis is the most commonly diagnosed infectious disease reducing milk yield and quality and is accompanied by mammary tissue damage in both humans and animals. Mastitis incurs welfare and economic costs as well as environmental concerns regarding treatment. Staphylococcus aureus (S. aureus) is a prevalent Gram-positive bacteria and a major cause of mastitis, however, pathogenesis of the intrinsic anti-inflammatory response in mammary tissues is still principally unknown. Our aim, in combatting the S. aureus induced inflammatory response in mammary tissues, was to elucidate the intrinsic anti-inflammatory role of MerTK signaling. Here, we demonstrate that Mer receptor tyrosine kinase (MerTK) regulates an intrinsic negative feedback to balance the over-reaction of the host defense system. S. aureus elicits toll-like receptors 2 and 6 (TLR2/TLR6) signaling pathways, subsequently recruiting TRAF6, whose ubiquitination is intricate to the downstream signaling including MAPKs and NF-κB. We observed that TLR2/TLR6 activation, in response to S. aureus, was concomitant with induced MerTK activation, leading to raised expression of suppressor of cytokine signaling 1 and 3 (SOCS1, SOCS3) in wild type mice mammary tissues and epithelial cells. Meanwhile, S. aureus infection in MerTK-/- mice showed significant increased phosphorylation of p65, IκBα, p38, JNK and ERK along with production of pro-inflammatory cytokines. Moreover, MerTK-/- evidently inhibited S. aureus induced phosphorylation of STAT1 and subsequent SOCS1/SOCS3 expression which are pivotal in the negative feedback mechanism for targeting TRAF6 to inhibit the TLR2/TLR6 mediated immune response. Taken together, our findings demonstrate the importance of MerTK in the regulation of the intrinsic feedback during the inflammatory response induced by S. aureus through STAT1/SOCS1/SOCS3 in mice mammary tissues and mice mammary epithelial cells (MMECs).

Currently, Mobile Ad hoc Networks (MANETs) have evolved as one of the essential next-generation wireless network technologies. MANET comprises of mobile nodes that are self-configurable, and every mobile node behaves as a router for every other node allowing data to move by making use of multi-hop network routes. MANETs signify a networking class that is crucial and differs from conventional systems. Although MANETs are being popularly employed in commercial as well as academic fields, these were primarily designed for deployment in areas like military battlefields, emergency rescue and search operations, and other challenging or hostile environments. The distributed and wireless nature of MANETs paves the way for intruders to reduce MANET functionalities. MANET are susceptible to various attack at different layers since the majority of MANET routing protocols are designed with the assumption that no malicious intruder is present in the network. Therefore, recognizing those threats and finding solutions for their mitigation become essential. This study analyses various security attributes, challenges, attacks on multiple layers and countermeasures for thwarting attacks in MANETs.

The current era of smart computing and enabling technologies encompasses the Internet of Things (IoT) as a network of connected, intelligent objects where objects range from sensors to smartphones and wearables. Here, nodes or objects cooperate during communication scenarios to accomplish effective throughput performance. Despite the deployment of large-scale infrastructure-based communications with faster access technologies, IoT communication layers can still be affected with security vulnerabilities if nodes/objects do not cooperate and intend to take advantage of other nodes for fulfilling their malevolent interest. Therefore, it is essential to formulate an intrusion detection/prevention system that can effectively identify the malicious node and restrict it from further communication activities-thus, the throughput, and energy performance can be maximized to a significant extent. This study introduces a combined multi-agent and multilayered game formulation where it incorporates a trust model to assess each node/object, which is participating in IoT communications from a security perspective. The experimental test scenarios are numerically evaluated, where it is observed that the proposed approach attains significantly improves intrusion detection accuracy, delay, and throughput performance as compared to the existing baseline approaches.