The tremendous advancement in embedded systems, miniaturization, and wireless technology had allowed Wireless Body Area Networks (WBAN) to have overwhelming applications in e-healthcare, entertainment, sports/games training, etc. WBAN is a special type of wireless sensor network where bio-sensors are attached or embedded to a single human-body designed to connect various bio-sensors and applications, operate autonomously and observe different vital signs of a human body remotely. Despite its enormous benefits and applications, some of the key challenges in designing heterogeneous WBAN is their energy-efficiency, reliability, and fault-tolerance among the installed bio-sensors. Due to the criticality of services related to WBAN applications, it is imperative to have a high degree of reliability and fault-tolerance, especially in the case of health-care monitoring applications where continuous monitoring of patient’s vital information is required for diagnosis. However, in health-care applications, interference and body fading occur, which affect the communication among nodes and gateway, which reduces the reliability and fault-tolerance of the network. To address these issues, in this paper, we have proposed an energy-efficient fault-tolerant scheme to improve the reliability of WBANs. The proposed scheme adopted the cooperative communication and network coding strategy to minimize channel impairment and body fading effect and hence reduces the ensued faults, bit error rate, and energy consumption. Based on the proposed scheme, a case study was designed for remote Sepsis monitoring. The system identifies tracking indicators using cooperative communication to reduce hospital re-admissions and mortality rates. The proposed scheme performance is also evaluated via extensive simulations using various metrics. From the results obtained, it is evident that the proposed scheme reduces energy consumption, delay, and bit error rate, thereby increasing the throughput and reliability in WBAN.

Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.

Vehicular Ad-Hoc Networks (VANETs) deliver a wide range of commercial as well as safety applications and further motivate the advancements of Internet of Vehicles (IoV), Intelligent Transportation Systems (ITS), and Vehicles to Everything (V2X) communication. However, due to their open, distributed, dynamic nature, and protocol design issues, VANETs are vulnerable to a variety of security attacks. One such notorious attack is the Gray-Hole Attack (GHA), commonly has two variants: Smart GHA and Sequence Number-based GHA. In Smart GHA, the malicious node behaves normally during the route discovery process, while in Sequence Number-based GHA, the malicious node starts misbehaving during the route discovery process. In either case, once the route is successfully established, it starts dropping the packets. In this paper, a novel security approach called “Detection and Prevention of GHA” (DPGHA) is proposed to detect and prevent both variants of GHA in Ad-Hoc On-Demand Distance Vector (AODV) based VANETs. The approach is based on the generation of dynamic threshold values of abnormal differences of received, forwarded, and generated control or data packets among nodes and their sequence numbers. The proposed DPGHA is implemented and tested in NS-2 and SUMO simulators and its various performances are compared with the most relevant benchmark approaches. The results showed that the proposed DPGHA performed better than the benchmark approaches in terms of reduced routing overhead by 10.85% and end-to-end delay by 3.85%, increased Packet Delivery Ratio (PDR) by 4.67% and throughput by 6.58%, and achieved a maximum detection rate of 2.3%.

Due to the lack of centralized identity management and the broadcast nature of wireless ad hoc networks, identity attacks are always tempting. The attackers can create multiple illegitimate (arbitrary or spoofed) identities on their physical devices for various malicious reasons, such as to launch Denial of Service attacks and to evade detection and accountability. In one scenario, the attacker creates more than one identity on a single physical device, which is called a Sybil attack. In the other one, the attacker creates cloned/replicated nodes. We refer collectively to these attacks as identity attacks. Using these malicious techniques, the attacker would perform activities in the network for which the attacker may not be authorized. In the existing literature, these attacks are often counteracted separately. However, in this paper, we propose a solution to counteract both attacks jointly. Our proposed scheme uses the received signal strength for the detection without using extra hardware (such as GPS, antennae or air monitors) and centralized entities (such as trusted third party or certification authority). Upon the detection of malicious identities, they will be quarantined and will be blacklisted for future data communication by the mobile nodes. Our proposed attack detector detects the presence of Sybil attacks and replication attacks locally by analysing the received signal strength captured by each node. Moreover, we propose a technique that will identify these attacks in the overall network. In both local and global cases, we evaluate our solutions theoretically and via simulation in NS-2. The obtained results demonstrate that it is possible to detect identity attacks with considerable accuracy without causing extra overhead in the form of extra hardware, periodic beacons or expensive localization operations in the wireless ad hoc networks.

Oral cancer is a complex disorder. Its creation and spreading are due to the interaction of several proteins and genes in different biological thoroughfares. To study biological pathways, many high-yield methods have been used. Efforts to merge several data found at separate levels related to biological thoroughfares and interlinkage networks remain elusive. In our research work, we have proposed a technique known as protein-protein interaction network for analysis and exploring the genes involved in oral cancer disorders. The previous studies have not fully analyzed the proteins or genes involved in oral cancer. Our proposed technique is fully interactive and analyzes the data of oral cancer disorder more accurately and efficiently. The methods used here enabled us to observe the wide network consists of one mighty network comprising of 208 nodes 1572 edges which connect these nodes and various detached small networks. In our study, TP53 is a gene that occupied an important position in the network. TP53 has a 113-degree value and 0.03881821 BC value, indicating that TP53 is centrally localized in the network and is a significant bottleneck protein in the oral cancer protein-protein interaction network. These findings suggested that the pathogenesis of oral cancer variation was organized by means of an integrated PPI network, which is centered on TP53. Furthermore, our identification shows that TP53 is the key role-playing protein in the oral cancer network, and its significance in the cellular networks in the body is determined as well. As TP53 (tumor protein 53) is a vital player in the cell division process, the cells may not grow or divide disorderly; it fulfills the function of at least one of the gene groups in oral cancer. However, the latter progression in the area is any measure; the intention of developing these networks is to transfigure sketch of core disease development, prognosis, and treatment.

The Internet of Things (IoT) is a new paradigm that connects objects to provide seamless communication and contextual information to anyone, anywhere, at any time (AAA). These Internet-of-Things-enabled automated objects interact with visitors to present a variety of information during museum navigation and exploration. In this article, a smart navigation and information system (SNIS) prototype for museum navigation and exploration is developed, which delivers an interactive and more exciting museum exploration experience based on the visitor’s personal presence. The objects inside a museum share the information that assist and navigate the visitors about the different sections and objects of the museum. The system was deployed inside Chakdara Museum and experimented with 381 users to achieve the results. For results, different users marked the proposed system in terms of parameters such as interesting, reality, ease of use, satisfaction, usefulness, and user friendly. Of these 381 users, 201 marked the system as most interesting, 138 marked most realistic, 121 marked it as easy-in-use, 219 marked it useful, and 210 marked it as user friendly. These statistics prove the efficiency of SNIS and its usefulness in smart cultural heritage, including smart museums, exhibitions and cultural sites.