Nowadays, rumor spreading has gradually evolved into a kind of organized behaviors, accompanied with strong uncertainty and fuzziness. However, existing fuzzy detection techniques for rumors focused ...their attention on supervised scenarios that require expert samples with labels for training. Thus, they are not able to well handle the unsupervised scenarios where labels are unavailable. To bridge such gap, this article proposed a fuzzy detection system for rumors through explainable adaptive learning. Specifically, its core is a graph embedding-based generative adversarial network (Graph-GAN) model. First of all, it constructs fine-grained feature spaces via graph-level encoding. Furthermore, it introduces continuous adversarial training between a generator and a discriminator for unsupervised decoding. The two-stage scheme not only solves the fuzzy rumor detection under unsupervised scenarios, but also improves robustness of the unsupervised training. Empirically, a set of experiments are carried out based on three real-world datasets. Compared with seven benchmark methods in terms of four metrics, the results of the Graph-GAN reveal a proper performance, which averagely exceeds baselines by 5-10%.
In recent times, Cyber thieves discover new software vulnerabilities and attack vectors to take advantage of them. Cyber Security (CS) specialists are having a constant battle to stay on top of the ...latest threats. Knowledge sharing, sometimes called intelligence sharing, can enhance collective resilience and responsiveness in the face of dangers if peers are willing to share information proactively. Internet of Things (IoT) is the buzz word which integrates almost all the technology concerning computation and communication. Before the IoT goal can be fully realized, some barriers must be addressed, with security and privacy being two of the most essential. When IoT devices connect to an IoT gateway or other edge device, the sensor data they gather is either transmitted to the cloud for analysis or processed locally. Based on the received information, they act and it can expose a device as well as its data. Insufficient or no device authentication and authorization are common problems, as is poor or no encryption. Due to restricted energy supplies and low processing power, IoT security and privacy are complex, especially for resource‐constrained devices. In this article, IoT‐CS security problems and associated threats are discussed. The overarching goals were identifying assets and exploring possible threats, assaults, and vulnerabilities encountered by the IoT in the sectors like healthcare, transportation, utilities, safety, and environmental health that might be significantly improved with IoT‐CS deployment in smart cities. The predominant challenges in the deployment of the IoT related technologies had been studied in the aspects of cyber security and mitigation strategies had been discussed.
The Industrial Internet of Things (IIoT) has been growing for presentations in industry in recent years. Security for the IIoT has unavoidably become a problem in terms of creating safe applications. ...Due to continual needs for new functionality, such as foresight, the number of linked devices in the industrial environment increases. Certification of fewer signatories gives strong authentication solutions and prevents trustworthy third parties from being publicly certified among available encryption instruments. Hence this blockchain-based endpoint protection platform (BCEPP) has been proposed to validate the network policies and reduce overall latency in isolation or hold endpoints. A resolver supports the encoded model as an input; network functions can be optimized as an output in an infrastructure network. The configuration of the virtual network functions (VNFs) involved fulfills network characteristics. The output ensures that the final service is supplied at the least cost, including processing time and network latency. According to the findings of this comparison, our design is better suited to simplified trust management in IIoT devices. Thus, the experimental results show the adaptability and resilience of our suggested confidence model against behavioral changes in hostile settings in IIoT networks. The experimental results show that our proposed method, BCEPP, has the following, when compared to other methods: high computational cost of 95.3%, low latency ratio of 28.5%, increased data transmitting rate up to 94.1%, enhanced security rate of 98.6%, packet reception ratio of 96.1%, user satisfaction index of 94.5%, and probability ratio of 33.8%.
In the past years, the energy constraint problem is known as a design issue of Wireless Sensor Networks (WSNs) due to equipping the sensor nodes with limited power supplies. During the last few ...years, Wireless Rechargeable Sensor Networks (WRSNs) have gained researchers attention. In a WRSN, the sensor nodes are equipped with RF circuits, which enables them to receive energy from Wireless Mobile Chargers (WMC). However, most of the existing wireless charging algorithms consider the unlimited power budget for WMCs, which is the opposite of feasibility of a real network environment. Likewise, most of the previous works fail to take full advantage of WMC as it starts recharging the nodes when their energy level reaches a threshold, which leads to increasing the inactive time of WMC. Moreover, although previous works employed WMCs, the network lifetime is limited. However, optimal division of the energy of WMC among nodes can guarantee the perpetual network operation. Therefore, proposing an efficient method that jointly solves these challenges is required. In this paper, a new Fair Energy Division Scheme (FEDS) is presented, which undertakes the permanent network operation by optimizing the energy division at the beginning of each cycle. Simulation results exhibit that FEDS achieves perpetual network lifetime. In addition, the proposed scheme improves energy efficiency, (25%) compared to Uneven Cluster-based Mobile Charging (UCMC) and (75%) compared to Nearest-Job-Next Preemption NJNP; travelling time of WMC, (50%) compared to UCMC and (75%) compared to NJNP. In conclusion, the proposed protocol significantly improves network.
Fog Computing (FC) is promising to Internet architecture for the emerging of modern technological approaches such as Fifth Generation (5G) networks and the Internet of Things (IoT). These are the ...advanced technologies that enable Internet architecture to enhance the data dissemination services based on numerous sensors generating continuous sensory information. It is tough for the current Internet architecture to meet up with the growing demands of the users for such a massive amount of information. Therefore, it needs to adopt modern technologies for efficient data dissemination services across the Internet. Thus, the FC and 5G are updating the data transmission using new technological approaches that are intelligently processing data to provide enhanced communications. This study proposes necessary measures to boost the growth of FC to 5G network usage. It is done by taking an extensive review of how 5G operates as well as studying its taxonomy, the idea of IoT, reviewed projects on IoT applicability, comparison of computing technologies, and the importance of FC. Moreover, it elaborates dynamic issues of computing network technologies, and information is provided on how to remedy these for future recommendations in the field of research and computing network technologies. This paper heavily focuses on the applications of FC as an enabler to the 5G network by identifying the necessary services and network-oriented features that are needed to be used in the place for an improved future enterprise network technology.
The scope of the Internet of Things (IoT) applications varies from strategic applications, such as smart grids, smart transportation, smart security, and smart healthcare, to industrial applications ...such as smart manufacturing, smart logistics, smart banking, and smart insurance. In the advancement of the IoT, connected devices become smart and intelligent with the help of sensors and actuators. However, issues and challenges need to be addressed regarding the data reliability and protection for significant next-generation IoT applications like smart healthcare. For these next-generation applications, there is a requirement for far-reaching privacy and security in the IoT. Recently, blockchain systems have emerged as a key technology that changes the way we exchange data. This emerging technology has revealed encouraging implementation scenarios, such as secured digital currencies. As a technical advancement, the blockchain network has the high possibility of transforming various industries, and the next-generation healthcare IoT (HIoT) can be one of those applications. There have been several studies on the integration of blockchain networks and IoT. However, blockchain-as-a-utility (BaaU) for privacy and security in HIoT systems requires a systematic framework. This paper reviews blockchain networks and proposes BaaU as one of the enablers. The proposed BaaU-based framework for trustworthiness in the next-generation HIoT systems is divided into two scenarios. The first scenario suggests that a healthcare service provider integrates IoT sensors such as body sensors to receive and transmit information to a blockchain network on the IoT devices. The second proposed scenario recommends implementing smart contracts, such as Ethereum, to automate and control the trusted devices’ subscription in the HIoT services.
Millions of devices are becoming part of Internet of Things/5G. Securing these devices against all potential threats is a huge challenge. The 5G specification goals require rigid and robust security ...protocol against such threats. Quantum cryptography is a recently emerged term in which we test the robustness of security protocols against quantum computers. Therefore, in this article, we propose a security protocol called quantum key GRID for authentication and key agreement (QKG-AKA) scheme for the dynamic security association. This scheme is efficiently deployed in long term evolution architecture without any significant modifications in the underlying base system. The proposed QKG-AKA mechanism is analyzed for robustness and proven safe against quantum computers. The simulation results and performance analysis show drastic improvement regarding security and key management over existing schemes.
Phosphoaspartate is one of the major components of eukaryotes and prokaryotic two-component signaling pathways, and it communicates the signal from the sensor of histidine kinase, through the ...response regulator, to the DNA alongside transcription features and initiates the transcription of correct response genes. Thus, the prediction of phosphoaspartate sites is critical, and its experimental identification can be expensive, time-consuming, and tedious. For this purpose, we propose iPhosD-PseAAC, a new computational model for predicting phosphoaspartate sites in a particular protein sequence using Chou’s 5-steps rues: (1) Benchmark dataset. (2) The feature extraction techniques such as pseudo amino acid composition (PseAAC), statistical moments, and position relative features. (3) For the classification, artificial neural network AAN will be used. (4) In this step, 10-fold cross-validation and self-consistency testing will be used for validation. For self-consistency testing, 100% Acc is achieved, whereas, for 10-fold crossvalidation 95.14% Acc, 95.58% Sn, 94.70% Sp and 0.95 MCC are observed. (5). The final step is the development of a user-friendly web server for the ease of users. Thus, the iPhosD-PseAAC is the first and novel predictor for accurate and efficient identification of phosphoaspartate sites.
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