IoT-based Secure Data Transmission Prediction using Deep Learning Model in Cloud Computing

The security of Internet of Things (IoT) networks has become highly significant due to the growing number of IoT devices and the rise in data transfer across cloud networks. Here, we propose Generative Adversarial Networks (GANs) method for predicting secure data transmission in IoT-based systems using cloud computing. We evaluated our model’s attainment on the UNSW-NB15 dataset and contrasted it with other machine-learning (ML) methods, comprising decision trees (DT), random forests, and support vector machines (SVM). The outcomes demonstrate that our suggested GANs model performed better than expected in terms of precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC). The GANs model generates a 98.07% accuracy rate for the testing dataset with a precision score of 98.45%, a recall score of 98.19%, an F1 score of 98.32%, and an AUC-ROC value of 0.998. These outcomes show how well our suggested GANs model predicts secure data transmission in cloud-based IoT-based systems, which is a crucial step in guaranteeing the confidentiality of IoT networks

Internet of things: Conceptual network structure, main challenges and future directions

Internet of Things (IoT) is a key technology trend that supports our digitalized society in applications such as smart countries and smart cities. In this study, we investigate the existing strategic themes, thematic evolution structure, key challenges, and potential research opportunities associated with the IoT. For this study, we conduct a Bibliometric Performance and Network Analysis (BPNA), supplemented by an exhaustive Systematic Literature Review (SLR). Specifically, in BPNA, the software SciMAT is used to analyze 14,385 documents and 30,381 keywords in the Web of Science (WoS) database, which was released between 2002 and 2019. The results reveal that 31 clusters are classified according to their importance and development, and the conceptual structures of key clusters are presented, along with their performance analysis and the relationship with other subthemes. The thematic evolution structure describes the important cluster(s) over time. For the SLR, 23 documents are analyzed. The SLR reveals key challenges and limitations associated with the IoT. We expect the results will form the basis of future research and guide decision-making in the IoT and other supporting industries.Coordenaç~ao de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001 and the Spanish Ministry of Science and Innovation under grants PID2019-105381 GA-100 (iScience)Consejo Nacional de Ciencia y Tecnología (CONACYT) and Direcci on General de Relaciones Exteriores (DGRI

Authentication Protocols for Internet of Things: A Comprehensive Survey

In this paper, a comprehensive survey of authentication protocols for Internet of Things (IoT) is presented. Specifically more than forty authentication protocols developed for or applied in the context of the IoT are selected and examined in detail. These protocols are categorized based on the target environment: (1) Machine to Machine Communications (M2M), (2) Internet of Vehicles (IoV), (3) Internet of Energy (IoE), and (4) Internet of Sensors (IoS). Threat models, countermeasures, and formal security verification techniques used in authentication protocols for the IoT are presented. In addition a taxonomy and comparison of authentication protocols that are developed for the IoT in terms of network model, specific security goals, main processes, computation complexity, and communication overhead are provided. Based on the current survey, open issues are identified and future research directions are proposed

A survey of IoT security based on a layered architecture of sensing and data analysis

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond

Integrated sensor and management system for urban waste water networks and prevention of critical situations

[EN] This work describes the design and implementation of improvements to the monitoring system of an urban waste water network, resulting in more efficient management of the system. To achieve this objective, the latest communications technology has been incorporated into heterogeneous networks and sensor systems. This technology includes mobile systems, which take measurements and transmit images in real time, an intelligent platform for processing and management of variables, and the implementation of wireless sensor networks (WSNs) designed with specific protocols and tools that allow the rapid deployment of the network and allow measurements to be taken in emergency situations. The sensors in this type of installation are extremely important for the management of the system as they allow us to collect information and make decisions with sufficient time to deal effectively with critical situations such as flooding or overloading of the waste water system, or environmental problems such as dumping of possible pollutants, as well as to make the best use of the water cycle. The solution presented here automates large portions of the processes, minimizing the possibility of human error, and increasing the frequency and accuracy of the measurements taken, ensuring a robust communication system covering all the elements involved to provide ubiquity of information, and finally gives an application layer to manage the system and receive alerts. © 2011 Elsevier Ltd.This work was supported by the MCyT (Spanish Ministry of Science and Technology) under the projects PET2007-0316 and TIN2010-21378-C02-02, which are partially funded by ERDF (European Regional Development Fund).Sempere Paya, VM.; Santonja Climent, S. (2012). Integrated sensor and management system for urban waste water networks and prevention of critical situations. Computers, Environment and Urban Systems. 36(1):65-80. https://doi.org/10.1016/j.compenvurbsys.2011.07.001S658036

A survey of secure middleware for the Internet of Things

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area

Protection of Records and Data Authentication based on Secret Shares and Watermarking

The rapid growth in communication technology facilitates the health industry in many aspects from transmission of sensor’s data to real-time diagnosis using cloud-based frameworks. However, the secure transmission of data and its authenticity become a challenging task, especially, for health-related applications. The medical information must be accessible to only the relevant healthcare staff to avoid any unfortunate circumstances for the patient as well as for the healthcare providers. Therefore, a method to protect the identity of a patient and authentication of transmitted data is proposed in this study. The proposed method provides dual protection. First, it encrypts the identity using Shamir’s secret sharing scheme without the increase in dimension of the original identity. Second, the identity is watermarked using zero-watermarking to avoid any distortion into the host signal. The experimental results show that the proposed method encrypts, embeds and extracts identities reliably. Moreover, in case of malicious attack, the method distorts the embedded identity which provides a clear indication of fabrication. An automatic disorder detection system using Mel-frequency cepstral coefficients and Gaussian mixture model is also implemented which concludes that malicious attacks greatly impact on the accurate diagnosis of disorders

Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study

This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machine’s ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives

A user-centric privacy-preserving authentication protocol for IoT-AmI environments

Ambient Intelligence (AmI) in Internet of Things (IoT) has empowered healthcare professionals to monitor, diagnose, and treat patients remotely. Besides, the AmI-IoT has improved patient engagement and gratification as doctors’ interactions have become more comfortable and efficient. However, the benefits of the AmI-IoT-based healthcare applications are not availed entirely due to the adversarial threats. IoT networks are prone to cyber attacks due to vulnerable wireless mediums and the absentia of lightweight and robust security protocols. This paper introduces computationally-inexpensive privacy-assuring authentication protocol for AmI-IoT healthcare applications. The use of blockchain & fog computing in the protocol guarantees unforgeability, non-repudiation, transparency, low latency, and efficient bandwidth utilization. The protocol uses physically unclonable functions (PUF), biometrics, and Ethereum powered smart contracts to prevent replay, impersonation, and cloning attacks. Results prove the resource efficiency of the protocol as the smart contract incurs very minimal gas and transaction fees. The Scyther results validate the robustness of the proposed protocol against cyber-attacks. The protocol applies lightweight cryptography primitives (Hash, PUF) instead of conventional public-key cryptography and scalar multiplications. Consequently, the proposed protocol is better than centralized infrastructure-based authentication approaches