Hasil untuk "iot"

Rongxing Lu, Kevin Heung, Arash Habibi Lashkari et al.

Fog computing-enhanced Internet of Things (IoT) has recently received considerable attention, as the fog devices deployed at the network edge can not only provide low latency, location awareness but also improve real-time and quality of services in IoT application scenarios. Privacy-preserving data aggregation is one of typical fog computing applications in IoT, and many privacy-preserving data aggregation schemes have been proposed in the past years. However, most of them only support data aggregation for homogeneous IoT devices, and cannot aggregate hybrid IoT devices’ data into one in some real IoT applications. To address this challenge, in this paper, we present a lightweight privacy-preserving data aggregation scheme, called Lightweight Privacy-preserving Data Aggregation, for fog computing-enhanced IoT. The proposed LPDA is characterized by employing the homomorphic Paillier encryption, Chinese Remainder Theorem, and one-way hash chain techniques to not only aggregate hybrid IoT devices’ data into one, but also early filter injected false data at the network edge. Detailed security analysis shows LPDA is really secure and privacy-enhanced with differential privacy techniques. In addition, extensive performance evaluations are conducted, and the results indicate LPDA is really lightweight in fog computing-enhanced IoT.

Yair Meidan, Michael Bohadana, A. Shabtai et al.

Stefano Bresciani, Alberto Ferraris, M. del Giudice

In the last decade, the Internet of Things (IoT) has affected the approach of organizations to innovation and how they create and capture value in everyday business activities. This is compounded in the so-called Smart Cities, where the objective of the IoT is to exploit information and communication technologies (ICTs) to support added-value services for citizens, giving companies more opportunities to innovate through the use of the latest technologies. In this context, multinational enterprises (MNEs) are building alliances, starting several projects with public and private city stakeholders aimed at exploring new technologies for cities but also at exploiting new IoT-based devices and services in order to profit from them. This implies that companies need to manage and integrate different types of knowledge to efficiently and effectively support the simultaneous pressure of exploration and exploitation, at a project portfolio level. Using structural equations modeling with data collected from 43 IoT smart city project alliances in Italy, this paper tests and finds evidence that MNEs need to develop knowledge management (KM) capabilities combined with ICT capabilities if they want to obtain greater ambidexterity performance at the project portfolio level. More specifically, we highlight that KM capabilities enhance alliance ambidexterity indirectly through firms' ICT capabilities, suggesting that MNE managers should design KM tools and develop new ICT skills. Implications for academics, managers and future lines of research are proposed.

S. Challa, Mohammad Wazid, A. Das et al.

Internet of Things (IoT) is a network of all devices that can be accessed through the Internet. These devices can be remotely accessed and controlled using existing network infrastructure, thus allowing a direct integration of computing systems with the physical world. This also reduces human involvement along with improving accuracy and efficiency, resulting in economic benefit. The devices in IoT facilitate the day-to-day life of people. However, the IoT has an enormous threat to security and privacy due to its heterogeneous and dynamic nature. Authentication is one of the most challenging security requirements in the IoT environment, where a user (external party) can directly access information from the devices, provided the mutual authentication between user and devices happens. In this paper, we present a new signature-based authenticated key establishment scheme for the IoT environment. The proposed scheme is tested for security with the help of the widely used Burrows-Abadi–Needham logic, informal security analysis, and also the formal security verification using the broadly accepted automated validation of Internet security protocols and applications tool. The proposed scheme is also implemented using the widely accepted NS2 simulator, and the simulation results demonstrate the practicability of the scheme. Finally, the proposed scheme provides more functionality features, and its computational and communication costs are also comparable with other existing approaches.

S. Prathibha, Anupama Hongal, M. Jyothi

P. Sharma, Saurabh Singh, Y. Jeong et al.

Jyoti Deogirikar, A. Vidhate

O. Skarlat, Matteo Nardelli, Stefan Schulte et al.

The Internet of Things (IoT) leads to an ever-growing presence of ubiquitous networked computing devices in public, business, and private spaces. These devices do not simply act as sensors, but feature computational, storage, and networking resources. Being located at the edge of the network, these resources can be exploited to execute IoT applications in a distributed manner. This concept is known as fog computing. While the theoretical foundations of fog computing are already established, there is a lack of resource provisioning approaches to enable the exploitation of fog-based computational resources. To resolve this shortcoming, we present a conceptual fog computing framework. Then, we model the service placement problem for IoT applications over fog resources as an optimization problem, which explicitly considers the heterogeneity of applications and resources in terms of Quality of Service attributes. Finally, we propose a genetic algorithm as a problem resolution heuristic and show, through experiments, that the service execution can achieve a reduction of network communication delays when the genetic algorithm is used, and a better utilization of fog resources when the exact optimization method is applied.

Tian Wang, Guangxue Zhang, Anfeng Liu et al.

The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT’s capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.

Ali Eghmazi, Mohammadhossein Ataei, René Jr Landry et al.

The Internet of Things (IoT) is a technology that can connect billions of devices or “things” to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart cities, smart houses, connected appliances, shipping, monitoring, smart supply chain management, and smart grids. As the number of devices all over the world is increasing (in all aspects of daily life), huge amounts of data are being produced as a result. New issues are therefore arising from the use and development of current technologies, regarding new applications, regulation, cloud computing, security, and privacy. The blockchain has shown promise in terms of securing and preserving the privacy of users and data, in a decentralized manner. In particular, Hyperledger Fabric v2.x is a new generation of blockchain that is open source and offers versatility, modularity, and performance. In this paper, a blockchain as a service (BaaS) application based on Hyperledger Fabric is presented to address the security and privacy challenges associated with the IoT. A new architecture is introduced to enable this integration, and is developed and deployed, and its performance is analyzed in real-world scenarios. We also propose a new data structure with encryption based on public and private keys for enhanced security and privacy.

Mikail Mohammed Salim, S. Rathore, J. Park

Mohammed Talal, A. A. Zaidan, B. Zaidan et al.

Karim Baker, M Aruna, Deepika K. et al.

In recent times, Internet of Things (IoT) ecosystem is rapidly expanding, with a flow in various devices being integrated to allow continuous and efficient communication. Most IoT devices are resource-constrained, and without clearly defined security standards, their communications remain exposed to potential risks. As a result, quickly identifying threats within IoT networks is critical, making Intrusion Detection Systems (IDS) an essential component of modern cybersecurity strategies. The unpredictable behavior of IoT traffic demands dynamic and context-sensitive rule configurations. Software Defined Networks (SDN’s) is programmable architecture enables real-time threat justification across heterogeneous IoT environments. The proposed IntruDet-LSTM which is Intrusion Detection with Long Short-Term Memory method introduces a hybrid system for intrusion detection and dynamic rule-based configuration, combining a signature-based SNORT method with a data-driven ensemble model built on LSTM. Fault tolerance is achieved through a dual-layer design, where the intrusion detection and rule configuration models are dissociated, enabling uninterrupted performance even when one layer is compromised. IntruDet-LSTM method effectively reduces false alarms, allowing true IoT traffic to flow continuous and still delivering high detection accuracy. The proposed IntruDet-LSTM achieves accuracy of 99.8%, which is better than existing Deep Integrated Stacking for the IoT (DIS-IoT).

Kanar Alaa Al-Sammak, Sama Hussein Al-Gburi, Ion Marghescu et al.

Real-time monitoring, data-driven decisions, and energy consumption optimization have reached a new level with IoT advancement. However, a significant challenge faced by intelligent nodes and IoT applications resides in their energy requirements in the long term, especially in the case of gas or water smart meters. This article proposes an algorithm for smart meters’ energy consumption optimization based on IoT, LoRaWAN, and NB-IoT using microcontroller-based development boards, PZEM004T energy meters, Dragino LoRaWAN shield, or BG96 NB-IoT modules. The algorithm adjusts the transmission time based on the change in data in real-time. According to the experimental results, the energy consumption and the number of packets transmitted significantly decreased using LoRaWAN or NB-IoT, saving up to 76.11% and 86.81% of the transmitted packets, respectively. Additionally, the outcome highlights a notable percentage reduction in the energy consumption spike frequency, with NB-IoT achieving an 87.3% reduction and LoRaWAN slightly higher at 88.5%. This study shows that adaptive algorithms are very effective in extending the lifetime of IoT nodes, thereby providing a solid baseline for scalable, lightweight, energy-monitoring IoT applications. The results could help shape the development of smart energy metering systems and sustainable IoT.

Дмитро Ніщеменко

Точне короткострокове прогнозування навантаження є ключовим завданням для ефективного управління енергоресурсами в системах розумного будинку. Гібридні моделі, що поєднують архітектури глибокого навчання (DL) та ансамблі дерев рішень, є провідним напрямом сучасних досліджень. Аналіз останніх публікацій підтверджує, що порівняння мереж з довгою короткостроковою пам'яттю (LSTM) та темпоральних згорткових мереж (TCN) є популярною темою, а гібридизація з LightGBM та використання стратегій корекції помилок («прогнозування залишків») є доведеними практиками для підвищення точності. Однак, огляд літератури виявляє декілька невирішених частин загальної проблеми: 1) відсутність систематичного аналізу компромісу між точністю прогнозу та обчислювальною вартістю (час навчання, вимоги до ресурсів), що є критичним для імплементації на пристроях Інтернету речей (IoT); 2) недостатня дослідженість впливу інженерії ознак, зокрема їх відбору, на обчислювальну ефективність гібридних моделей; 3) тенденція до фокусування на метриках точності без надання практичних методологій вибору оптимальної моделі залежно від конкретного завдання. Ця робота спрямована на заповнення вказаних прогалин. Реалізовано багатоетапний експериментальний аналіз. Для обраних моделей тестувалися дві стратегії гібридизації: "коригування піків" та "прогнозування залишків. Розроблено методику оптимізації часу навчання шляхом відбору найважливіших ознак для моделі-коректора. Для забезпечення статистичної значущості результатів застосовувалася перехресна валідація для часових рядів. Дослідження підтвердило, що гібридні моделі значно перевершують базові, а стратегія "прогнозування залишків" є найбільш ефективною. Виявлено дві високопродуктивні спеціалізовані конфігурації. Гібрид LSTM + LightGBM продемонстрував найвищу загальну точність (MAPE 13.36%). Водночас гібрид TCN + LightGBM виявився ефективнішим у прогнозуванні критичних пікових навантажень (Peak Magnitude MAPE 16.71%) та на 21% швидшим у навчанні. Ключовим результатом є запропонована методика оптимізації моделі TCN + LightGBM шляхом відбору ознак, що дозволило прискорити навчання в 5.4 рази при збереженні високої точності прогнозування піків (Peak MAPE 16.77%). Робота заповнює ідентифіковані прогалини в літературі, надаючи не лише кількісні результати, а й практичну методологію для обґрунтованого вибору архітектури прогнозування залежно від пріоритетних завдань системи розумного будинку: максимальна загальна точність, пріоритетне управління піковими навантаженнями або збалансована продуктивність для пристроїв з обмеженими ресурсами. Запропонований оптимізований гібридний підхід є перспективним для практичного впровадження в адаптивні системи управління енергією завдяки доведеному балансу високої точності та низьких обчислювальних витрат.

Mohammad Sepehri, Adel Farzaneh

Objective: main concern is lack of codification of indigenous intelligent command and control model, main goal is to develop indigenous intelligent command and control model using military Internet of Things, other goals: to count dimensions and components, determine relationships between dimensions and components of model design, and to count achievements, consequences, functions and requirements of model design. Method: type of applied-developmental research, descriptive-case research method, mixed research approach and method of data collection, field and library, with library study tools are books, articles, documents, interviews, questionnaires, and time domain of years 1402-1403 for five years and spatial domain of country's armed forces. Statistical population of 70 experts and experts, structural equation modeling is used to analyze and investigate relationship and correlation between factors. Results:By testing PLS model in SRMR test, since it is smaller than 0.08, overall model of PLS has a good fit and is therefore consistent with desired model in society.Conclusion:dimensions of model design are intelligence, information management, sustainability, interoperability, integration, and network-oriented. achievements and consequences of designing model are improvement (intelligence of c4isr, and decision-making, comprehensive defense readiness, deterrence), increasing military authority and capability, and increasing indigenous cyber power. Functions of model design are intelligence-making (action-oriented and strategic command systems, control, monitoring and evaluation systems, communication systems, computer and cyberspace systems, information collection systems, surveillance and identification systems) and online situational awareness on battlefield.requirements of designing model are battlefield intelligence, localization of IoT standards, IoT software security, and funding and credit, training and skill development.

Jesús Antonio Mayorquín Robles, Gabriel Antonio López Valencia, José Jesús Rodríguez Senday et al.

Cuando se trabaja en el desarrollo de diferentes interfaces que funcionan como una sola, es complicado, en ocasiones es poco entendible, en la mayoría de las veces eso pasa debido a que el o los desarrolladores no siguen un proceso metodológico adecuado. En el desarrollo de servicios WEB, APP móviles e inclusive en los sistemas embebidos es posible que se basen en técnicas como MVC o UML, los cuales le dan al desarrollo del proyecto una base científica que puede ser entendida por cualquier persona que realice este tipo de proyectos. El presente trabajo muestra el desarrollo de una aplicación basada en IoT, es decir, un servicio WEB, una APP móvil y un sistema embebido, raspberry pi, que trabajan de manera conjunta y basados en técnicas estructuradas de desarrollo MVC con la finalidad de mostrar que es posible que trabajos con cierto grado de complejidad puedan mostrarse más sencillos. El sistema fue probado en un servicio de préstamo de bicicletas, generando una base de datos de usuarios y haciendo pruebas de manera individual con cada uno.

Pei Siang Chia, Noor Hisham Kamis, Siti Fatimah Abdul Razak et al.

IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) are specifically designed for applications that require lower data rates and reduced power consumption in wireless internet connectivity. In the context of 6LoWPAN, Internet of Things (IoT) devices with limited resources can now seamlessly connect to the network using IPv6. This study focuses on examining the performance and power consumption of routing protocols in the context of 6LoWPAN, drawing insights from prior research and utilizing simulation techniques. The simulation involves the application of routing protocols, namely Routing Protocol for Low-power and Lossy (RPL) Networks, Ad hoc On-demand Distance Vector (AODV), Lightweight On-demand Ad hoc Distance-vector Next Generation (LOADng), implemented through the Cooja simulator. The simulation also runs in different network topologies to gain an insight into the performance of the protocols in the specific topology including random, linear, and eclipse topology. The raw data gathered from the tools including Powertrace and Collect-View were then analyzed with Python code to transfer into useful information and visualize the graph. The results demonstrate that the power consumption, specifically CPU power, Listen Power, and Total Consumption Power, will increase with the incremental of motes. The result also shows that RPL is the most power-efficient protocol among the scenarios compared to LOADng and AODV. The result is helpful because it brings insights into the performance, specifically power consumption in the 6LoWPAN network. This result is valuable to further implement these protocols in the testbed as well as provide an idea of the algorithmic enhancements.

Rodrigo Aldana-López, Omar Longoria-Gandara, Jose Valencia-Velasco et al.

There is increasing interest in improving the reliability of short-range wireless links in dense IoT deployments, where BLE is widely used due to its low power consumption and robust GFSK modulation. For this purpose, this work presents a novel Orthogonal Space-Time (OST) scheme for transmission and detection of BLE signals while preserving the BLE GFSK waveform and modulation constraints. The proposed signal processing system integrates advanced OST coding techniques with nonlinear GFSK modulation to achieve high-quality communication while maintaining phase continuity. This implies that the standard BLE GFSK modulator and demodulator blocks can be reused, with additional processing introduced only in the multi-antenna encoder and combiner. A detailed theoretical analysis demonstrates the feasibility of employing the Rayleigh fading channel model in BLE communications and establishes the BER performance bounds for various MIMO configurations. Simulations confirm the advantages of the proposed OST-GFSK signal processing scheme, maintaining a consistent performance when compared with OST linear modulation approaches under Rayleigh fading channels. As a result, the proposed IoT-enabling technology integrates the advantages of widely used OST linear modulation with nonlinear GFSK modulation required for BLE.

S. Hameed, F. Khan, B. Hameed

Internet of things (IoT) is realized by the idea of free flow of information amongst various low-power embedded devices that use the Internet to communicate with one another. It is predicted that the IoT will be widely deployed and will find applicability in various domains of life. Demands of IoT have lately attracted huge attention, and organizations are excited about the business value of the data that will be generated by deploying such networks. On the contrary, IoT has various security and privacy concerns for the end users that limit its proliferation. In this paper, we have identified, categorized, and discussed various security challenges and state-of-the-art efforts to resolve these challenges.