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The Internet of Things (IoT) has recently been implemented in various applications. An IoT network is a group of Internet-connected computing devices embedded in everyday objects. Usually, those devices can interact with each other via the Internet by exchanging data. Because of privacy and security requirements, users of IoT-connected objects need measures to secure corresponding data during storage and transmission. This work presents an architecture that integrates IoT devices, blockchain technology, and embedded homomorphic encryption to ensure high computation speed and security levels in IoT systems. The ultralight linear encryption technique enhances computation speed, making it possible to obtain homomorphic addition over the encrypted data. Using this technique, each administrator gains specific access to the encrypted data. Security, stability, traceability, and anonymity are provided through blockchain technology, which is used to store data. The proposed architecture is demonstrated via a use case from the healthcare sector. The experimental analysis shows our technique's effectiveness in energy consumption reduction and privacy preservation with minimal computation and communication costs. By using five fields per record, name, ID, age, gender, and blood glucose level, we achieved an encryption time equals 0,19 ms and decryption time equals 0,98 ms vs. 15,7 and 1,6 respectively in the best comparison technique. In communication cost, we achieved 1KB vs. 5KB. [ABSTRACT FROM AUTHOR]

In the rapidly advancing landscape of digital technologies, clustering plays a critical role in the domains of artificial intelligence and big data. Clustering is essential for extracting meaningful insights and patterns from large, intricate datasets. Despite the efficacy of traditional clustering techniques in handling diverse data types and sizes, they encounter challenges posed by the increasing volume and dimensionality of data, as well as the complex structures inherent in high-dimensional spaces. This research recognizes the constraints of conventional clustering methods, including sensitivity to initial centroids, dependence on prior knowledge of cluster counts, and scalability issues, particularly in large datasets and Internet of Things implementations. In response to these challenges, we propose a K-level clustering algorithm inspired by the collective behavior of fish locomotion. K-level introduces a novel clustering approach based on greedy merging driven by distances in stages. This iterative process efficiently establishes hierarchical structures without the need for exhaustive computations. K-level gives users enhanced control over computational complexity, enabling them to specify the number of clusters merged simultaneously. This flexibility ensures accurate and efficient hierarchical clustering across diverse data types, offering a scalable solution for processing extensive datasets within a reasonable timeframe. The internal validation metrics, including the Silhouette Score, Davies–Bouldin Index, and Calinski–Harabasz Index, are utilized to evaluate the K-level algorithm across various types of datasets. Additionally, comparisons are made with rivals in the literature, including UPGMA, CLINK, UPGMC, SLINK, and K-means. The experiments and analyses show that the proposed algorithm overcomes many of the limitations of existing clustering methods, presenting scalable and adaptable clustering in the dynamic landscape of evolving data challenges. [ABSTRACT FROM AUTHOR]

Artificial intelligence has been involved in several domains. Despite the advantages of using artificial intelligence techniques, some crucial limitations prevent them from being implemented in specific domains and locations. The accuracy, poor quality of gathered data, and processing time are considered major concerns in implementing machine learning techniques, certainly in low-end smart devices. This paper aims to introduce a novel pre-treatment technique dedicated to image text detection that uses the images' pixel divergence and similarity to reduce the image size. Mitigating the image size while keeping its features improves the model training time with an acceptable accuracy rate. The mitigation is reached by gathering similar image pixels in one pixel based on calculated values of the standard deviation σ, where we consider that two pixels are similar if they have approximately the same σ values. The work proposes a new pipeline approach that reduces the size of the image in the input and intermediate layers of a deep learning model based on merged pixels using standard deviation values instead of the whole image. The experimental results prove that this technique significantly improves the performance of existing text detection methods, particularly in challenging scenarios such as using low-end IoT devices that offer low contrast or noisy backgrounds. Compared with other techniques, the proposed technique can potentially be exploited for text detection in IoT-gathered multimedia data with reasonable accuracy in a short computation time. Evaluation of the MSRA-TD500 dataset demonstrates the remarkable performance of our approach, Standard Deviation Network (σNet), with precision and recall values of 93.8% and 85.6%, respectively, that outperform recent research results. [ABSTRACT FROM AUTHOR]

Internet cloud services come at a price, especially when they provide top-tier security measures. The cost incurred by cloud utilization is directly proportional to the storage requirements. Companies are always looking to increase profits and reduce costs while preserving the security of their data by encrypting them. One of the offered solutions is to find an efficient encryption method that can store data in a much smaller space than traditional encryption techniques. This article introduces a novel encryption approach centered on consolidating information into a single ciphertext by implementing Multi-Key Embedded Encryption (MKEE). The effectiveness of MKEE scales in tandem with the volume of information encapsulated within the ciphertext. MKEE substantially reduced the size of the ciphertext, achieving an 88% decrease when incorporating ten plaintext values. To further reduce the size of the ciphertext in our proposal, a Modular Multiplicative Inverse method (MMI) is introduced. MMI experiments were conducted, demonstrating that we achieved a commendable 50% reduction in the ciphertext size. To validate the practicality of the proposed method, a case study was conducted on a diabetes dataset. By integrating MKEE and MMI, this study showed a data storage reduction of 94%. [ABSTRACT FROM AUTHOR]

A corporation or company's production velocity and efficiency are essential. It is necessary to use robotic automation to create a successful organization in a competitive business environment. Recent investments have been made in robots across a wider range of manufacturing sectors. In this era of industry, recent advances in robotics technology are dramatically transforming the business and entrepreneurial landscape. Today, robotics is already well established in many areas of our professional, personal, and even daily lives. This technology can develop and modernize commercial processes, innovative ideas, services, and products and solve complex tasks by producing new results for the massive growth of entrepreneurial activities. This study aims to outline the significance of the impact of investment in robotic automation on business performance and employment at the enterprise level and its further perspectives. Following the review of the most important international articles on exploiting this technology, we conducted a brief study on an Algerian factory to learn about the level of use of robotics technology and its future prospects. [ABSTRACT FROM AUTHOR]

Multi-agent systems (MASs) have gained a lot of interest recently, due to their ability to solve problems that are difficult or even impossible for an individual agent. However, an important procedure that needs attention in designing multi-agent systems, and consequently applications that utilize MASs, is achieving a fair agreement between the involved agents. Researchers try to prevent agreement manipulation by utilizing decentralized control and strategic voting. Moreover, emphasis is given to local decision making and perception of events occurring locally. This manuscript presents a novel secure decision-support algorithm in a multi-agent system that aims to ensure the system's robustness and credibility. The proposed consensus-based model can be applied to production planning and control, supply chain management, and product design and development. The algorithm considers an open system; i.e., the number of agents present can be variable in each procedure. While a group of agents can make different decisions during a task, the algorithm chooses one of these decisions in a way that is logical, safe, efficient, fast, and is not influenced by factors that might affect production. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technologies, particularly the Internet of Medical Things (IoMT), with wireless sensor networks (WSNs) has revolutionized the healthcare industry. However, despite the undeniable benefits of WSNs, their limited communication capabilities and network congestion have emerged as critical challenges in the context of healthcare applications. This research addresses these challenges through a dynamic and on-demand route-finding protocol called P2P-IoMT, based on LOADng for point-to-point routing in IoMT. To reduce congestion, dynamic composite routing metrics allow nodes to select the optimal parent based on the application requirements during the routing discovery phase. Nodes running the proposed routing protocol use the multi-criteria decision-making Skyline technique for parent selection. Experimental evaluation results show that P2P-IoMT protocol outperforms its best rivals in the literature in terms of residual network energy and packet delivery ratio. The network lifetime is extended by 4% while achieving a comparable packet delivery ratio and communication delay compared to LRRE. These performances are offered on top of the dynamic path selection and configurable route metrics capabilities of P2P-IoMT. [ABSTRACT FROM AUTHOR]

In today's hyperconnected world, the Internet of Things and Cloud Computing complement each other in several areas. Cloud Computing provides IoT systems with an efficient and flexible environment that supports application requirements such as real-time control/monitoring, scalability, fault tolerance, and numerous security services. Hardware and software limitations of IoT devices can be mitigated using the massive on-demand cloud resources. However, IoT cloud-based solutions pose some security and privacy concerns, specifically when an untrusted cloud is used. This calls for strong encryption schemes that allow operations on data in an encrypted format without compromising the encryption. This paper presents an asymmetric multi-key and partially homomorphic encryption scheme. The scheme provides the addition operation by encrypting each decimal digit of the given integer number separately using a special key. In addition, data integrity processes are performed when an untrusted third party performs homomorphic operations on encrypted data. The proposed work considers the most widely known issues like the encrypted data size, slow operations at the hardware level, and high computing costs at the provider level. The size of generated ciphertext is almost equal to the size of the plaintext, and order-preserving is ensured using an asymmetrical encryption version. [ABSTRACT FROM AUTHOR]

Digital signature schemes are practical mechanisms for achieving message integrity, authenticity, and non-repudiation. Several asymmetric encryption techniques have been proposed in the literature, each with its proper limitations. RSA and El Gamal prove their robustness, but are unsuitable in several domains due to their computational complexity. Other asymmetric encryption schemes have been proposed to provide a cloud homomorphic encryption service, where the researchers focused only on how to ensure the homomorphic property. This paper proposes a new digital signature scheme dedicated to a family of encryption techniques. The proposal consists of two parts: the first focused on the secret key, and the second focused on the public key. Signature validity checking was performed by multiplying these two parts to reform again the sender's public key, then comparing the result with the decrypted message. The validation of the decrypted message guarantees data integrity, where the signer public key is used to ensure authenticity. The proposed scheme takes a shorter execution time for the entire signature operation, including signing and verification, compared to other modern techniques. The analysis showed its robustness against private key recovery and forgery attacks. The implementation results of the proposed scheme showed promising performance in terms of complexity and robustness. The results confirmed that the proposed scheme is efficient and effective for signature generation and verification. [ABSTRACT FROM AUTHOR]

Unconditional security means that knowledge of an encrypted text does not provide any information about the corresponding plaintext: or more. regardless of the number of ciphertexts available to an attacker. no amount of cryptanalysis can break the cipher. Until now. only the One-Time Pad (OTP) method meets this condition with well-defined assumptions. The design of a Homomorphic Encryption scheme that allows operations over the encrypted data is required in current applications to reach the highest possible level of privacy. However. existing symmetric solutions that use OTP have a key management problem: they are not linear encryption. which means that they have high computational complexity. and some of them do not meet all homomorphic properties. This article simulates the 0TP taking into consideration these issues and achieving the maximum resistance to cryptanalysis, even when the attacker has great computing power. The first major advantage of the proposed OTP-based method is that it only uses a single pre-shared key, The key is composed of two sections, a fixed number of bits followed by random bits, the size of each section is dependent on the robustness of the system. Analysis of the proposed technique shows that it provides perfect privacy by using a different key for each message to be encrypted. [ABSTRACT FROM AUTHOR]

This article is to propose a consensus algorithm, called Proof of Chance (PoCh), which is designed for the industrial Internet of Things (IIoT). The PoCh protocol is designed to be scalable and extensible, with a controllable conformance delay and low hardware and computation requirements. To reach a consensus, PoCh uses chance rather than computing power: “if condition $_{1}$ , I am a candidate; if condition $_{2}$ , I am the miner.” During every consensus iteration, the condition $_{1}$ is updated, and a single miner is chosen using condition $_{2}$. Those conditions are randomized without the node generating any value and without assigning any weight to such value. The fault tolerance of PoCh is $5f/3 + 1$ , meaning that PoCh can successfully achieve consensus as long as more than 40% of nodes are functioning properly, compared to 50% in the Proof of Stake (PoS) protocol. [ABSTRACT FROM AUTHOR]

Nowadays, cloud computing offers a digital infrastructure for smart city development. Cognitive cities are steadily automating daily urban processes. The ever expanding objective‐driven communities gather and share sensitive data that must be stored securely. Cloud computing offers a suitable platform that allows cognitive smart cities to access and re‐access data to learn from their past to adapt its current behaviour. However, the cloud is an untrusted entity that may expose data when decrypted for processing by systems. In this paper, we treat the issue of encrypted data processing. Often, the data is encrypted prior to transferring it to the cloud, where the cloud must have the data in clear to be able to make calculations which raises security and privacy threats if the cloud is considered untrusted. The scenario of asking users to make the calculations after decrypting the received cloud data and encrypting the obtained results before sending them back to the cloud is not a practical solution in distributed multi‐tenant architectures. Homomorphic encryption allows offers a solution for processing encrypted data. Many existing homomorphic encryption schemes suffer from limitations that hinder their usability. This paper presents an efficient fully homomorphic encryption scheme using twin key encryption and magic number fragmentation. The details of the scheme are presented along with cryptanalytic attacks to assess its effectiveness. The proposed scheme exhibits strong resilience against brute‐force attacks compared to its rivals from the literature. Finally, we illustrate the applicability of the proposed scheme using a cognitive smart city application. [ABSTRACT FROM AUTHOR]

Complex systems are often designed in a decentralized and open way so that they can operate on heterogeneous entities that communicate with each other. Numerous studies consider the process of components simulation in a complex system as a proven approach to realistically predict the behavior of a complex system or to effectively manage its complexity. The simulation of different complex system components can be coupled via co-simulation to reproduce the behavior emerging from their interaction. On the other hand, multi-agent simulations have been largely implemented in complex system modeling and simulation. Each multi-agent simulator's role is to solve one of the VRP objectives. These simulators interact within a co-simulation platform called MECSYCO, to ensure the integration of the various proposed VRP models. This paper presents the Vehicle Routing Problem (VRP) simulation results in several aspects, where the main goal is to satisfy several client demands. The experiments show the performance of the proposed VRP multi-model and carry out its improvement in terms of computational complexity. [ABSTRACT FROM AUTHOR]

Several trusted tasks use consensus algorithms to solve agreement challenges. Usually, consensus agreements are used to ensure data integrity and reliability in untrusted environments. In many distributed networking fields, the Proof of Work (PoW) consensus algorithm is commonly used. However, the standard PoW mechanism has two main limitations, where the first is the high power consumption and the second is the 51% attack vulnerability. In this paper, we look to improve the PoW consensus protocol by introducing several proof rounds. Any given consensus node should resolve the game of the current round R o u n d i before participating in the next round R o u n d i + 1 . Any node that resolves the game of R o u n d i can only pass to the next round if a predetermined number of solutions has been found by other nodes. The obtained evaluation results of this technique show significant improvements in terms of energy consumption and robustness against the 51% and Sybil attacks. By fixing the number of processes, we obtained an energy gain rate of 15.63% with five rounds and a gain rate of 19.91% with ten rounds. [ABSTRACT FROM AUTHOR]

The PMUs are high-precision devices used to monitor the operation of the power system. These devices provide synchronized measurement of AC voltage and current phasors at the same time by the global positioning system (GPS). Due to the high costs of these devices, they cannot be placed on all network buses. Therefore this paper aims to find the lowest possible number of PMUs to ensure a complete observability of the power system and improve the measurement redundancy, During normal cases (with and without ZIBs), Then in conditions of failure of single PMUs and outage of single line, by using gravitational search algorithm (GSA). The suggested GSA has been applied to the IEEE 14-bus, 24-bus, 30-bus, 57-bus, New England 39-bus, and Algerian 114-bus. To check the effectiveness and robustness of this technique, a comparison of results is made with some of the methods recently reported. Comparison results show that the proposed technique has succeeded in significantly reducing the number of PMUs and improving the redundancy of measurements. [ABSTRACT FROM AUTHOR]