Search Results (6,017)

This study proposes a comprehensive framework for integrating data-driven approaches into policy analysis and intervention strategies. The methodology is structured around five critical components: data collection, historical analysis, policy impact assessment, predictive modeling, and intervention design. Leveraging data-driven approaches capabilities, the line of work enables advanced multilingual data processing, advanced statistics in population trends, evaluation of policy outcomes, and the development of evidence-based interventions. A key focus is on the theoretical integration of social order mechanisms, including communication modes as institutional structures, token optimization as an efficiency mechanism, and institutional memory adaptation. A mixed methods approach was used that included sophisticated visualization techniques and use cases in the hospitality sector, in global food security, and in educational development. The framework demonstrates its capacity to inform government and industry policies by leveraging statistics, visualization, and AI-driven decision support. We introduce the concept of “institutional intelligence”—the synergistic integration of human expertise, AI capabilities, and institutional theory—to create adaptive yet stable policy-making systems. This research highlights the transformative potential of data-driven approaches combined with large language models in supporting sustainable and inclusive policy-making processes. Full article

With the advent of NextG wireless networks, the reliance on centralized identity and service management systems poses significant challenges, including limited interoperability, increased privacy vulnerabilities, and the risk of unauthorized tracking or monitoring of user activity. To address these issues, there is a critical need for a decentralized framework that empowers users with self-sovereignty over their subscription information while maintaining trust and privacy among network entities. This article presents a novel framework to enable Self-Sovereign Federated NextG (SSFXG) wireless communication networks. The SSFXG framework separates identity management from the service management layer typically controlled by network operators to foster interoperability functionalities with enhanced privacy and trace-resistant assurances in the NextG landscape. The proposed model relies on blockchain technology as an infrastructure to enable single-authority-free service provisioning and boost mutual trust among federated network components. Further, the SSFXG framework facilitates subscribers’ self-sovereignty over their subscription information while ensuring anonymity and enhanced privacy preservation, avoiding unnecessary network activity monitoring or tracking. Preliminary evaluations demonstrated the effectiveness and efficiency of the proposed framework, making it a promising solution for advancing secure and interoperable NextG wireless networks. Full article

With the rapid increase in the human population and urbanization worldwide, the demand for food production has played a significant role in driving the integration of technology into agriculture. Various Cloud-based systems, such as livestock tracking systems, have been proposed. In those systems, data were collected by the sensors and sent to the Cloud for processing. However, significant issues with those systems were noted, such as high bandwidth utilization and security concerns, such as a high volume of row data traveling from the data collection devices (such as sensors) to the Cloud through the Internet. Additionally, the long distance between the Cloud and the data collection devices makes it unsuitable for latency-sensitive livestock disease monitoring and tracking systems. Therefore, this paper proposes a Fog–Cloud-based approach, where the processing is conducted at the Fog layer, closer to the data collection devices, and only the result is sent to the Cloud for remote viewing. The proposed method aims to reduce power consumption and latency in communication. To validate the proposed method, both the Cloud-based and Fog–Cloud-based scenarios are simulated using iFogSim (a novel simulation tool for IoT and Cloud computing), and the result shows that there is less than twice the power consumption in some scenarios and that the time consumed in the proposed Fog–Cloud-based system, depending on the number of sensors, is five to ten times lower. This study further supports the point that the Fog–Cloud-based is suitable for latency-dependent farming systems such as livestock tracking systems. Full article

PaxosStore is a high-availability storage system developed to support the comprehensive business of WeChat. With the widespread application of WeChat, it is particularly important to verify the safety of PaxosStore. This work proposes a formal model for the storage system PaxosStore using the process algebra Communicating Sequential Processes (CSP) to clearly reflect the interactions of the components in PaxosStore. More importantly, we utilize the model checker Process Analysis Toolkit (PAT) to simulate and verify the constructed CSP model. We specifically verify the validity of six properties: deadlock-freeness, divergence-freeness, robustness, consistency, nontriviality and liveness. Through the verification results, we demonstrate that our formalization model successfully satisfies these properties, confirming the correctness and effectiveness of the framework in ensuring secure interactions among the PaxosStore storage system components. Full article

The future Internet of Things (IoT) will consist of energy harvesting devices and Unmanned Aerial Vehicles (UAVs) to support applications in remote areas. However, as UAVs communicate with IoT devices using broadcast channels, information leakage emerges as a critical security threat. This paper considers the problem of maximizing the minimum secrecy rate in an energy harvesting IoT network supported by two UAVs, where one acts as a server to collect data from devices, and the other is an eavesdropper to intercept data transmission. It presents a novel Mixed-Integer Nonlinear Program (MINLP), which we then linearize into a Mixed-Integer Linear Program (MILP) problem. It also proposes a heuristic solution called Fly Nearest Location (FNL). Both solutions determine (i) the UAV server’s flight routing, flight time, and computation time, as well as (ii) the energy usage and operation mode of IoT devices. Our results show that FNL achieves on average 78.15% of MILP’s performance. Full article

The automatic identification system (AIS) is an essential tool for modern ships, enabling the broadcast of identification and location information. However, the current AIS standard lacks security features, meaning that messages exchanged via AISs are transmitted in plaintext, which leads to security issues such as privacy leakage. Most existing solutions rely on public key cryptography. This paper proposes a physical-layer key generation protocol based on the current AIS standard (ITU-R M.1371-5). In the case of unicast AIS communication, the protocol utilizes channel randomness to generate symmetric keys for securing communications. Compared to public key cryptography, the proposed protocol offers advantages such as low overhead, elimination of third parties, and ease of implementation. Finally, this paper discusses the security of the protocol against various threats as well as evaluates its performance and overhead. Under common speed and signal-to-noise ratio (SNR) conditions, The protocol generates Advanced Encryption Standard (AES) keys of different lengths in under 4000 ms, and these keys successfully pass the National Institute of Standards and Technology (NIST) randomness test. Full article

Community Restaurants (CRs), part of the Brazilian government’s Popular Restaurant Program (PRP), provide free and/or affordable nutritionally balanced meals as an essential strategy to meet the most vulnerable population’s basic needs and rights. This cross-sectional study evaluated the effectiveness of these CRs’ proposed objectives in cities with ≥100,000 inhabitants in Brazil’s northern and northeastern regions—Brazil’s most vulnerable and historically unequal regions. Effectiveness was assessed using a CR evaluation matrix-based indicator system to classify CRs as “not very effective”, “effective”, or “very effective”. Among the 94 CRs assessed (north: n = 23, 24.5%; northeast: n = 71, 75.5%), most were classified as “effective” or “very effective”, except for the northern states of Amapá and Tocantins, whose only CR was rated as “not very effective” and the northeastern state of Sergipe, which had a PR considered “not very effective”. State-operated CRs predominated (north: 82.6%; northeast: 76.1%) and primarily operated Monday to Friday (north: 87.0%; northeast: 59.2%), with 35.2% of the northeast CRs operating daily, serving lunch as the main meal (100%). Average daily meal counts were 486.5 (north) and 926.9 (northeast), and the average meal offering time was from 10:55 am to 1:21 pm in the north and from 10:35 am to 2:00 pm in the northeast region, with costs averaging USD 0.27 and USD 0.20, respectively. All CRs employed a nutritionist as a technical manager responsible for menu planning and demonstrated compliance with essential infrastructure criteria, including regular waste collection, water supply, and proximity to public transport. Most were in areas with sanitary sewage coverage (north: 91.3%; northeast: 98.6%) and had monitoring mechanisms (91.3% north; 94.4% northeast) and prioritization systems for vulnerable populations (north: 73.9%; northeast: 80.0%). These findings indicate that CRs in these regions effectively strive to address food security goals, demonstrating tangible outcomes that benefit society. Full article

In this work, we study the security performance of a double intelligent reflecting surface non-orthogonal multiple access (DIRS-NOMA) wireless communication system supporting communication for a group of two NOMA users (UEs) at the edge, with the existence of an eavesdropping device (ED). We also assume that there is no direct connection between the BS and the UEs. From the proposed model, we compute closed-form expressions for the secrecy outage probability (SOP) and the average security rate (ASR) for each UE. After that, we discuss and analyze the system security performance according to the NOMA power allocation for each user and the number of IRS counter-emission elements. In addition, we analyze the SOP of both the considered DIRS-NOMA and conventional NOMA systems to demonstrate that DIRS-NOMA systems have much better security than conventional NOMA systems. Based on the analytical results, we develop an ASR optimization algorithm using the alternating optimization method, combining NOMA power allocation factor optimization and IRS passive beam optimization through the Lagrange double transform. The derived analytical expressions are validated through Monte Carlo simulations. Full article

Lawful Interception refers to the acquisition of the contents of communications between private individuals or organizations by subjects authorized by law. It involves three actors: the network operator (NO), the Law Enforcement Agency (LEA), and the Law Enforcement Monitoring Facility (LEMF). In the literature, standards and scientific solutions are proposed for the interception procedure and the interaction between the NO and the LEMF. However, no standard has been proposed for the interaction between the LEMF and the LEA. The absence of standards for controlling LEA (or a delegated agency) access to intercepted contents stored by the LEMF is a significant gap that should be overcome. This prevents the implementation of secure, interoperable, and automated procedures, leading to inefficiencies and security risks. In this paper, we propose to cover the above gap by adopting the Self-Sovereign Identity (SSI) paradigm. The adopted research methodology follows a multi-phase approach that includes studying existing solutions, system design, and technical feasibility testing. The study first examines existing standards and identity management frameworks and their limitations. Next, an SSI-based architecture is proposed to manage the interactions between LEA (or a delegated agency) and LEMF. Finally, a proof of concept of the proposed solution written in Python and using the Hyperledger Indy blockchain has been implemented to assess whether our proposal is technically feasible. The proposed solution enhances automation, security, and interoperability in lawful interception. Indeed, it enables machine-readable authorizations, reducing errors and improving efficiency by eliminating manual operations. Additionally, verifiable credentials and decentralized identifiers strengthen security and standardize interactions across jurisdictions, ensuring privacy-preserving identity management. By standardizing interactions between LEA and LEMF, this research contributes to a more secure, privacy-preserving, and legally compliant lawful interception process. Full article

Most electromagnetic metasurfaces only control a single property of electromagnetic waves, such as the phase, amplitude, polarization or frequency, leading to a shortage in capacity and security in communication and a decrease in radar imaging efficiency. By switching the states of four PIN diodes soldered between adjacent resonant arms, cross-polarization and co-polarization reflected waves both with a 1-bit phase can be implemented. The simulation results demonstrate that the proposed metasurface operates within a frequency band of 5.7 GHz to 5.88 GHz, covering ISM 5.8 GHz. Within its operational frequency range, in the cross-polarization reflection case, the losses of the 1-bit phase reflected wave are from 1 dB to 1.5 dB, with a high polarization conversion rate exceeding 91% and even reaching 99%. For the co-polarization reflection case, the losses of the 1-bit reflected wave are from 0.3 dB to 2 dB, and the polarization conversion is almost 100%. The phase difference of the reflected wave in both cases can be realized as about 180°, which satisfies the 1-bit phase requirement for building a good property of beam steering. Upon constructing a 10 × 10 small array, the cross-polarized reflection beam can be steered within the range of elevation angle from 0° to 45° and the elevation angle from 0° to 30° in the co-polarized reflection case. Full article

With the continuous development of UAV technology, the application of UAV swarm has gradually become the focus of research all over the world. Although UAV swarm provides some advantages in terms of autonomous collaboration, the traditional UAV management technology suffers from security challenges, including the risk of single points of failure due to centralized control, which makes UAV swarm susceptible to hacker attacks. Due to some advantages of blockchain, such as decentralization, tamper-proof characteristics, and traceability, it is applied to the drone swarm to solve some security challenges brought about by centralized management. However, blockchain cannot achieve secure access control on the data it stores, which may leak some crucial data. Therefore, a secure and efficient access-control model based on blockchain and ciphertext-policy attribute-based encryption (CP-ABE) is proposed, and a secure data-access scheme is designed under this model, which can not only prevent the leakage of critical data but also realize lightweight access control. Moreover, to improve the decryption efficiency of the data user, an outsourcing-based data decryption scheme is also studied, in which the complex calculations are completed by the data user agency. The experiments show that when the number of attributes is 60, the computation cost of the proposed scheme is 0.404 s, which is much lower than the existing research, and is more suitable for the UAV swarm with limited computing power. Moreover, the communication cost of the proposed scheme is reduced by about 30% compared with the existing scheme under the same conditions. The security analysis also shows that the proposed scheme is secure and reliable, and can resist a variety of attacks such as collusion attacks, man-in-the-middle attacks, and forgery attacks. Full article

In this paper, we consider the issue of the physical layer security (PLS) problem between two nodes, i.e., transmitter (Alice) and receiver (Bob), in the presence of an eavesdropper (Eve) in a near-field communication (NFC) system. Notably, massive multiple-input multiple-output (MIMO) arrays significantly increase array aperture, thereby rendering the eavesdroppers more inclined to lurk near the transmission end. This situation necessitates using near-field channel models to more accurately describe channel characteristics. We consider two schemes with imperfect channel estimation information (CSI). The first scheme involves a conventional multiple-input multiple-output multiple-antenna eavesdropper (MIMOME) setup, where Alice simultaneously transmits information signal and artificial noise (AN). In the second scheme, Bob operates in a full-duplex (FD) mode, with Alice transmitting information signal while Bob emits AN. We then jointly design beamforming and AN vectors to degrade the reception signal quality at Eve, based on the signal-to-interference-plus-noise ratio (SINR) of each node. To tackle the power minimization problem, we propose an iterative algorithm that includes an additional constraint to ensure adherence to specified quality-of-service (QoS) metrics. Additionally, we decompose the robust optimization problem of the two schemes into two sub-problems, with one that can be solved using generalized Rayleigh quotient methods and the other that can be addressed through semi-definite programming (SDP). Finally, our simulation results confirm the viability of the proposed approach and demonstrate the effectiveness of the protection zone for NFC systems operating with CSI. Full article

This paper presents an integrated chaos-based algorithm for image encryption that combines the chaotic Hénon map and chaotic logistic map (CLM) to enhance the security of digital image communication. The proposed method leverages chaos theory to generate cryptographic keys, utilizing a 1D key from the logistic map generator and a 2D key from the chaotic Hénon map generator. These chaotic maps produce highly unpredictable and complex keys essential for robust encryption. Extensive experiments demonstrate the algorithm’s resilience against various attacks, including chosen-plaintext, noise, clipping, occlusion, and known-plaintext attacks. Performance evaluation in terms of encryption time, throughput, and image quality metrics validates the effectiveness of the proposed integrated approach. The results indicate that the chaotic Hénon–logistic map integration provides a powerful and secure method for safeguarding digital images during transmission and storage with a key space that reaches up to $2^{200}$. Moreover, the algorithm has potential applications in secure image sharing, cloud storage, and digital forensics, inspiring new possibilities. Full article

Background: This systematic review will address the influence of Information and Communication Technologies (ICTs) on democratic processes and citizens’ participation, which is enabled by such tools as social media, e-voting systems, e-government initiatives, and e-participation platforms. Methods: Based on an in-depth analysis of 46 peer-reviewed articles published between 1999 and 2024, this review emphasizes how ICTs have improved democratic engagement quality, efficiency, and transparency, but highlights key challenges and research gaps. Results: From this angle, ICT tools have great potential to nurture civic engagement and good governance through transparency. Challenges persist with the ethical and social implications of surveillance technologies, security concerns about digital voting systems, and the widening digital divide disproportionately affecting marginalized populations. The current regulatory framework dealing with privacy and misinformation issues is relatively weak, and there is also a lack of understanding about ICTs’ long-term effects on democratic governance. Conclusions: This review underlines the duality of the roles played by ICT as both an enabler and a challenge to democratic processes. It calls for regulatory measures to protect privacy, fight disinformation, and reduce the digital divide. Future research in this area should focus on the long-term effects of ICTs and how they can be equitably and efficiently integrated into democratic systems, with strategies aimed at maximizing benefits while minimizing risks. Full article

The Haor region in northeastern Bangladesh, characterized by seasonal wetlands and a heavy reliance on fisheries, faces significant challenges due to climate change. Erratic rainfall, prolonged flooding, and ecosystem degradation threaten traditional fishing practices and community livelihoods. This study investigates the potential of climate-resilient cage aquaculture as a sustainable, alternative income-generating solution for vulnerable Haor communities. An 80-day experiment was conducted in five villages of Sunamganj district, Sylhet division, Bangladesh, where tilapia (Oreochromis niloticus) fry were reared in climate-resilient floating cages at five stocking densities: T1 (800 fry/m³), T2 (900 fry/m³), T3 (1000 fry/m³), T4 (1100 fry/m³), and T5 (1200 fry/m³). Key environmental parameters, including temperature (28.12–29.55 °C), dissolved oxygen (4.61–6.55 mg/L), pH (7.53–7.72), and ammonia (0.05–0.76 mg/L), remained within optimal ranges across treatments. Growth performance, survival rate, and economic feasibility were evaluated with T5 yielding the highest gross production (51.77 ± 4.80 kg/m³) and net benefits (7500 ± 500 BDT/m³), achieving a benefit–cost ratio of 1:2.86. The survey findings revealed that a majority of fishers (82%) identified tilapia cage culture as a promising alternative livelihood, yet financial constraints and limited access to credit hinder adoption. Despite these socioeconomic challenges, our findings suggest that tilapia cage culture offers a viable income-generating solution, particularly during flood periods. The study highlights floating cage aquaculture as a climate-resilient strategy to mitigate climate impacts, enhance food security, and improve economic resilience in flood-prone and ecologically sensitive regions. Full article