Search Results (114)

The Social Opportunistic Internet of Things (SO-IoT) is a rapidly emerging paradigm that enables mobile, ad-hoc device communication based on both physical and social interactions. In such networks, routing decisions heavily depend on the selection of intermediate nodes to ensure secure and efficient data dissemination. Traditional approaches relying solely on reliability or social interest fail to capture the multifaceted trustworthiness of nodes in dynamic SO-IoT environments. This paper proposes a trust-based route optimization framework that integrates social interest and behavioral reliability using Bayesian inference and Jeffrey’s conditioning. A composite trust level is computed for each intermediate node to determine its suitability for data forwarding. To validate the framework, we conduct a two-phase simulation-based analysis: a scenario-driven evaluation that demonstrates the model’s behavior in controlled settings, and a large-scale NS-3-based simulation comparing our method with benchmark routing schemes, including random, greedy, and AI-based protocols. Results confirm that our proposed model achieves up to an $88.9\%$ delivery ratio with minimal energy consumption and the highest trust accuracy ($86.5\%$), demonstrating its robustness and scalability in real-world-inspired IoT environments. Full article

Rapid socio-economic development has intensified the conflict between supply and demand for regional water resources, necessitating optimized water resource allocation to enhance water security. This study establishes a multi-objective water resource optimization model by comprehensively considering economic, social, and ecological benefits. Based on the Non-dominated Sorting Genetic Algorithm-III (NSGA-III), we propose the I-NSGA-III algorithm by integrating reference point improvement strategies, dynamic retention of high-quality solutions, and optimized selection strategies to solve the multi-objective optimization model. A multi-system coupling coordination evaluation model is constructed to assess the final allocation schemes. Compared with some commonly used multi-objective algorithms and tested using the DTLZ series functions, the proposed algorithm demonstrates improved overall performance. Specifically, the IGD indicator decreases by 5.17–50.22%, and the HV indicator increases by 2.71–25.51% compared to NSGA-III. The proposed model is applied to Jinzhong City, China, with four scenarios set for the years 2030 and 2035 at P = 50% and P = 75% to derive reasonable water resource allocation schemes. The results show that the economic benefits range from 161.94 × 10⁸ to 212.74 × 10⁸ CNY, the water shortage rate is controlled between 1.38% and 10.86%, and COD emissions are maintained between 6.03 × 10⁴ and 6.91 × 10⁴ tons. Except for the 2030 drought scenario (P = 75%) with a coordination degree of 0.7847, classified as a medium coordination level, all other scenarios have coordination degrees greater than 0.8, indicating a good coordination level. The optimized allocation scheme can serve as a reference for the rational allocation of water resources in Jinzhong City. Moreover, the method proposed in this paper is a general approach that can be extended to other similar water-scarce cities with appropriate parameter adjustments, contributing to the sustainable development of urban water resources. Full article

The widespread use of smart devices, such as phones and live-streaming cameras, has ushered in an era where digital images can be captured and shared on social networks anytime and anywhere. Sharing images demands more bandwidth and stricter security than text. This prevalence poses challenges for secure image forwarding, as it is susceptible to privacy leaks when sharing data. While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. The limited computing power of smart devices complicates the encrypted transmission of images, creating substantial obstacles to implementing security policies on low-computing devices. To address privacy concerns regarding image sharing on social networks, we propose a lightweight data forwarding mechanism for resource-constrained environments. By integrating large-scale data forwarding with visual cryptography, we enhance data security and resource utilization while minimizing overhead. We introduce a downsampling-based non-expansive scheme to reduce pixel expansion and decrease encrypted image size without compromising decryption quality. Experimental results demonstrate that our method achieves a peak signal-to-noise ratio of up to 20.54 dB, and a structural similarity index of 0.72, outperforming existing methods such as random-grid. Our approach prevents size expansion while maintaining high decryption quality, addressing access control gaps, and enabling secure and efficient data exchange between interconnected systems. Full article

In this digital era, social images are the most vital information carrier on multimedia social platforms. More and more users are interested in sharing social images with mobile terminals on multimedia social platforms. Social image sharing also faces potential risks from malicious use, such as illegal sharing, piracy, and misappropriation. This paper mainly concentrates on secure social image sharing. To address how to share social images in a safe way, a social image security scheme is proposed. The technology addresses the social image security problem and the active tracing problem. First, discrete wavelet transform (DWT) is performed directly from the JPEG image. Then, the high-bit planes of the LL, LH, and HL are permuted with cellular automation (CA), bit-XOR, and singular value decomposition (SVD) computing, and their low-bit planes are chosen to embed a watermark. In the end, the encrypted and watermarked image is again permuted with cellular automation in the discrete cosine transform (DCT) domain. Experimental results and security analysis show that the social image security method not only has good performance in robustness, security, and time complexity but can also actively trace the illegal distribution of social images. The proposed social image security method can provide double-level security for multimedia social platforms. Full article

Exploring the spatiotemporal evolution pattern of agricultural functions, analyzing their tradeoff and synergies, carrying out multifunctional zoning, and determining the combination and expansion direction of agricultural functions in combination with regional development strategies are conducive to guiding the adjustment of agricultural structure and promoting the sustainable development of regional agriculture. In this context, based on the county scale and statistical data, this paper uses the agricultural function evaluation index system to measure and analyze the agricultural function index of Sichuan Province and its mutual relations. Spatial overlay analysis is used to analyze the agricultural function index for agricultural leading function zoning. Cluster analysis is used to evaluate the agricultural function results to explore the agricultural multifunctional zoning scheme of Sichuan Province. The results show that the spatial and temporal distribution of agricultural product supply, agricultural leisure, ecological services, employment and social security services are heterogeneous, and the agricultural multifunction index of Sichuan Province shows a spatial distribution pattern of high in the east and low in the west. The synergistic effect between the supply function of agricultural products and the function of employment and life security is the strongest. From 2010 to 2020, the relationships between the ecological service function and the supply function of agricultural products, the agricultural leisure function, employment, and the social security function change from irrelevant or there being a tradeoff effect to there being a significant synergistic effect. The leading areas of the ecological service function are mainly distributed in western and northern Sichuan. The leading areas of the agricultural product supply function are mainly distributed in eastern and southern Sichuan. Agricultural multifunctional zoning in Sichuan Province is divided into the agricultural leisure function, the agricultural product supply cooperative functional area, the weak cooperative functional area, the strong cooperative functional area, and the agricultural leisure priority functional area. The spatiotemporal heterogeneity of agricultural functions and the changes in tradeoffs and synergies in Sichuan Province have a significant impact on the development of agricultural functions. The research results can provide s theoretical reference for agricultural multifunctional zoning in the study area and provide guidance and suggestions for the sustainable development of agricultural economy and society in Sichuan Province. Full article

As the indispensable basic resource of agricultural production, cultivated land has always carried the important mission of maintaining food stability, promoting rural economic development, and maintaining ecological balance. However, in application, there is often a conflict between the multiple functions of cultivated land and the limited ability of cultivated land to perform multiple functions. Therefore, this paper uses hot spot analysis, the IUEMS model, the InVEST model, Pearson correlation coefficients and self-organizing feature maps (SOFMs) to explore the multifunctional trade-offs and synergistic relationships of cultivated land in the Hexi Corridor at the grid scale and the zoning optimization scheme. The results revealed that from 2000 to 2020, the cultivated land production functions and social security functions in the Hexi Corridor maintained a high level and continued to rise, and the hot spots exhibited a stable pattern of “central and southeast concentration”. The ecological function performance is relatively weak, and the hot spots are concentrated mainly in the southeast, whereas the landscape view recreational functions as a whole show a trend of gradual recovery after weakening. In terms of mutual relationships, there are significant synergies between cultivated land production and social security functions, whereas the trade-offs and synergies between other functions are complex and changeable. Production and social security show a coordinated spatial distribution pattern. Production, social security, and ecological functions are dominated by spatial trade-offs. The production and landscape recreation functions, social security and ecological functions, social security and landscape recreation functions, and ecological and landscape recreation functions are mainly synergistic in space. Through self-organizing feature map analysis, the cultivated land in the Hexi Corridor is divided into four functional areas: agricultural production-dominant areas, agricultural social security areas, ecological agriculture areas, and balanced development areas, and management objectives are proposed. This study can provide useful lessons and references for land use planning and management in other similar areas. Full article

Cloud-to-Vehicle (C2V) integration serves as a fundamental infrastructure to provide robust computing and storage support for Vehicular Social Networks (VSNs). However, the proliferation of sensitive personal data within VSNs poses significant challenges in achieving secure and efficient data sharing while maintaining data usability and precise retrieval capabilities. Although existing searchable attribute-based encryption schemes offer the secure retrieval of encrypted data and fine-grained access control mechanisms, these schemes still exhibit limitations in terms of bilateral access control, dynamic index updates, and search result verification. This study presents a Dual-Policy Attribute-based Searchable Encryption (DP-ABSE) scheme with dynamic keyword update functionality for VSNs. The scheme implements a fine-grained decoupling mechanism that decomposes data attributes into two distinct components: immutable attribute names and mutable attribute values. This decomposition transfers the attribute verification process from data owners to the encrypted files themselves, enabling data attribute-level granularity in access control. Through the integration of an identity-based authentication mechanism derived from the data owner’s unique identifier and bilinear pairing verification, it achieves secure updates of the specified keywords index while preserving both the anonymity of the non-updated data and the confidentiality of the message content. The encryption process employs an offline/online two-phase design, allowing data owners to pre-compute ciphertext pools for efficient real-time encryption. Subsequently, the decryption process introduces an outsourcing local-phase mechanism, leveraging key encapsulation technology for secure attribute computation outsourcing, thereby reducing the terminal computational load. To enhance security at the terminal decryption stage, the scheme incorporates a security verification module based on retrieval keyword and ciphertext correlation validation, preventing replacement attacks and ensuring data integrity. Security analysis under standard assumptions confirms the theoretical soundness of the proposed solution, and extensive performance evaluations showcase its effectiveness. Full article

With The integration of renewable energy sources into smart grids and electric vehicle (EV) charger-sharing networks is essential for achieving the goal of environmental sustainability. However, the uneven distribution of distributed energy trading among EVs, fixed charging stations (FCSs), and mobile charging stations (MCSs) introduces challenges such as inadequate supply at FCSs and prolonged latencies at MCSs. In this paper, we propose a multi-agent deep reinforcement learning (MADRL)-based auction algorithm for energy trading that effectively balances charger supply with energy demand in distributed EV charging markets, while also reducing total charging latency. Specifically, this involves a MADRL-based hierarchical auction that dynamically adapts to real-time conditions, optimizing the balance of supply and demand. During energy trading, each EV, acting as a learning agent, can refine its bidding strategy to participate in various local energy trading markets, thus enhancing both individual utility and global social welfare. Furthermore, we design a cross-chain scheme to securely record and verify transaction results of energy trading in decentralized EV charger-sharing networks to ensure integrity and transparency. Finally, experimental results show that the proposed algorithm significantly outperforms both the second-price and double auctions in increasing global social welfare and reducing total charging latency. Full article

The rapid development of Artificial General Intelligence (AGI) in recent years has provided many new opportunities and challenges for human social production. However, recent evaluation methods have some problems with regard to consistency, subjectivity and comprehensiveness. In order to solve the above problems, in this paper, we propose an Artificial General Intelligence Security Evaluation scheme (AGISE), which is based on analytic hierarchy process (AHP) technology with a genetic algorithm, to comprehensively evaluate the AGI security based on multiple security risk styles and complex indicators. Firstly, our AGISE combines AHP technology with a genetic algorithm to realize reliable, consistent and objective evaluation for AGI security. Secondly, in our AGISE, we propose implementing more effective AGI security evaluation classification and indicator settings. Finally, we demonstrate the effectiveness of our AGISE through experiments. Full article

This study establishes and refines a social-landscape ecological security pattern that integrates the demand and supply of ecosystem services, providing a substantial foundation for the ecological restoration of territorial spaces. This foundation is crucial for enhancing the effectiveness of “social–ecological” systems in achieving sustainable development. Jilin Province, serving as a national ecological security buffer and experiencing rapid economic growth, exhibits a significant spatial imbalance between social and economic progress and ecological conservation. The balance of ecosystem service demand and supply is pivotal in this context, making Jilin Province an ideal study area. We employed a multifaceted approach, including MSPA, the InVEST model, landscape connectivity assessment, circuit theory, and ecological network integrity evaluation, to elucidate the spatial disparities between the demand and supply of ecosystem services. We then developed and optimized social and landscape ecological security patterns to meet human demands and safeguard ecological integrity, thereby promoting the sustainable development of “social–ecological” systems. The key findings are as follows: (1) The supply of ecosystem services shows a clear spatial gradient, with lower values in the west and higher in the east, while demand is concentrated in the central region with lower values in the east and west, indicating a pronounced spatial mismatch in Jilin Province. (2) The landscape ecological security pattern includes 18 barrier points, 33 pinch points, 166 ecological corridors, and 101 ecological sources. (3) The social–ecological security pattern comprises 119 demand sources and 150 supply–demand corridors. (4) The study introduces 14 supply–demand nodes and 47 optimization corridors, proposing zoning schemes for the eastern core protection area, the central ecological demand area, and the western core restoration area. Additionally, recommendations are concerning the optimization of the “social–ecological” system pattern. This research advances the theoretical understanding of “social–ecological” system development in Jilin Province and offers insights for more harmonized development strategies. Full article

Social economy actors have assisted the recovery from crises by providing innovative solutions that are aimed at strengthening public services to complement government action. Currently, the widespread use of information and communication technologies (ICTs) by both citizens and organizations has changed society’s routine behavior, giving rise to the so-called information society. One of the major burdens of using big data for social problems is the lack of adequate data governance standards. Challenging and critical issues about big data include privacy and security for most of the social economy field of activities. Blockchain technology has attracted the attention of academic researchers and industries, which combines technologies like cryptography, end-to-end communication, and algorithms. Moreover, blockchain technology provides user anonymity to protect the privacy of users. We propose a hierarchical blockchain system for social economy services that can effectively protect the security and privacy of users and transmitted data. The proposed scheme was proven to ensure the legitimacy of all parties in the system and security of data and transactions, and blockchain technology and signcryption mechanisms were applied to achieve integrity, non-repudiation, and traceability. Security and performance analyses are also provided to prove that the proposed scheme achieved the above security concerns with efficiency. Full article

The abuse of UAVs poses a potential risk to social security, necessitating the investigation of anti-UAV methods to safeguard critical areas. However, the existing UAV countermeasures face challenges such as high environmental impact, restricted spatial deployment, and low cost-effectiveness. To address these limitations, we developed a novel anti-UAV system known as UAV Hunter, which adopts an airborne tether-net capture device with visual aids to counter unauthorized UAVs. This system employs an “Anti-UAV with UAV” scheme, comprising a ground control station and a net-capturing UAV. The operator utilizes the ground control station to determine the mission area and flight path and then controls the flight of the net-capturing UAV. During flight, the net-capturing UAV leverages its dual-mode sensor to continuously monitor the target area. Simultaneously, the onboard computer executes a UAV detection and tracking algorithm to search for unauthorized UAVs in real time. The results are relayed to the operator in real time, facilitating precise adjustments for the net-capturing UAV to launch the rope net accurately. The system successfully realizes the functions of dual-mode real-time detection and tracking, precise net capture, and efficient integrated control. Compared with existing methods, the developed system exhibits accurate recognition, rapid action, diverse application scenarios, and an enhanced human–machine interaction experience. Test results in the open environment further validate the feasibility and functional integrity of the system, demonstrating its capability to effectively capture low-altitude unauthorized UAVs. Full article

This study contributes to the discussion about a fair and balanced pension system with a collectively funded pension scheme or social security and a defined contribution pillar. With an invigorated risk approach using financial option positions, it considers the variance of socioeconomic interests of different society-earning cohorts. By that, it enables the assumption of un-uniformity in interests about the fair and sustainable pension design. Specifically, we claim that the alternative cost of hedging the ideal position to the counterparty position studies the implied risks and returns that participants are willing to absorb and hence may lead to a fair compromise when there are different interests. The novelty of the introduced method is mainly based on the variety of participants’ risks and not on the utility function. Accordingly, we spare the discussion about the right shape of the utility function and the proper calibrations. Full article

As technology advances and develops, the need for strong and simple authentication mechanisms that can help protect data intensifies. The contemporary approach to giving access control is through graphical passwords comprising images, patterns, or graphical items. The objective of this review was to determine the documented security risks that are related to the use of graphical passwords, together with the measures that have been taken to prevent them. The review was intended to present an extensive literature review of the subject matter on graphical password protection and to point toward potential future research directions. Many attacks, such as shoulder surfing attacks, SQL injection attacks, and spyware attacks, can easily exploit the graphical password scheme, which is one of the most widely used. To counter these security threats, several measures have been suggested, but none of the security attacks can be completely overcome. Each of the proposed measures has its pros and cons. This study begins by elucidating some of the graphical password schemes studied between 2012 and 2023, delving into potential threats and defense mechanisms associated with these schemes. Following a thorough identification and selection process, five of the reviewed papers explain the threat of shoulder surfing and spyware attacks on graphical password schemes, while two explain the threat of brute force attacks. One paper focuses on dictionary attacks, while four other papers address social engineering, SQL injection attacks, and guessing attacks as potential threats to graphical password schemes. In addition, the papers recognize other forms of attacks, such as video recording attacks, filtering attacks, reverse engineering attacks, multiple observation attacks, key/mouse logger attacks, insider attacks, computer vision attacks, image gallery attacks, sonar attacks, reply attacks, data interception attacks, and histogram manipulation attacks. These attacks are examined in three, three, eight, one, four, one, one, one, one, one, one, and one papers, respectively. Moreover, out of all such countermeasures, most of them are based on three categories—randomization, obfuscation, and password space complexity—which are the most commonly employed strategies for improving graphical password schemes. Full article

Today, more than ever before, technological progress is evolving rapidly, and in the absence of adequate regulatory frameworks, the big players in the digital market (the so-called Big Techs) are exploiting personal data (name, address, telephone numbers) and private data (political opinions, religious beliefs, financial information, or health status) in an uncontrolled manner. A crucial role in this scenario is played by the weakness of international regulatory frameworks due to the slow response time of legislators who are incapable, from a regulatory point of view, of keeping pace with technological evolution and responding to the new requirements coming from the social context, which is increasingly characterized by the pervasive presence of new technologies, such as smartphones and wearable devices. At the European level, the General Data Protection Regulation (GDPR) and the Regulation on Electronic Identification, Authentication and Trust Services (eIDAS) have marked a significant turning point in the regulatory landscape. However, the mechanisms proposed present clear security issues, particularly in light of emerging concepts such as digital identity. Moreover, despite the centrality of biometric issues within the European regulatory framework and the practical introduction of biometric data within electronic national identity (eID) cards, there are still no efforts to use biometric features for the identification and authentication of a person in a digital context. This paper clarifies and precisely defines the potential impact of biometric-based digital identity and hypothesizes its practical use for accessing network-based services and applications commonly used in daily life. Using the Italian eID card as a model, an authentication scheme leveraging biometric data is proposed, ensuring full compliance with GDPR and eIDAS regulations. The findings suggest that such a scheme can significantly improve the security and reliability of electronic identification systems, promoting broader adoption of eIDAS solutions. Full article