Implementation, Characterization and Application of Path Changing Switch based Arbiter PUF on FPGA as a lightweight Security Primitive for IoT

The damage caused by counterfeits of semiconductors has become a serious problem. Recently, a physical unclonable function (PUF) has attracted attention as a technique to prevent counterfeiting. The present study investigates an arbiter PUF, which is a typical PUF. The vulnerability of a PUF against machine-learning attacks has been revealed. It has also been indicated that the output of a PUF is inverted from its normal output owing to the difference in environmental variations, such as the changes in power supply voltage and temperature. The resistance of a PUF against machine-learning attacks due to the difference in environmental variation has seldom been evaluated. The present study evaluated the resistance of an arbiter PUF against machine-learning attacks due to the difference in environmental variation. By performing an evaluation experiment using a simulation, the present study revealed that the resistance of an arbiter PUF against machine-learning attacks due to environmental variation was slightly improved. However, the present study also successfully predicted more than 95% of the outputs by increasing the number of learning cycles. Therefore, an arbiter PUF was revealed to be vulnerable to machine-learning attacks even after environmental variation.

With limited resources, growing environment constraints and downward pressure on the economy, increasing agricultural environmental total factor productivity (AETFP) and its contribution to agricultural growth is significant for transforming agricultural development to make it more resource efficient and environment-friendly. This paper considered technological heterogeneity in different regions of China and measured AETFP in 30 provinces from 1997 to 2015 using the Metafrontier Malmquist-Luenberger (MML) productivity index. Multi-dimensional analysis was made on temporal and spatial characteristics, evolution patterns, and influencing factors of AETFP in China. The results showed that: (1) AETFP increased in the Ninth, Tenth, Eleventh, and Twelfth Five-Year Plan periods, with average annual growth rates of 0.76%, 0.88%, 1.17%, and 0.87%, respectively. (2) The average annual growth rate of AETFP in the eastern, central, and western regions decreased successively. The eastern region generally had played a leading role. The central region had a catch-up effect on environmental production technologies from the eastern region, while the western region lacked the catch-up effect. (3) The dynamic evolution of AETFP had prominent features. For the whole nation, the kernel density curve of AETFP continuously moved to the right. The main peak value continuously decreased and the width of the main peak continuously increased. The internal differences of AETFP in the eastern and western regions exhibited an increasing trend, while the internal differences of AETFP in the central region showed little change. (4) There was an inverted U-shaped relationship between agricultural economic growth and AETFP. Both the disaster rate and planting structure had a negative impact on AETFP with varying degrees of significance. Income gaps between urban and rural areas can partially offset the role of urbanization in promoting the growth of AETFP. The greater the income differences between urban and rural areas, the weaker the role of urbanization in promoting the growth of AETFP. These findings can help the government determine policies to change the agricultural development mode and formulate effective measures to improve AETFP.

Edge computing (EC) faces unique security threats due to its distributed architecture, resource-constrained devices, and diverse applications, making it vulnerable to data breaches, malware infiltration, and device compromise. The mitigation strategies against EC data security threats include encryption, secure authentication, regular updates, tamper-resistant hardware, and lightweight security protocols. Physical Unclonable Functions (PUFs) are digital fingerprints for device authentication that enhance interconnected devices’ security due to their cryptographic characteristics. PUFs produce output responses against challenge inputs based on the physical structure and intrinsic manufacturing variations of an integrated circuit (IC). These challenge-response pairs (CRPs) enable secure and reliable device authentication. Our work implements the Arbiter PUF (APUF) on Altera Cyclone IV FPGAs installed on the ALINX AX4010 board. The proposed APUF has achieved performance metrics of 49.28% uniqueness, 38.6% uniformity, and 89.19% reliability. The robustness of the proposed APUF against machine learning (ML)-based modeling attacks is tested using supervised Support Vector Machines (SVMs), logistic regression (LR), and an ensemble of gradient boosting (GB) models. These ML models were trained over more than 19K CRPs, achieving prediction accuracies of 61.1%, 63.5%, and 63%, respectively, thus cementing the resiliency of the device against modeling attacks. However, the proposed APUF exhibited its vulnerability to Multi-Layer Perceptron (MLP) and random forest (RF) modeling attacks, with 95.4% and 95.9% prediction accuracies, gaining successful authentication. APUFs are well-suited for device authentication due to their lightweight design and can produce a vast number of challenge-response pairs (CRPs), even in environments with limited resources. Our findings confirm that our approach effectively resists widely recognized attack methods to model PUFs.

In the next future, IoT systems will be “ubiquitous” and “pervasive”, bringing several benefits to mankind and also many issues about interoperability, security and privacy. The intrinsic vulnerabilities of IoT devices, with limited resources and heterogeneous technologies, together with the lack of specifically designed IoT standards, represent a fertile ground for the expansion of specific cyber threats. Consequently, security and privacy issues have become a great challenge in the IoT topic. In this paper we try to bring order on the IoT security panorama providing a taxonomical analysis from the perspective of the three main key layers of the IoT system model: Perception, Transportation and Application levels. As a result of the analysis, we will highlight the most critical issues with the aim of guiding future research directions.

COST OF DEFENSE IN THE CONTEXT OF PLANT COMPETITION: BRASSICA RAPA MAY GROW<i>AND</i>DEFEND

Internet of Things(IoT) is a technical revolution of the internet where users, computing systems, and daily objects having sensing abilities, collaborate to provide innovative services in several application domains. Opportunistic IoT(OppIoT)is an extension of the opportunistic networks that exploits the interactions between the human-based communities and the IoT devices to increase the network connectivity and reliability. In this context, the security and privacy requirements play a crucial role as the collected information is exposed to a wide unknown audience. An adaptable infrastructure is required to handle the intrinsic vulnerabilities of OppIoT devices, with limited resources and heterogeneous technologies. This chapter elaborates the security requirements, the possible threats, and the current work conducted in the field of security in OppIoT networks.

The Internet of Things (IoT) is a network of physically connected, online-connected, globally distributed things. Given that most smart gadgets are carried by people, we may take advantage of their owners' social connections to prevent interception by unauthorized users, which is consistent with the Social Internet of Things (SIoT) concept. SIoT combines social networks and IoT to enable communication between devices and people as well as information sharing. This convergence has enhanced both perspectives and given rise to new ecologies. Indeed, the inherent weaknesses of SIoT devices, combined with limited resources and heterogeneous technology, as well as the absence of particularly developed IoT protocols, provide ideal platform for the spread of specialised cyber attacks. The security of social IoT is a big concern since linked devices can lead to large amounts of personal data being gathered and retained by organizations. To ensure security, it is vital for firms to take mechanisms such as encryption, authentication, authorization, and access control to secure data and ensure privacy. Furthermore, businesses should adopt security rules and standards to ensure that data is handled securely. This can include routine software upgrades as well as the installation of firewalls and secure networks. This paper provides an overview of the privacy issues and requirements that SIoT currently confronts.

Social Internet of Things (SIoT) is a new paradigm where Internet of Things (IoT) merges with social networks, allowing people and devices to interact, and facilitating information sharing. However, security and privacy issues are a great challenge for IoT but they are also enabling factors to create a “trust ecosystem.” In fact, the intrinsic vulnerabilities of IoT devices, with limited resources and heterogeneous technologies, together with the lack of specifically designed IoT standards, represent a fertile ground for the expansion of specific cyber threats. In this paper, we try to bring order on the IoT security panorama providing a taxonomic analysis from the perspective of the three main key layers of the IoT system model: 1) perception; 2) transportation; and 3) application levels. As a result of the analysis, we will highlight the most critical issues with the aim of guiding future research directions.

A large-scale complex construction project is a gigantic system integrated with multiple factors, participants, management levels and relations. Complicated and varying management risks arise in such projects due to the diversity of project targets, the limitation of resources, the variation of environments and conflicts of multiple interests. Traditional risk management methods may be improper and inadaptable for large complex projects. Based on the characteristics and laws in management risks of such projects, a study was conducted on the feasible methods and related steps of management risk analysis. A system of management risk evaluation for large complex projects based on Grey Evaluation was brought forward, with a case study of Nanning International Convention and Exhibition Center presented as a demonstration. The result indicates that this method can reflect the randomicity, fuzziness and grayness of risk information in the management of large complex projects, and make the risk evaluation more scientific and reasonable.

Current climate change models predict an increase in temperature variability and extreme events such as heatwaves, and organisms need to cope with consequent changes to environmental variation. Non-genetic inheritance mechanisms can enable parental generations to prime their offspring's abilities to acclimate to environmental change-but they may also be deleterious. When parents are exposed to predictable environments, intergenerational plasticity can lead to better offspring trait performance in matching environments. Alternatively, parents exposed to variable or unpredictable environments may use plastic bet-hedging strategies to adjust the phenotypic variance among offspring. Here, we used a model species, the threespine stickleback (Gasterosteus aculeatus), to test whether putatively adaptive intergenerational effects can occur in response to shifts in environmental variation as well as to shifts in environmental mean, and whether parents employ plastic bet-hedging strategies in response to increasing environmental variation. We used a full-factorial, split-clutch experiment with parents and offspring exposed to three temperature regimes: constant, natural variation, and increased variation. We show that within-generation exposure to increased temperature variation reduces growth of offspring, but having parents that were exposed to natural temperature variation during gametogenesis may offset some early-life negative growth effects. However, these mitigating intergenerational effects do not appear to persist later in life. We found no indication that stickleback mothers plastically altered offspring phenotypic variance (egg size or clutch size) in response to temperature variation. However, lower inter-individual variance of juvenile fish morphology in offspring of increased variation parents may imply the presence of conservative bet-hedging strategies in natural populations. Overall, in our experiment, parental exposure to temperature variation had limited effects on offspring fitness-related traits. Natural levels of environmental variation promoted a potentially adaptive intergenerational response in early life development, but under more challenging conditions associated with increased environmental variation, the effect was lost.

It has been a significant issue to satisfy the rapidly growing data traffic with the limited wireless radio resources. Licensed-assisted access to unlicensed spectrum (e.g., LAA) brings hope for the service provider (SP) to mitigate the deficiency of radio resources. This work contributes on designing a pricing model in a licensed and unlicensed coexisting network, modelled as a two-sided market with content providers (CPs) and end users (EUs) at the SP's two sides. A premium content delivery deal is further designed via the optimal auction in order to efficiently allocate the scarce radio resources for the CPs with higher traffic load and QoS requirement. Thus, the SP and CPs form a prioritized spectrum game, and the SP and EUs form a radio access subscription game. By backward induction, we derive the basic delivery price and the premium delivery price to CPs, the reservation price, and the LTE-only and LAA subscription prices to EUs. Analysis shows that all players benefit from the premium delivery deal and co-existence of unlicensed LTE. When the unlicensed spectrum becomes reliable, all players' payoffs and the subscription ratio increase. In addition, the impact of the subsidies and technology heterogeneity are also addressed in this article.

Aim In terrestrial plant communities, the relationship between native species diversity and exotic success is typically scale‐dependent. It is often proposed that within local neighbourhoods, high native diversity limits resources, thereby inhibiting exotic success. However, environmental variation that manifests over space or time can create positive correlations between native diversity and exotic success at larger scales. In marine habitats, there have been few multi‐scale surveys of this pattern, so it is unclear how diversity, resource limitation and the environment influence the success of exotic species in these systems.Location Washington, USA.Methods I analysed nested spatial and temporal surveys of fouling communities, which are assemblages of sessile marine invertebrates, to test whether the relationships between native richness, resource availability and exotic cover supported the diversity‐stability and diversity‐resistance theories, to test whether these relationships changed with spatio‐temporal scale, and to explore the temperature preferences of native and exotic fouling species.Results Survey data failed to support diversity‐stability theory: space availability actually increased with native richness at the local neighbourhood scale, and neither space availability nor variability decreased with native richness across larger spatio‐temporal scales. I did find support for diversity‐resistance theory, as richness negatively correlated with exotic cover in local neighbourhoods. Unexpectedly, this negative correlation disappeared at intermediate scales, but emerged again at the regional scale. This scale‐dependent pattern could be partially explained by contrasting water temperature preferences of native and exotic species.Main conclusions Within local neighbourhoods, native diversity may inhibit exotic abundance, but the mechanism is unlikely related to resource limitation. At the largest scale, correlations suggest that native richness is higher in cooler environments, whereas exotic richness is higher in warmer environments. This large‐scale pattern contrasts with the typical plant community pattern, and has important implications for coastal management in the face of global climate change.

The carbon isotopic composition (δ(13) C) of plant material has been used extensively as an indirect measure of carbon fixation per volume of water used. More recently, the δ(13) C of phloem sap (δ(13) C(phl) ) has been used as a surrogate measure of short-term, canopy scale δ(13) C. Using a combination of δ(13) C physiological, structural and chemical indices from leaves and phloem sap of Eucalyptus globulus at sites of contrasting water availability, we sought to identify short-term, canopy scale resource limitations. Results illustrate that δ(13) C(phl) offers valid reflections of short-term, canopy scale values of leaf δ(13) C and tree water status. Under conditions limited by water, leaf and phloem sap photoassimilates differ in (13) C abundance of a magnitude large enough to significantly influence predictions of water use efficiency. This pattern was not detected among trees with adequate water supply indicating fractionation into heterotrophic tissues that may be sensitive to plant water status. Trees employed a range of physiological, biochemical and structural adaptations to acclimate to resource limitation that differed among sites providing a useful context upon which to interpret patterns in δ(13) C. Our results highlight that such easily characterized properties are ideal for use as minimally invasive tools to monitor growth and resilience of plants to variations in resource availability.

Climate change can impact species interactions by changing the spatial and/or temporal overlap of interaction partners, but interspecific interactions can also vary when partners remain co‐located in space and time. Understanding the effects of climate‐driven environmental variation, such as rising temperatures, is particularly important for interactions that underlie key ecosystem functions like pollination. However, very little is known about how temperature variation may impact plant‐pollinator interaction patterns in the absence of shifts in species presence or abundance, in part because environmental variation across multiple days or sites is often confounded with changing community composition.In this study, we examined the effects of temperature variation on pollinators' choice of floral partners within near‐static ecological communities by sampling interactions at multiple temperatures within individual days—a method that allowed us to disentangle the effects of temperature variation and species turnover on patterns of plant‐pollinator interactions. The substantial temperature variation both within and across days in each growing season also enabled us to largely disentangle temperature variation from time‐of‐day effects. With this sampling protocol, we show that temperature can influence pollinator floral choice independently of changes in species composition.We found differences in the choice of floral resources across pollinator taxa as temperature varied during individual days and further found that bumble bees, but not sweat bees, exhibited this pattern when analyzed independently. We also confirmed that our observed trends were not driven by variation in the number of interactions recorded, the relative abundance of pollinators, or in the overall attractiveness of flowers at different temperatures.We propose that thermal niche partitioning in this system could be driven by physiological and behavioral factors including energetics and competition for specific floral resources at different temperatures. These insights into thermal variation in pollinators' floral choice contribute to wider understanding of the fine‐scale mechanisms through which climate change may impact ecological networks, community resilience, and ecosystem functioning.

Using ecological theory to develop recovery criteria for an endangered butterfly