Quarantine region scheme to mitigate spam attacks in wireless sensor networks

The Quarantine Region Scheme (QRS) is introduced to defend against spam attacks in wireless sensor networks where malicious antinodes frequently generate dummy spam messages to be relayed toward the sink. The aim of the attacker is the exhaustion of the sensor node batteries and the extra delay caused by processing the spam messages. Network-wide message authentication may solve this problem with a cost of cryptographic operations to be performed over all messages. QRS is designed to reduce this cost by applying authentication only whenever and wherever necessary. In QRS, the nodes that detect a nearby spam attack assume themselves to be in a quarantine region. This detection is performed by intermittent authentication checks. Once quarantined, a node continuously applies authentication measures until the spam attack ceases. In the QRS scheme, there is a tradeoff between the resilience against spam attacks and the number of authentications. Our experiments show that, in the worst-case scenario that we considered, a not quarantined node catches 80 percent of the spam messages by authenticating only 50 percent of all messages that it processe

Secure Adaptive Topology Control for Wireless Ad-Hoc Sensor Networks

This paper presents a secure decentralized clustering algorithm for wireless ad-hoc sensor networks. The algorithm operates without a centralized controller, operates asynchronously, and does not require that the location of the sensors be known a priori. Based on the cluster-based topology, secure hierarchical communication protocols and dynamic quarantine strategies are introduced to defend against spam attacks, since this type of attacks can exhaust the energy of sensor nodes and will shorten the lifetime of a sensor network drastically. By adjusting the threshold of infected percentage of the cluster coverage, our scheme can dynamically coordinate the proportion of the quarantine region and adaptively achieve the cluster control and the neighborhood control of attacks. Simulation results show that the proposed approach is feasible and cost effective for wireless sensor networks

Implementing biosecurity measures on dairy farms in Ireland

peer-reviewedDairy farms in Ireland are expanding in preparation for a new era of unrestricted milk production with the elimination of the European Union (EU) production quotas in 2015. Countries experiencing a changing agricultural demographic, including farm expansion, can benefit from documenting the implementation of on-farm biosecurity. The objectives of this study were to document and describe influences on biosecurity practices and related opinions on dairy farms. A representative response rate of 64% was achieved to a nationwide telesurvey of farmers. A 20% discrepancy was found between self-declared and truly ‘closed’ herds indicating a lack of understanding of the closed herd concept. Although >72% of farmers surveyed considered biosecurity to be important, 53% stated that a lack of information might prevent them from improving their biosecurity. Logistic regression highlighted regional, age, and farm-size related differences in biosecurity practices and opinions towards its implementation. Farmers in the most dairy cattle dense region were three times more likely to quarantine purchased stock than were their equivalents in regions where dairy production was less intense (P = 0.012). Younger farmers in general were over twice as likely as middle-aged farmers to implement biosecurity guidelines (P = 0.026). The owners of large enterprises were almost five times more likely to join a voluntary animal health scheme (P = 0.003), and were over three times more likely to pay a premium price for health accredited animals (P = 0.02) than were those farming small holdings. The baseline data recorded in this survey will form the basis for more detailed sociological and demographic research which will facilitate the targeting of future training of the farming community in biosecurity

Achieve Secure Handover Session Key Management via Mobile Relay in LTE-Advanced Networks

Internet of Things is increasing the network by group action immense quantity of close objects which needs the secure and reliable transmission of the high volume knowledge generation, and also the mobile relay technique is one among the economical ways in which to satisfy the on-board knowledge explosion in LTE-Advanced (LTE-A) networks. However, the observe of the mobile relay can cause potential threats to the knowledge security throughout the relinquishing method. Therefore, to handle this challenge, during this paper, we have a tendency to propose a secure relinquishing session key management theme via mobile relay in LTE-A networks. Specifically, within the planned theme, to realize forward and backward key separations, the session key shared between the on-board user instrumentality (UE) and also the connected donor evolved node B (DeNB) is initial generated by the on-board UE then firmly distributed to the DeNB. moreover, to cut back the communication overhead and also the process complexness, a unique proxy re-encryption technique is used, wherever the session keys at the start encrypted with the general public key of the quality management entity (MME) are going to be re-encrypted by a mobile relay node (MRN), so alternative DeNB will later rewrite the session keys with their own non-public keys whereas while not the direct involvement of the MME. elaborated security analysis shows that the planned theme will with success establish session keys between the on-board UEs and their connected DeNB, achieving backward and forward key separations, and resisting against the collusion between the MRN and also the DeNB because the same time. Additionally, performance evaluations via in depth simulations area unit applied to demonstrate the potency and effectiveness of the planned theme

Emotional well-being in COVID-19 mass quarantine: the role of personal response and life activity: a 14-day diary study in China

Objectives: dis study aims to explore quarantined individuals’ emotional well-being over time and how personal response and life activity predict emotional well-being and its change. Design/Methods: Daily data were collected from 134 participants wif 71 having 14 consecutive days’ data. Hierarchical linear modeling (HLM) and General Linear Model (GLM) were used to examine the primary tests. Results: Overall, positive and negative emotions declined significantly during the surveyed period. Meanwhile, differences were observed in the level of positive, depressed, and negative emotions and/or patterns of change among different population categories. The personal response of worrying about work and life was positively related to depressed and negative emotions at baseline, but was negatively related to the development of both depressed and negative emotions over time. Among life activities, family stressor was a significant predictor for both depressed and negative emotions while social support predicted positive emotions. Moreover, health & hygiene activity was positively related to positive emotions at baseline. Conclusions: The results provide scientific evidence for public health policymakers on quarantine policies and inform the general public about quarantine life. They highlight the importance of addressing the needs of vulnerable groups (parents wif young children, divorcees, clinicians) during the pandemic, and demonstrate the benefits of promoting healthcare and hygiene activity, having a sense of worry and access to social support.info:eu-repo/semantics/acceptedVersio

Defining the Costs of an Outbreak of Karnal Bunt of Wheat

In determining the economic impact of a possible outbreak of the quarantinable wheat disease Karnal Bunt, an examination was made of the detailed components of the costs involved. The costs were classified as: (a) Direct costs (yield and quality losses); (b) Reaction costs (export bans, quality down-grading, seed industry costs); and (c) Control costs (quarantine zones, fungicides, spore destruction). The relative importance of each of these cost components is measured for a hypothetical outbreak of Karnal Bunt in the European Union, as a means of ensuring that the policy responses to such an outbreak are appropriate considering the costs involved.disease, quarantine, cost, wheat, Agricultural and Food Policy, Crop Production/Industries,

Management of invading pathogens should be informed by epidemiology rather than administrative boundaries.

Plant and animal disease outbreaks have significant ecological and economic impacts. The spatial extent of control is often informed solely by administrative geography - for example, quarantine of an entire county or state once an invading disease is detected - with little regard for pathogen epidemiology. We present a stochastic model for the spread of a plant pathogen that couples spread in the natural environment and transmission via the nursery trade, and use it to illustrate that control deployed according to administrative boundaries is almost always sub-optimal. We use sudden oak death (caused by Phytophthora ramorum) in mixed forests in California as motivation for our study, since the decision as to whether or not to deploy plant trade quarantine is currently undertaken on a county-by-county basis for that system. However, our key conclusion is applicable more generally: basing management of any disease entirely upon administrative borders does not balance the cost of control with the possible economic and ecological costs of further spread in the optimal fashion.This work was funded by a BBSRC G2O PhD studentship (RNT). We thank Matthew Patrick for help building the GIS map in Figure 1a, and also Richard Stutt and Stephen Parnell for useful discussions.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ecolmodel.2015.12.014

Scalable and Secure Row-Swap: Efficient and Safe Row Hammer Mitigation in Memory Systems

As Dynamic Random Access Memories (DRAM) scale, they are becoming increasingly susceptible to Row Hammer. By rapidly activating rows of DRAM cells (aggressor rows), attackers can exploit inter-cell interference through Row Hammer to flip bits in neighboring rows (victim rows). A recent work, called Randomized Row-Swap (RRS), proposed proactively swapping aggressor rows with randomly selected rows before an aggressor row can cause Row Hammer. Our paper observes that RRS is neither secure nor scalable. We first propose the `Juggernaut attack pattern' that breaks RRS in under 1 day. Juggernaut exploits the fact that the mitigative action of RRS, a swap operation, can itself induce additional target row activations, defeating such a defense. Second, this paper proposes a new defense Secure Row-Swap mechanism that avoids the additional activations from swap (and unswap) operations and protects against Juggernaut. Furthermore, this paper extends Secure Row-Swap with attack detection to defend against even future attacks. While this provides better security, it also allows for securely reducing the frequency of swaps, thereby enabling Scalable and Secure Row-Swap. The Scalable and Secure Row-Swap mechanism provides years of Row Hammer protection with 3.3X lower storage overheads as compared to the RRS design. It incurs only a 0.7% slowdown as compared to a not-secure baseline for a Row Hammer threshold of 1200

A data quarantine model to secure data in edge computing

Edge computing provides an agile data processing platform for latency-sensitive and communication-intensive applications through a decentralized cloud and geographically distributed edge nodes. Gaining centralized control over the edge nodes can be challenging due to security issues and threats. Among several security issues, data integrity attacks can lead to inconsistent data and intrude edge data analytics. Further intensification of the attack makes it challenging to mitigate and identify the root cause. Therefore, this paper proposes a new concept of data quarantine model to mitigate data integrity attacks by quarantining intruders. The efficient security solutions in cloud, ad-hoc networks, and computer systems using quarantine have motivated adopting it in edge computing. The data acquisition edge nodes identify the intruders and quarantine all the suspected devices through dimensionality reduction. During quarantine, the proposed concept builds the reputation scores to determine the falsely identified legitimate devices and sanitize their affected data to regain data integrity. As a preliminary investigation, this work identifies an appropriate machine learning method, linear discriminant analysis (LDA), for dimensionality reduction. The LDA results in 72.83% quarantine accuracy and 0.9 seconds training time, which is efficient than other state-of-the-art methods. In future, this would be implemented and validated with ground truth data

Quantification of risks associated with plant disease: the case of Karnal bunt of wheat.

End of Project ReportThe aim of this study was to assess the economic impact of Tilletia indica, the cause of Karnal bunt of wheat (and triticale) in the EU. The methodologies used are relevant to estimating the costs of controlling other plant and animal diseases. The work was carried out as part of an EU funded research project.European Unio