Blockchain-Enabled Authenticated Key Agreement Scheme for Mobile Vehicles-Assisted Precision Agricultural IoT Networks

Precision Farming Has a Positive Potential in the Agricultural Industry Regarding Water Conservation, Increased Productivity, Better Development of Rural Areas, and Increased Income. Blockchain Technology is a Better Alternative for Storing and Sharing Farm Data as It is Reliable, Transparent, Immutable, and Decentralized. Remote Monitoring of an Agricultural Field Requires Security Systems to Ensure that Any Sensitive Information is Exchanged Only among Authenticated Entities in the Network. to This End, We Design an Efficient Blockchain-Enabled Authenticated Key Agreement Scheme for Mobile Vehicles-Assisted Precision Agricultural Internet of Things (IoT) Networks Called AgroMobiBlock. the Limited Existing Work on Authentication in Agricultural Networks Shows Passive Usage of Blockchains with Very High Costs. AgroMobiBlock Proposes a Novel Idea using the Elliptic Curve Operations on an Active Hybrid Blockchain over Mobile Farming Vehicles with Low Computation and Communication Costs. Formal and Informal Security Analysis Along with the Formal Security Verification using the Automated Validation of Internet Security Protocols and Applications (AVISPA) Software Tool Have Shown the Robustness of AgroMobiBlock Against Man-In-The-Middle, Impersonation, Replay, Physical Capture, and Ephemeral Secret Leakage Attacks among Other Potential Attacks. the Blockchain-Based Simulation on Large-Scale Nodes Shows the Computational Time for an Increase in the Network and Block Sizes. Moreover, the Real-Time Testbed Experiments Have Been Performed to Show the Practical Usefulness of the Proposed Scheme

Performance optimization problem in speculative prefetching

Speculative prefetching has been proposed to improve the response time of network access. Previous studies in speculative prefetching focus on building and evaluating access models for the purpose of access prediction. This paper investigates a complementary area which has been largely ignored, that of performance modeling. We analyze the performance of a prefetcher that has uncertain knowledge about future accesses. Our performance metric is the improvement in access time, for which we derive a formula in terms of resource parameters (time available and time required for prefetehing) and speculative parameters (probabilities for next access). We develop a prefetch algorithm to maximize the improvement in access time. The algorithm is based on finding the best solution to a stretch knapsack problem, using theoretically proven apparatus to reduce the search space. An integration between speculative prefetching and caching is also investigated

Coverage Enhancement of PBCH using Reduced Search Viterbi for MTC in LTE-Advanced Networks

Abstract-Machine Type Communication (MTC) is becoming an integral part of the Long Term Evolution -Advanced (LTE-A) cellular network. Challenges arise when some of the MTC devices, due to the nature of their applications, are deployed in low signal locations. As per 3GPP requirements, there is a need for additional coverage enhancement up to 20 dB in comparison with LTE category 1 UE for MTC devices. In the previous works reported till now, Repetition Coding is proposed as an effective technique to achieve the required coverage enhancements at cost of longer decoding time. In low signal conditions where many repetitions are required to build the SNR needed, the decoding delay may be unacceptable. For a LTE-A MTC UE, Physical Broadcast CHannel (PBCH) decoding has a very important role and fast, efficient decoding of PBCH will help to improve the device performance. In this paper, we propose to use well established technique called Reduced Search (RS) Viterbi to improve PBCH decoding performance without compromising the time-to-decode. RS Viterbi technique utilizes a priori knowledge of transmitted bits to reduce the size and complexity of trellis, which in turn also reduces probability of choosing incorrect path, i.e., error. Up to 2.2 dB SNR gain is seen in simulation using the RS Viterbi decoding against the conventional Viterbi decoding, which will contribute in improving the sensitivity of MTC devices for better reachability

Active Learning Augmented Folded Gaussian Model for Anomaly Detection in Smart Transportation

Smart transportation networks have become instrumental in smart city applications with the potential to enhance road safety, improve the traffic management system and driving experience. A Traffic Message Channel (TMC) is an IoT device that records the data collected from the vehicles and forwards it to the Roadside Units (RSUs). This data is further processed and shared with the vehicles to inquire the fastest route and incidents that can cause significant delays. The failure of the TMC sensors can have adverse effects on the transportation network. In this paper, we propose a Gaussian distribution-based trust scoring model to identify anomalous TMC devices. Then we propose a semi-supervised active learning approach that reduces the manual labeling cost to determine the threshold to classify the honest and malicious devices. Extensive simulation results using real-world vehicular data from Nashville are provided to verify the accuracy of the proposed method

Preserving Privacy In Image Database Through Bit-planes Obfuscation

The recent surge in computer vision applications has caused visual privacy concerns to people who are either users or exposed to an underlying surveillance system. To preserve their privacy, image obfuscation lays out a strong road through which the usability of images can also be maintained without revealing any visual private information. However, prior solutions are susceptible to reconstruction attacks or produce non-trainable images even by leveraging the obfuscation ways. This paper proposes a novel bit-planes-based image obfuscation scheme, called Bimof, to protect the visual privacy of the user in the images that are input into a recognition-based system. By incorporating the chaotic system for non-invertible noise with matrix decomposition, Bimof offers strong security and usability for creating a secure image database. In Bimof, it is hard for an adversary to recover the original image, withstanding a malicious server. We conduct experiments on two standard activity recognition datasets, UCF101 and HMDB51, to validate the effectiveness and usability of our scheme. We provide a rigorous quantitative security analysis through pixel frequency attacks and differential analysis to support our findings

Mobile terminal receiver design: LTE and LTE-advanced

Combines in one volume the basics of evolving radio access technologies and their implementation in mobile phones. Reviews the evolution of radio access technologies (RAT) used in mobile phones and then focuses on the technologies needed to implement the LTE (Long term evolution) capability. Coverage includes the architectural aspects of the RF and digital baseband parts before dealing in more detail with some of the hardware implementation. Unique coverage of design parameters and operation details for LTE-A phone transceiver. Discusses design of multi-RAT Mobile with the consideration of cost and form factors. Provides in one book a review of the evolution of radio access technologies and a good overview of LTE and its implementation in a handset. Unveils the concepts and research updates of 5G technologies and the internal hardware and software of a 5G phone

Target Detection and Localization Methods using Compartmental Model for Internet of Things

This paper analyses the performance of target detection and localization methods in heterogeneous sensor networks using compartmental model, which is an attenuation model expressing the variation of received signal strength (RSS) with propagation distance. First, we compute the threshold for the proposed target detection scheme, based on the decision fusion of different sensors and without requiring a priori probability. We also derive the bound on the threshold and subsequently the lower and upper bounds on the detection and false-alarm probabilities. Next, the location of the detected target is estimated using iterative mini-batch Singular Value Decomposition (SVD) methods in the presence of sensor location uncertainty. We highlight that the method for localization has low computational complexity which is suitable for Internet of Things (IoT) networks. The effectiveness of the compartmental model is demonstrated using both simulation study and real experiments. The model parameters are estimated using WiFi signal strength received on the mobile phones from the access points in an indoor environment

ZU-Mean: Fingerprinting based Device Localization Methods for IoT in the Presence of Additive and Multiplicative Noise

This paper proposes Zero-Mean and Unity-Mean (ZU-Mean) features based device localization methods for internet of things (IoT). These features do not depend on the hardwares and/or specifications of the devices being used. Moreover, the zero-mean and unity-mean features mitigate the additive and multiplicative noise, respectively. Extensive real experiments are conducted in two different sites (residential and mall areas) using WiFi received signal strength (RSS) for five weeks. The performance of the proposed methods is better than the absolute RSS based method. We also highlight that the absolute RSS feature cannot be used in calibration-free method and hence, it is not suitable for diverse devices in IoT networks. Additionally, the proposed low-cost method is computationally efficient as compared to the existing methods in the literature

Studies directed toward the exploitation of vicinal diols in the synthesis of (+)-nebivolol intermediates

While the exploitation of the Sharpless asymmetric dihydroxylation as the source of chirality in the synthesis of acyclic molecules and saturated heterocycles has been tremendous, its synthetic utility toward chiral benzo-annulated heterocycles is relatively limited. Thus, in the search for wider applications of Sharpless asymmetric dihydroxylation-derived diols for the synthesis of benzo-annulated heterocycles, we report herein our studies in the asymmetric synthesis of (R)-1-((R)-6-fluorochroman-2-yl)ethane-1,2-diol, (R)-1-((S)-6-fluorochroman-2-yl)ethane-1,2-diol and (S)-6-fluoro-2-((R)-oxiran-2-yl)chroman, which have been used as late-stage intermediates for the asymmetric synthesis of the antihypertensive drug (S,R,R,R)-nebivolol. Noteworthy is that a large number of racemic and asymmetric syntheses of nebivolol and their intermediates have been described in the literature, however, the Sharpless asymmetric dihydroxylation has never been employed as the sole source of chirality for this purpose