Wireless networks have continued to evolve to offer connectivity between users and smart devices such as drones and wireless sensor nodes. In this environment, insecure public channels are deployed to link the users to their remote smart devices. Some of the application areas of these smart devices include military surveillance and healthcare monitoring. Since the data collected and transmitted to the users are highly sensitive and private, any leakages can have adverse effects. As such, strong entity authentication should be implemented before any access is granted in these wireless networks. Although numerous protocols have been developed for this purpose, the simultaneous attainment of robust security and privacy at low latencies, execution time and bandwidth remains a mirage. In this paper, a session-dependent token-based payload enciphering scheme for integrity enhancements in wireless networks is presented. This protocol amalgamates fuzzy extraction with extended Chebyshev chaotic maps to boost the integrity of the exchanged payload. The security analysis shows that this scheme offers entity anonymity and backward and forward key secrecy. In addition, it is demonstrated to be robust against secret ephemeral leakage, side-channeling, man-in-the-middle and impersonation attacks, among other security threats. From the performance perspective, the proposed scheme requires the least communication overheads and a relatively low execution time during the authentication process.
Highly sensitive information about people’s social life and daily activities flows in smart home networks. As such, if attackers can manage to capture or even eavesdrop on this information, the privacy of the users can be compromised. The consequences can be far-reaching, such as knowing the status of home occupancy that can then facilitate burglary. To address these challenges, approaches such as data aggregation and signcryption have been utilized. Elliptic curve cryptography, bilinear pairing, asymmetric key cryptosystem, blockchain, and exponential operations are among the most popular techniques deployed to design these security solutions. However, the computational, storage and communication complexities exhibited by the majority of these techniques are too high. This renders these techniques unsuitable for smart home components such as smart switches and sensors. Some of these schemes have centralized architectures, which present some single points of failure. In this paper, symmetric key authentication procedures are presented for smart home networks. The proposed protocol leverages on cryptographic primitives such as one-way hashing and bitwise exclusive-Or operations. The results indicate that this scheme incurs the lowest communication, storage, and computation costs compared to other related state-of-the-art techniques. Empirically, our protocol reduces the communication and computation complexities by 16.7% and 57.7%, respectively. In addition, it provides backward key secrecy, robust mutual authentication, anonymity, forward key secrecy, and unlinkability. Moreover, it can effectively prevent attacks such as impersonation, session hijacking, denial of service, packet replays, man-in-the-middle, and message eavesdropping.
Precision agriculture encompasses automation and application of a wide range of information technology devices to improve farm output. In this environment, smart devices collect and exchange a massive number of messages with other devices and servers over public channels. Consequently, smart farming is exposed to diverse attacks, which can have serious consequences since the sensed data are normally processed to help determine the agricultural field status and facilitate decision-making. Although a myriad of security schemes has been presented in the literature to curb these challenges, they either have poor performance or are susceptible to attacks. In this paper, an elliptic curve cryptography-based scheme is presented, which is shown to be formally secure under the Burrows–Abadi–Needham (BAN) logic. In addition, it is semantically demonstrated to offer user privacy, anonymity, unlinkability, untraceability, robust authentication, session key agreement, and key secrecy and does not require the deployment of verifier tables. In addition, it can withstand side-channeling, physical capture, eavesdropping, password guessing, spoofing, forgery, replay, session hijacking, impersonation, de-synchronization, man-in-the-middle, privileged insider, denial of service, stolen smart device, and known session-specific temporary information attacks. In terms of performance, the proposed protocol results in 14.67% and 18% reductions in computation and communication costs, respectively, and a 35.29% improvement in supported security features.
The full automated microfluidic system has been designed for the determination of zinc (II) ion in pharmaceutical samples home-made. Two-channel microchips (30 μl×4 cm) was designed in this study. The proposed system was controlled by using Arduino UNO and Mega microcontrollers. The first type was utilized to control the homemade micro-peristaltic pump to withdraw samples and chemical reagents in the microchip and then to the spectrophotometer equipment with 7-microliter flow cell. The other one type is Mega, was used as a data-logger to manipulate and recording the results as peak height corresponding the concentration by using Microsoft Excel 2016 program. The linearity was ranged 1-7 µg/ml, the correlation coefficient (R2) was 0.9998. The relative standard deviation for ten measurements of Zn(II) ion 4 µg/ml was (0.982%), as well as the detection limit was 0.125 µg/ml. The dilution factor of this system was 1.07.
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