Abstract

The widespread use of mobile devices, sensors, and wireless sensor networks and the progressive development of the Internet of Things (IoT) has motivated medical and health-care societies to employ IoT to monitor, collect data, and communicate with patients using the wireless body area networks (WBANs). The collected data will make a lot of medical diagnosis applications of WBANs, which are obtained directly from the patients’ bodies. Therefore, because of the nature of wireless networks and freely accessible data feature over the public channel, the security and privacy of WBANs is the most critical concern for those who use it for health-care purposes. Accordingly, there is a need for an authentication scheme for letting a trusted user such as doctors or clinical personnel access to the sensor’s data from patients. In this paper, we propose a new lightweight hash-chain-based and forward secure authentication scheme for wireless body area networks in health-care IoT. Our scheme is secure against various known attacks obliged for WBANs. Additionally, we perform the formal security analysis using Real-or Random (ROR) model, and informal security on the proposed scheme, also, security verification of our scheme is validated by the ProVerif tool. Besides, our scheme is simulated by the OPNET network simulator and compared with several new schemes in terms of security and performance requirements. The simulation results and comparisons confirm that the proposed scheme is suitable for WBANs, and it supports more security features compared to related schemes.

Abstract

The Internet of Thing (IoT) is useful for connecting and collecting variable data of objects through the Internet, which makes to generate useful data for humanity. An indispensable enabler of IoT is the wireless sensor networks (WSNs). Many environments, such as smart healthcare, smart transportation and smart grid, have adopted WSN. Nonetheless, WSNs remain vulnerable to variety of attacks because they send and receive data over public channels. Moreover, the performance of IoT enabled sensor devices has limitations since the sensors are lightweight devices and are resource constrained. To overcome these problems, many security authentication protocols for WSNs have been proposed. However, many researchers have pointed out that preventing smartcard stolen and off-line guessing attacks is an important security issue, and guessing identity and password at the same time is still possible. To address these weaknesses, this paper presents a secure and efficient authentication protocol based on three-factor authentication by taking advantage of biometrics. Meanwhile, the proposed protocol uses a honey_list technique to protect against brute force and stolen smartcard attacks. By using the honey_list technique and three factors, the proposed protocol can provide security even if two of the three factors are compromised. Considering the limited performance of the sensors, we propose an efficient protocol using only hash functions excluding the public key based elliptic curve cryptography. For security evaluation of the proposed authentication protocol, we perform informal security analysis, and Real-Or-Random (ROR) model-based and Burrows Abadi Needham (BAN) logic based formal security analysis. We also perform the formal verification using the widely-used Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation software. Besides, compared to previous researches, we demonstrate that our proposed authentication protocol for WSNs systems is more suitable and secure than others.

Abstract

With advancements in engineering and science, the application dimensions of Cyber–Physical System (CPS) are increasing due to their improving efficiency, safety, reliability, usability and autonomy. By providing on-demand access to shared processing resources, cloud computing reduces infrastructure costs. Ensuring quality of service and information privacy and security is important in such environments. In this paper, we design a new authentication scheme related to the cloud-assisted CPS in two directions: (1) authentication between a user and a cloud server, and (2) authentication between a smart meter and a cloud server. In the former situation, any external party (user) can access the information stored in a cloud server provided that the user is legal and has the right to access information. In the later situation, a smart meter and a cloud server authentication is needed for secure communication of data stored in the cloud server. In both cases, both entities first mutually authenticate each other and only after successful authentication with the help of a trusted authority, establish a session key for their future secure communication. The proposed scheme deals with both the cases and provides high security as compared to other related works, which is shown through formal and informal security analysis. In addition, the mutual authentication using the widely-accepted Burrows–Abadi–Needham logic (BAN logic) and also formal security verification using the broadly-used Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool demonstrate further that the scheme is strong in security. Finally, the proposed scheme is shown to be efficient in terms of communication and computation costs as compared to those for other related existing schemes.

Abstract

We propose the notion of quantum coherence for superpositions over states which are not necessarily mutually orthogonal. This anticipatedly leads to a resource theory of non-orthogonal coherence. We characterize free states and free operations in this theory, and connect the latter with free operations in the resource theory of quantum coherence for orthogonal bases. We show that the concept of non-orthogonal coherence naturally furnishes us with a wave-particle duality in quantum double-slit experiments where the channels beyond the slits are leaky between them. Furthermore, we demonstrate existence of a unique maximally coherent qubit state corresponding to any given purity. In addition, and in contradistinction with the case of orthogonal bases, there appears a non-trivial minimally coherent qubit state for a given purity. We also study the behavior of quantum coherence for some typical configurations of …

Abstract

We present a formalism for detection of non-Markovianity (NM) through uncertainty relations. We show that when there is an information back-flow to the system from its environment through CP-divisibility breaking, the Choi-states corresponding to the reduced system evolution contain at least one negative eigenvalue. The consequent break down of uncertainty relations for such states can be used to witness non-Markovian dynamics. We present some relevant examples of the phenomenon for qubit channels. We further prove that square of the variance of a suitable Hermitian operator can act as a non-linear witness of NM. We finally show that NM is necessary in order to decrease the uncertainty of the states undergoing unital dynamics for qubits. This provides another method of certifying NM.

Abstract

We establish a connection between non-Markovianity and negative entropy production rate for various classes of quantum operations. We analyse several aspects of unital and thermal operations in connection with resource theories of purity and thermodynamics. We fully characterize Lindblad operators corresponding to unital operations. We also characterize the Lindblad dynamics for a large class of thermal operations. We next generalize the definition of the entropy production rate for the non-equilibrium case to connect it with the rate of change of free energy of the system, and establish complementary relations between non-Markovianity and maximum loss of free energy. We naturally conclude that non-Markovianity in terms of divisibility breaking is a necessary resource for the backflow of other resources like purity or free energy under the corresponding allowed operations.

Abstract

This paper proposes the use of copula theory for cooperative spectrum sensing (CSS) of orthogonal frequency-division multiplexing (OFDM) based primary user (PU). A distributed detection model is assumed where secondary users (SUs) employ autocorrelation detectors (ADs) for the detection of a PU. In the presence of a PU, it is assumed that the observations across different SUs and subsequently the decision statistics are dependent. For the fusion of these dependent statistics, different copulas such as -copula, Gaussian, Clayton and Gumbel are employed. In the presence of dependence among decision statistics, significant improvement in detection performance is observed while using copula theory instead of the traditional assumption of independence. Simulation results are presented to show the superiority of copula-based spectrum sensing.

Abstract

Cross-tier interference management is one of the major challenges in heterogeneous cellular networks (HetNets). Though the network throughput increases due to a better area spectral efficiency of a HetNet, there is possibility that high interference will make few link capacities close to zero when users regard interference as noise (IAN). In this letter, successive interference cancellation (SIC) is used to cancel the cross-tier interference in a reverse time division duplexing (RTDD) scheme. We demonstrate that by opportunistic use of SIC, a minimum guarantee on the sum link capacity can be ensured for an RTDD HetNet. This minimum sum link capacity is later on proved to be the maximum that can be achieved by orthogonal resource allocation schemes. Through system-level simulations for random allocation, it is shown that the proposed scheme is better than using SIC and IAN alone. To further improve the overall system capacity, an optimization problem for selecting co-channel users is formulated, and the Hungarian algorithm is employed to solve it.

Abstract

Reducing the amount of wireless data transmissions in constrainedbattery-powered sensor nodes is an effective way of prolongingtheir lifetime. In this paper, we present a machine learning-baseddata transmission reduction scheme for application-specific IoTnetworks. Though many error thresholding-based data predictionschemes have been explored in the past, this is the first work toincorporate machine learning in constrained sensor nodes to reducedata transmissions. We also provide a generic overview and com-parison of five traditional supervised machine learning algorithmsin the context of offloading trained models to memory and computa-tionally constrained microcontrollers. The proposed data reductionscheme is validated on an occupancy estimation testbed deployed inour lab. Experimental results demonstrate 99.91% overall reductionin data transmissions while imparting similar performance and 18to 82 times lesser transmissions than Shewhart change detectionalgorithm.

Abstract

This paper analyzes the performance of low earth orbit (LEO) satellites based internet-of-things (IoT) network where each IoT node makes use of multiple satellites to communicate with the ground station (GS). In this work, we consider fixed and variable gain amplify-and-forward (AF) relaying protocol at each satellite where the received signal from each IoT node is amplified before transmitting to the terrestrial GS for data processing. To analyze the performance of this novel LEO satellites based direct access architecture, the closed-form expressions for outage probability are derived considering two combining schemes at the GS:(i) selection combining;(ii) maximal ratio combining. Further, to gain more insights for diversity order and coding gain, asymptotic outage probability analysis at high SNR for both schemes is also performed. Finally, simulation results are presented to validate the analytical results derived and also to develop several interesting insights into the system performance.