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Vehicular Ad Hoc Network (VANET) is a key component in the Intelligent Transportation System (ITS) with a number of applications for safety, traffic management, emergency services, entertainment, and so on. These applications are implemented by exchanging data among the nodes in an open, dynamic, and distributed fashion, and hence VANETs are vulnerable to different network attacks. For examples, DoS and black-hole attacks can be easily executed in VANETs, and strongly affect the routing protocol and its functionality. Through the nature of VANETs, trust management is considered one of the practical means to secure these networks. In this paper, we propose an up-to-date dynamic entity-centric trust model for VANETs, called T-AODV. We use social science techniques to apply weight and fuzzy logic theory and identify the malicious nodes. Our NS2 simulation results indicate that T-AODV can be more resists in contact with black-hole attacks by boosting the security of AODV routing protocol. T-AODV slightly increases the routing overhead of AODV and provides better performance than the existing I-AODV scheme. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of network selection in dense heterogeneous cellular networks, where multiple base stations (BSs) are available to meet the demand for wireless data. The selection of the most appropriate BS for each user equipment (UE) is a complex task, taking into account factors such as signal strength, interference, and available resources. To solve this problem, we propose a distributed algorithm based on game theory that optimizes network selection by considering the physical rate of UEs towards various BSs. The algorithm clusters UEs based on their physical rate and formulates the network selection problem as a convex optimization problem. We propose a distributed algorithm based on game theory that can reach optimal solution and speeds up convergence by simultaneously changing the BS for a set of UEs belonging to the same cluster. Simulation results are used to verify the performance of the proposed algorithm and explore the convergence speed. Specifically, in our simulations, the Modified BIR algorithm achieves convergence almost two times faster than the BIR algorithm, while the cluster-based BIR algorithm converges around 10 times faster than the original BIR algorithm. These findings highlight the significant improvement in network selection performance achieved by our proposed algorithms. [ABSTRACT FROM AUTHOR]

Simultaneous wireless information power transfer with power splitting is a new technology for energy harvesting that splits the received signal into two streams with adjustable power levels for information decoding and energy saving. Traditionally, decode and forward (DF) and amplify and forward (AF) schemes are used for energy harvesting in three‐step two‐way relay networks (TWRNs). In this paper, piece‐wise and forward (PF) scheme are applied with power splitting for energy harvesting in TWRNs. In PF, the received signal from each source at relay is compared to an adaptive threshold, if the signal strength is above the threshold, the relay functions similar to DF scheme, otherwise, the relay transmits a particular combination of its received signals from the sources. Next, the outage performance of PF protocol in a three‐step TWRN is studied and optimal lossless energy saving (OLES) method are presented to minimise the outage probability by computing the optimum power splitting ratio. The simulation and analytical results indicate that the outage probability of PF can be significantly improved using OLES technique in comparison with other related relaying schemes. The results show that the outage probability of PF‐OLES is 13, 3, and 5dB$5\nobreakspace \text{dB}$ lower than AF‐OLES, DF‐OLES, and DAPS [1], respectively. [ABSTRACT FROM AUTHOR]

In this paper, we study joint dual relay- selection (RS) and physical network coding (PNC) schemes for wireless two-way relay channels. We propose four schemes in which the sources transmit information to the relays and two "best" relays are selected based on minimum bit-error-rate (BER) criterion. Then, the selected relays combine the received information from sources and broadcast it towards each other. The BER of the proposed schemes are obtained analytically and also verified through Monte Carlo simulations. The results indicate that the schemes have superior performance compared to an existing work which uses Alamouti space-time block codes (STBC). [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Network selection in heterogeneous dense networks based on user clustering" published in the journal Wireless Networks. The correction addresses an error in the online and PDF versions of the article, specifically in Section 6.1 regarding the uniqueness of Nash equilibrium. The corrected version of the equilibrium is provided in the notice. The correction has been made by the authors Alireza Ahadipour and Alireza Keshavarz-Haddad. Springer Nature, the publisher, remains neutral in terms of jurisdictional claims and institutional affiliations. [Extracted from the article]

Network coding and relay selection have attracted significant attention due to their performance improvement and spectral efficiency in wireless networks. In this work, we study joint relay selection and network coding cooperation schemes for M source-destination pairs assisted with N relays. We propose a new smart decode-and-forward max-min relay selection scheme based on the source-destination links' outage status and L selected relays to enhance the communication system diversity. Our objective is realize joint network coding and relay selection strategies for maximizing the expected number of recovered packets by the intended destinations in various situations. We analyze the performance of the proposed scheme and prove that the maximum diversity order of N + 1 is achieved when the number of active relays is at least ⌈ N + 1 3 ⌉ . Also, we show that the scheme can achieve a diversity order of 3L when L < ⌈ N + 1 3 ⌉ . Our analytical and simulation results indicate that the proposed scheme provides higher performance than the existing network coded cooperation schemes. [ABSTRACT FROM AUTHOR]

Physical layer network coding can significantly increase the throughput of two-way relay networks. However, fading phenomenon usually causes great asymmetry between two multiple access channels which can drastically degrade the performance of PNC protocol. To handle this issue, we propose an alternative detection method to improve the detection of physical layer network coded signal in multi-relay networks. First, we introduce single node detection to extract a single data from superimposed signal in the multiple access phase of physical layer network coding protocol. Then, we propose a relay selection method based on single node detection (RS-SND) and compare it to conventional relay selection method based on physical network coding (RS-PNC) in terms of average bit error rate for detection of XOR-ed data of the two source nodes. Closed-form expressions are derived for average BER of the proposed scheme and its asymptotic approximation at high signal to noise ratio. It is shown that RS-SND outperforms RS-PNC in Rayleigh fading channels when more than two relays are employed. Finally, we propose a relay selection-opportunistic physical layer network coding (RS-OPNC) method by dynamically selecting between RS-SND and RS-PNC schemes based on channel state information. Simulation results verify that RS-OPNC offers considerable SNR gain over conventional RS-PNC method. [ABSTRACT FROM AUTHOR]

Metamorphic malware is a kind of malware which evades signature-based anti-viruses by changing its internal structure in each infection. This paper, firstly, introduces a new measure of distance between two computer programs called program dissimilarity measure based on entropy (PDME). Then, it suggests a measure for the degree of metamorphism, based on the suggested distance measure. The distance measure is defined based on the Entropy of the two malware programs. Moreover, the paper shows that the distance measure can be used for classifying metamorphic malware via K-Nearest Neighbors (KNN) method. The method is evaluated by four metamorphic malware families. The results demonstrate that the measure can indicate the degree of metamorphism efficiently, and the KNN classification method using PDME can classify the metamorphic malware with a high precision. [ABSTRACT FROM AUTHOR]

Bounds on the capacity of wireless networks often rely on simplifying assumptions and are given in terms of coarse network parameters, such as the number of nodes. While useful due to their simplicity, such bounds can significantly overestimate the achievable capacity in real-world situations, ignoring actual network topology and traffic patterns. The results of this paper improve such analytical results on network capacity in several ways. At the heart of our methodology lies the concept of transmission arenas, which indicates the presence of active transmissions near any given location in the network. This novel space-based approach is well-suited to untangle the interactions of simultaneous transmissions. Avoiding a graph-based model of the network, it opens new avenues of studying capacities. For homogeneous networks, we recover classical bounds. However, our methodology applies to arbitrary networks and can, thus, inform placing and activating of nodes also in the presence of clustering. Our method works with all classical channel models and dimensions. It provides bounds on the transport capacity which involve only high-level knowledge of node locations, such as the length of Euclidean minimum spanning tree. As an additional novelty, we establish bounds on wireless unicast and multicast capacities. [ABSTRACT FROM PUBLISHER]

We study the dynamics of network selection in heterogeneous wireless networks based on client-side control. Clients in such networks selfishly select the best radio access technology (RAT) that maximizes their own throughputs. We study two general classes of throughput models that capture the basic properties of random access (e.g., Wi-Fi) and scheduled access (e.g., WiMAX, LTE, and 3G) networks. Formulating the problem as a non-cooperative game, we study its existence of equilibria, convergence time, efficiency, and practicality. Our results reveal that: 1) single-class RAT selection games converge to Nash equilibria, while an improvement path can be repeated infinitely with a mixture of classes; 2) we provide tight bounds on the convergence time of these games; 3) we analyze the Pareto-efficiency of the Nash equilibria of these games, deriving the conditions under which Nash equilibria are Pareto-optimal, and quantifying the distance of equilibria with respect to the set of Pareto-dominant points when the conditions are not satisfied; and 4) with extensive measurement-driven simulations, we show that RAT selection games converge to Nash equilibria in a small number of steps, and are amenable to practical implementation. We also investigate the impact of noisy throughput estimates, and propose solutions to handle them. [ABSTRACT FROM PUBLISHER]

Communication security of wireless sensor networks is achieved using cryptographic keys assigned to the nodes. Due to resource constraints in such networks, random key pre-distribution schemes are of high interest. Although in most of these schemes no location information is considered, there are scenarios that location information can be obtained by nodes after their deployment. In this paper, we propose a novel probabilistic key pre-distribution scheme, for large-scale wireless sensor networks which utilizes location information in order to improve the performance of random key pre-distribution substantially. In order to apply the location information of the nodes in key distribution process, we partition the network into some regions and use graph coloring techniques to efficiently assign the random keys. The proposed scheme has a superior scalability by supporting larger number of nodes and also increasing the probability of existence of a shared exclusive key among the nearby nodes, i.e., the probability of having an isolated node is significantly reduced in comparison with the existing random key pre-distribution schemes. Our simulation results verify these terms. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) is an adaptive, intelligent radio technology that can automatically detects available channels in a wireless spectrum and change transmission parameters to allow more concurrent wireless communications in a given spectrum band at a location. Physical layer attack is a common attack in these networks which can degrade the performance of cognitive radio networks severely. In this attack, the attacker mimics the signals of the Primary Users (PU) to mislead the cognitive users about the existence of the primary users. Two physical layer attack approaches are studied in this paper. First, we have considered the case that the cognitive users are united against the attacker to maximize the network total throughput. Second, we have studied the case that the cognitive users are selfish but have a common attacker. In both cases, we have assumed that the cognitive network employs carrier sense multiple access with collision avoidance (CSMA/CA) to prevent collisions. We use the game theory approach to model the optimization problem and then try to solve it. Some simulations are conducted to evaluate the cognitive network performances. [ABSTRACT FROM AUTHOR]

In this paper, we explore fundamental limitations of the benefit of network coding in multihop wireless networks. We study two well-accepted scenarios in the field: single multicast session and multiple unicast sessions. We assume arbitrary but fixed topology and traffic patterns for the wireless network. We prove that the gain of network coding in terms of throughput and energy saving of a single multicast session is at most a constant factor. Also, we present a lower bound on the average number of transmissions of multiple unicast sessions under any arbitrary network coding. We identify scenarios under which network coding provides no gain at all, in the sense that there exists a simple flow scheme that achieves the same performance. Moreover, we prove that the gain of network coding in terms of the maximum transport capacity is bounded by a constant factor of at most $(\pi)$ in any arbitrary wireless network under all traditional Gaussian channel models. As a corollary, we find that the gain of network coding on the throughput of large homogeneous wireless networks is asymptotically bounded by a constant. Furthermore, we establish theorems which relate a network coding scheme to a simple routing scheme for multiple unicast sessions. The theorems can be used as criteria for evaluating the potential gain of network coding in a given wired or wireless network. Based on these criteria, we find more scenarios where network coding has no gain on throughput or energy saving. [ABSTRACT FROM AUTHOR]