Cognitive Radio Networks (CRNs) present a promising solution to overcome the spectrum scarcity problem by allowing dynamic and opportunistic access to unused licensed bands by unlicensed (secondary) users. One of the core features of this technology is its ability to share the scarce spectrum resource among primary (licensed) and secondary users. In this context, multiple spectrum sharing models have evolved, however, auction theory has gained significant attention due to its fair, effective and incentive-compatible resource allocation. This paper provides a detailed survey of auction-based spectrum sharing mechanisms deployed in CRNs, with a specific focus on single-sided and double-sided auction models. In single-sided auction, only bidders participate competing for the auctioned items. Whereas in double-sided auction, both bidders and sellers are involved in the auction game. The paper begins with a brief overview on auction theory and its relevance to spectrum sharing, analyzing various auction designs based on key economic properties. Further, spectrum allocation encompasses different allocation strategies, namely Single-Channel Single-Winner (SCSW) allocation, Single-Channel Multi-Winner (SCMW) allocation, and Multi-Channel Multi-Winner (MCMW) allocation. This survey highlights how extensively single auction and double auction have been deployed in these allocation strategies to provide effective and fair spectrum distribution among secondary users. Finally, the survey outlines practical challenges and open research directions associated with the existing auction-based models with respect to CRN deployment, and focuses on the need to adapt these models to CR constraints for their real-time execution in next-generation cognitive radio networks.

Cognitive Radio Networks (CRNs) play a vital role in enabling dynamic spectrum sharing, effectively addressing the challenges of wireless spectrum scarcity. Cognitive Radio Sensor Networks (CRSNs), consisting of Cognitive Radio (CR) devices, optimize spectrum allocation to enhance the deployment of sensor-based devices. However, security vulnerabilities in CRSNs create opportunities for attackers to exploit, leading to malicious activities that degrade overall performance. Therefore, it is crucial to detect and mitigate these vulnerabilities to maintain and enhance the network performance. Identifying malicious nodes that exhibit low levels of malicious activity is particularly challenging. This work addresses selective forwarding and ON-OFF attacks, where the ON-OFF attack exhibits selective forwarding behavior during its ON phase. To address this issue, a trust mechanism is proposed that incorporates both direct and indirect (recommendation-based) trust evaluations. In direct trust evaluation, a technique is developed to calculate the behavioral expectancy factor by analyzing the difference between the actual and expected data packet forwarding rates. Whereas, for indirect trust evaluation, a filtering technique is introduced to discard malicious recommendations from badmouthing attackers. Finally, the simulation results demonstrate that the proposed approach outperforms the existing method in terms of detection ratio, detection efficiency, relative average packet delivery ratio, and relative average packet drop ratio.

Due to the scarcity of wireless spectrum, it entails the utilization of dynamic shared spectrum solutions, which can be availed with an intelligent wireless communication technology called Cognitive Radio (CR).Wireless sensor nodes equipped with CR reconfigure dynamically to utilize the vacant spectrum holes, forming a Cognitive Radio Sensor Network (CRSN), which has high demand in Internet of Things (IoT) applications. Despite of attaining high spectrum utilization via CR capabilities, CR based sensor networks require energy efficient solutions due to their resource-constrained behavior. Therefore, a clustered architecture becomes suitable for maintaining opportunistically available radio resources and energy efficiency in CRSNs. In this paper, a trust-based secure clustering scheme is introduced for routing in CRSNs, where both direct and indirect/recommended trust are considered, along with an aging method for updating trust. This scheme accumulates the history of trust values to detect and eliminate malicious nodes from the network. Additionally, during cluster formation, two parameters weight value and neighbor set of each node are taken into consideration. These parameters are obtained through the suggested neighbor selection scheme. The neighbor selection approach considers the neighbor’s requirements in terms of transmission time and the availability of a common channel between the Cognitive Sensor (CS) node and the associated neighbor set. Thereafter, the proposed secure clustering approach will incorporate cluster head rotation to ensure an even distribution of energy consumption among the nodes in a cluster. Simulation based study demonstrates that the proposed scheme enhances detection efficiency, detection ratio, the network’s relative average packet delivery ratio, relative average packet drop ratio, average end-to-end delay, and average energy consumption of the network for selective forwarding, blackhole, and ON-OFF attacks in comparison with an existing method. Moreover, the correctness of the proposed scheme is evaluated in terms of precision and F1-Score.

Cognitive Radio (CR) is an advanced wireless communication technology that intelligently senses its operating environment to identify available licensed spectrum gaps and adaptively operate on these vacant bands, thereby enhancing spectrum utilization efficiently. Allocation of these free bands to unlicensed users is becoming an inherent necessity in order to overcome the issue of adequate spectrum while satisfying their requisite spectrum demands. Hence, with an intent of enhancing radio spectrum usage, this paper proposes a channel allocation method which carries out single-sided auction in CR networks. Channels are sold out at appropriate prices using the single-sided auction to achieve finer spectrum use, along with reuse of the unused spectrum amongst non-interfering users. Further, with the CR limitations, multi-channel allocation can relevantly improve the channel utilization by performing multiple auction rounds with regard to channel availability time. Rate of data transfer over the heterogeneous nature of channels specifies the bidding language. Reuse of idle bands is provided through a group formation approach following which winning bidders decide their payments. Finally, theoretical analysis and simulation results demonstrate the improvements in performance of the proposed model.

The scarcity of wireless spectrum resources demands dynamic shared spectrum allocation solutions through Cognitive Radio Networks (CRNs). These networks, comprising Cognitive Radio (CR) devices, facilitate the widespread adoption of sensorbased devices via Cognitive Radio Sensor Networks (CRSNs). In these networks, the presence of attackers degrade network throughput. Therefore, detecting and eliminating these threats is crucial for maintaining optimal network performance. Moreover, identifying attackers exhibiting low levels of malicious behavior, such as ON-OFF attackers with selective forwarding behavior, can be challenging. With these considerations, this paper proposes an efficient trust mechanism for CRSNs that incorporates both direct trust and recommendation-based trust formulations. To determine the packet forwarding rate (PFR), the direct trust calculation utilizes a fuzzy model. It also incorporates a parameter called the expected behavior factor, which accounts for the differences between the expected and actual PFR. Additionally, a trust updating scheme is proposed that assigns greater weight to recent trust values, while ensuring that a node’s trust value does not increase too rapidly. Experimental simulations show that the proposed scheme achieves a higher detection ratio and a better average packet delivery ratio compared to the existing Beta and Link quality based Trust Model (BLTM). Furthermore, our scheme more rapidly decreases the trust value in response to malicious activity by attackers than the BLTM.

Credit card fraud remains a persistent challenge in the realm of financial security, necessitating innovative approaches for detection. This paper presents a comprehensive investigation into credit card fraud detection, focusing on integrating rule-based systems and machine learning methods to enhance accuracy and efficiency. The methodology encompasses data collection from a reputable source, thorough preprocessing, model development, and online execution. Performance evaluation employs a diverse array of metrics, including precision, recall, F1 score, accuracy, confusion matrix, false positive rate, learning curve, precision-recall curve, cumulative gains curve, and ROC curve. Results demonstrate a balanced trade-off between precision and recall, essential for effective fraud detection. Detailed discussions interpret these findings, offering valuable insights and avenues for future research. This research contributes to advancing fraud detection methodologies and holds promise for enhancing financial transaction security

In order to alleviate imbalances in radio spectrum usage, cognitive radio (CR) is designed as a dominant solution, which constantly senses the spectrum for free bands and opportunistically utilizes those bands to improve spectrum utilization. One of the essential functionalities of this emerging technology is to efficiently allocate licensed unused channels amongst Secondary Users (SUs). With this initiative, this paper deploys an auction theoretical model to provide transparent resource allocation. Auction offers a market-based mechanism where an auctioneer (primary owner) fairly leases its free channels to desirable buyers (SUs). In this paper, we propose a single-sided sealed-bid multi-unit auction mechanism for CR networks (CRNs) which sells temporarily available heterogeneous channels amongst SUs at suitable rates. Differences in channel availability time and dynamics in spectrum opportunities decide bid collection from SUs while reducing the possibility of disruption during SUs' transmission using the allocated channels. Multiple auction rounds with concurrent bidding allows the mechanism to make utmost use of the scarce radio resource. The proposed model derives a winner determination algorithm and a payment rule to select the winning bidders and their respective expenses. Additionally, we provide the proofs of truthfulness and individual rationality to obtain an economically robust auction. Simulation based results indicate performance improvements in the proposed model in terms of spectrum utilization, auctioneer's revenue, utility per buyer, user satisfaction compared to a similar approach from literature.

Cognitive radio (CR) is a novel intelligent technology which enables opportunistic access to temporarily unused licensed frequency bands. A key functionality of CR is to distribute free channels efficiently amongst Secondary Users (SUs) boosting spectrum usage to assist the escalating wireless applications world wide. In this context, this paper introduces a channel allocation mechanism which enables SUs (CR enabled unlicensed users) to dynamically access unused spectrum bands to fulfill their spectrum needs. We model the channel allocation problem as a sealed-bid single-sided auction which primarily aims at maximizing the overall spectrum utilization. Market based spectrum auctions in CR networks motivate licensed users to participate and lease their under utilized radio resources to gain monetary benefits. Sequential bidding is applied to this model for auctioning homogeneous channels, which reduces communication overhead. Bid submission takes into account two major CR constraints, namely, dynamics in spectrum opportunities and differences in channel availability time, which on incorporation provide disruption free data transmission to the SUs. We reduce resource wastage in this model by performing multiple auction rounds. Application of second price auction determines winning bidders and their respective payments to auctioneer. The design of our auction mechanism is supported with the proofs of truthfulness and individually rational properties. Furthermore, experimental results indicate that our model outperforms an existing auction method. Spectrum utilization values show 22 to 75% improvement in our model with changing number of SUs, and 23 to 93% improvement in our model with changing number of channels.

Cognitive Radio (CR) is an advanced technology, which intends to boost the radio spectrum utilization. On perceiving the spectrum holes, next there is a need to provide a fair distribution of the vacant licensed channels amongst Secondary Users (SUs) during the spectrum allocation process. In this context, our paper introduces two allocation models to resolve the spectrum allocation problem. Initially, we design a simple centralized model to assign the channels. Then, we extend it to a centralized fair allocation model that aims to impart a better utilization of the free channels. Both approaches assign a common channel to a group of non-interfering SUs simultaneously. This facilitates spectrum reuse. The constraint related to dynamics in spectrum opportunities in CR is handled during channel allocation. Simulation study analyzes the proposed approaches with an existing allocation mechanism and reveals the performance improvement of centralized fair allocation model in terms of spectrum utilization.

Opportunistic availability of licensed frequency bands enables the secondary users (SUs) to avail the radio spectrum dynamically. Cognitive radio (CR) paradigm extends the dynamic spectrum access techniques to sense for free channels (called spectrum holes) which can be efficiently redistributed amongst SUs. Motivated by the adaptive technology in CR, this paper introduces a sealed-bid double auction mechanism which aims to obtain an effective allocation of the unused radio spectrum. The proposed auction model adopts multi-channel allocation where one SU can access more than one available channel, while imposing the constraints for dynamics in spectrum opportunities and varying channel availability time amongst SUs. Previously designed double auctions miss out the CR constraints which can further degrade the network performance. Also, multi-winner allocation is induced in the model which encourages spectrum reuse by allowing a common channel to be assigned to multiple non-interfering SUs. A preference list of channels is maintained at each SU using which SUs offer their bid values for the heterogeneous channels which the primary owners are competing to lease. To organize channel specific groups of non-interfering SUs, a bidder group formation algorithm is developed such that members of a winner group get access to a common channel. The auctioneer formulates a winner determination strategy and a pricing strategy which achieves truthfulness while assigning the idle spectrum. Effectiveness of the proposed model is studied by comparing it with an existing work which shows that channel allocation gets significantly improved on deploying the proposed model.

Cognitive Radio (CR) empowers unlicensed users to opportunistically utilize free licensed bands. Spectrum allocation is one of the salient features in CR which provides efficient redistribution of unused channels amongst preferable secondary users (SUs). This paper proposes an auction-based spectrum allocation mechanism which aims to achieve an improved spectrum utilization. The proposed model applies a single-sided sealed bid auction which accepts simultaneous bid submission from SUs for dynamically available channels. Channels are heterogeneous with respect to their bandwidth, and CR constraints are incorporated to proffer network performance. Winner determination algorithm is designed to choose winning bidders which along with assures truthfulness in the model. Experimental results validate our proposed mechanism by comparing it with Vickrey Clarke Groves (VCG) auction.

Cognitive radio (CR) has evolved as a novel technology for overcoming the spectrum-scarcity problem in wireless communication networks. With its opportunistic behaviour for improving the spectrum-usage efficiency, CR enables the desired secondary users (SUs) to dynamically utilize the idle spectrum owned by primary users. On sensing the spectrum to identify the idle frequency bands, proper spectrum-allocation mechanisms need to be designed to provide an effectual use of the radio resource. In this paper, we propose a single-sided sealed-bid sequential-bidding-based auction framework that extends the channel-reuse property in a spectrum-allocation mechanism to efficiently redistribute the unused channels. Existing auction designs primarily aim at maximizing the auctioneer's revenue, due to which certain CR constraints remain excluded in their models. We address two such constraints, viz. the dynamics in spectrum opportunities and varying availability time of vacant channels, and formulate an allocation problem that maximizes the utilization of the radio spectrum. The auctioneer strategises winner determination based on bids collected from SUs and sequentially leases the unused channels, while restricting the channel assignment to a single-channel-multi-user allocation. To model the spectrum-sharing mechanism, we initially developed a group-formation algorithm that enables the members of a group to access a common channel. Furthermore, the spectrum-allocation and pricing algorithms are operated under constrained circumstances, which guarantees truthfulness in the model. An analysis of the simulation results and comparison with existing auction models revealed the effectiveness of the proposed approach in assigning the unexploited spectrum.

Cognitive Radio (CR) is a novel technology which empowers the unlicensed users to opportunistically avail the free channels left unoccupied by the licensed owners. This apparently resolves the spectrum scarcity problem arising in today’s telecommunication industry. In this technology, once the free bands (called spectrum holes) are detected using sensing techniques, next there is a need to efficiently redistribute the idle spectrum. Such an allocation process of CR has attracted several researchers across the world to contribute in this domain. With an initiative to analyze the functionality of spectrum allocation, this paper carries out a survey on the allocation mechanisms which have been applied to use the spectrum holes. We primarily focus our exploration on auction theoretic allocation models due to their efficacy in channel allocation. Auction formulation takes the unlicensed users as bidders where they bid for the spectrum holes as the auctioned item. Winner determination strategy and pricing strategy are two important aspects of an auction model which determines a fair allocation pattern and along with decides the monetary benefit of sellers and auctioneer. We go through a detailed study on single-sided auction and double-sided auction which are deployed with different CR network constraints to design the allocation model. Finally, we conclude the paper by underlining some future research directions in this area.

Fair allocation of unused licensed spectrum among preferable secondary users (SUs) is an important feature to be supported by Cognitive Radio (CR) for its successful deployment. This paper proposes an auction theoretic model for spectrum allocation by incorporating different constraints of a CR network and intents to achieve an effective utilization of the radio spectrum. We consider heterogeneous channel condition which allows SUs to express their preference of channels in terms of bid values. A sealed-bid concurrent bidding policy is implemented which collects bids from SUs while dealing with variation in availability time of the auctioned channels. The proposed model develops a truthful winner determination algorithm which exploits spectrum reusability as well as restraints to dynamics in spectrum opportunities amongst SUs. Allowing multiple non-interfering SUs to utilize a common channel significantly helps to achieve an improved spectrum utility. However, every SU acquires at most one channel. The proposed model also develops a pricing algorithm which helps the auctioneer to earn a revenue from every wining bidder. Simulation based results demonstrate the effectiveness in performance of the proposed model in terms of spectrum utilization compared to the general concurrent auction model.

Under-utilization of wireless spectrum by the licensed owners creates spectrum holes which can be opportunistically exploited by secondary users (SUs). By incorporating dynamic spectrum access techniques, Cognitive Radio (CR) emerges as a novel technology which facilitates redistribution of the spectrum holes dynamically. In this context, this paper proposes a double auction framework for CR networks which addresses the channel allocation problem to boost the spectrum utilization efficiency. Multi-winner allocation relates to the condition where a common channel can be utilized by multiple non-interfering SUs which induces spectrum reuse. However, a single SU obtains at most one channel. To avoid disturbances during data transmission, availability time of a channel plays a key role. In this paper, bid submission from SUs rely on channel availability time, and to lease the idle channels, licensed users specify certain ask values. The proposed double auction mechanism develops winner determination and pricing strategies which are proved to be truthful and significantly improves the usage of the radio spectrum. Network simulations validate the improved performance of the proposed auction model compared to the McAfee auction.

Spectrum sharing is a key functionality of cognitive radio network (CRN) that features a fair distribution of vacant licensed channels among secondary users. This paper proposes a spectrum allocation scheme for CRN that takes into account different spectrum opportunities to be allocated to the secondary users while improving the spectrum utilization. A central entity is made responsible for deciding upon the channel assignment strategies. Moreover, channels are shared one after another in a sequential fashion such that a channel gets allotted to only one user at a time, and also a user can use at most one channel at a time. Simulation study reveals the performance improvement of the proposed scheme as compared to a random allocation strategy in terms of spectrum utilization efficiency.

With its opportunistic nature to exploit the unused licensed bands, cognitive radio (CR) presents itself as an advancing technology that senses for spectrum holes and distributes them rightly among secondary users. This paper proposes a spectrum assignment approach for CR networks that looks to provide a proper sharing of the available channels such that spectrum utilization is improved. While incorporating a concurrent strategy for channel allocation, the model constraints to the allocation limitation stating that one channel can be allotted to only one user at a time, and also one secondary user can gain access to at most one channel at a time. Further, simulation results of the proposed model show its effectiveness in terms of spectrum utilization efficiency.

Cognitive radio (CR) proffers a paradigm to improve spectrum utilization efficiency by assigning vacant licensed bands among unlicensed users. With different functionalities incorporating the CR system, spectrum sharing is one such key functionality that allows an efficient allocation of the spectrum resource. This paper concentrates on the concern related to spectrum sharing in cognitive radio networks (CRN) such that radio frequency can have an effective usage among licensed and unlicensed users. The paper formulates an auction-based spectrum allocation mechanism where bids for available bands are collected from secondary users and the primary owner decides upon the channel allocation while being restricted to single-unit-single-user allocation constraint and avoiding any harmful interference. A sequential bidding policy is deployed during the game that incorporates the winner determination and pricing strategies. Simulation results for the proposed approach unveil its effectiveness in allocating unused spectrum bands.

Cooperative spectrum sensing has been proven to improve sensing performance of cognitive users in presence of spectral diversity. For multi-channel CRN (MC-CRN), designing a cooperative spectrum sensing scheme becomes quite challenging as it needs an optimal sensing scheduling scheme, which schedules cognitive users to different channels such that a good balance between detection performance and the discovery of spectrum holes is achieved. The main issue associated with cooperative spectrum sensing scheduling (CSSS) scheme is the design of an optimal schedule that could specify which SUs should be assigned to which channels at what time to achieve maximal network throughput with minimal amount of energy and satisfying the desirable sensing accuracy. In this regard, designing an efficient CSSS scheme for MC-CRN is of utmost importance for practical implementation of CRN. In this article, we explore CSSS problem from a broad perspective and present the different objectives and the inherent issues and challenges arise in designing the CSSS scheme. We also discuss the different methods used for modeling of the CSSS scheme for MC-CRN. Further, a few future research directions are listed which need investigation while developing the solution for CSSS problem.