In the evolving landscape of secure image transmission, safeguarding sensitive visual information against unauthorized access remains a critical challenge. This study introduces an innovative DNA-based encryption scheme that leverages the inherent randomness of SHA-256 hashing with mutation, and crossover operations to enhance the security of image encryption. The proposed method transforms image data into a DNA sequence, subsequently encrypted using a key derived from the SHA-256 hash function. This process ensures a robust, non-linear relationship between the original image and the encrypted output, making the encryption resistant to traditional cryptanalytic attacks. Modified results after crossover and other operations of the SHA-256 hash function can produce unique, fixed-length outputs from variable input sizes, introducing a high level of unpredictability and entropy, further securing the encrypted images. The encryption scheme was rigorously tested on various standard image datasets, demonstrating its effectiveness in maintaining image fidelity while providing a strong defense against unauthorized decryption attempts. This experiment underscores the potential of integrating DNA-based encryption with cryptographic hash functions to achieve a new security standard in image transmission.

In the exclusive-use model of spectrum trading , cognitive radio devices or secondary users can buy spectrum resources from licensed users or primary users for a short or long period of time. Considering such spectrum access, a trading model is introduced where a buyer can select a set of candidate sellers based on their reputation and their offers in fulfilling its requirements, namely, offered signal quality, contract duration, coverage and bandwidth. Similarly, a seller can assess a buyer as a potential trading partner considering the buyer’s reliability, which the seller can derive from the buyer’s reputation and financial profile. In our scheme, seller reputation or buyer reliability can be either obtained from a reputation brokerage service, if one exists, or calculated using our model. Since in a competitive market, the price of a seller depends on that of other sellers, game theory is used to model the competition among multiple sellers. An optimization technique is used by a buyer to select the best seller(s) and optimize purchase to maximize its utility. This may result in buying from multiple sellers of certain amount of bandwidth from each, depending on price and meeting requirements and budget constraints. Stability of the model is analyzed and performance evaluation shows that it benefits sellers and buyers in terms of profit and throughput, respectively.

Secondary service providers can buy spectrum resources from primary service providers for a short or long period of time and exploit it to solve the problem of spectrum scarcity. This buying decision of spectrum buyers can depend on several factors including pricing of the spectrum, reputation of a seller, and duration of the contract and spectrum quality. However, existing pricing models for dynamic spectrum access consider mainly bandwidth which makes them unsuitable for real-world trading. In this paper, we consider these issues related to the pricing of spectrum sale in terms of microeconomic theories. First, we consider reputation of spectrum sellers and update it dynamically by considering a buyer's own trading experience with the sellers and collecting recommendations on sellers from other buyers. Second, trustworthiness of recommenders as well as incentive to encourage recommendations are modeled. Third, contract duration and spectrum quality are incorporated such that a buyer's utility is formulated as a function of buyer's resource requirement, reputation of seller and trustworthiness of recommenders. Fourth, the model is analyzed using dynamic pricing of the market and the solution is obtained using market equilibrium. Results demonstrate the superiority of our model over the existing microeconomic models for dynamic spectrum trading.

We develop a realistic pricing modeling for dynamic spectrum access network considering a number of factors that influence real world trading. Our model incorporates the reputation of sellers, incentive mechanism to attract buyers, timing requirement of the contract, signal quality along with bandwidth size and price of the spectrum resources. Reputation information is accumulated from self experience and/or from the recommendations of other users. Trustworthiness of the recommending SUs is also modeled in this paper. An incentive mechanism is applied to encourage in dissemination of recommendations and to attract the buyers by providing discounts. A utility function for the spectrum trading is modeled such that a buyer can trade with the seller which maximizes its utility based on the above factors and the pricing solution is obtained using the market equilibrium model. The performance of the proposed model is evaluated using simulation results which show that our model benefits both the sellers and the buyers in terms of profit and throughput, respectively.

Spectrum resources are becoming more and more congested as the number of wireless devices are increasing and becoming ubiquitous. Cognitive radios or secondary users (SUs) can provide the solution for better spectrum availability, bandwidth and economic aspects for both the primary service providers and the SUs. We propose a pricing model for spectrum sharing in a single level market where the primary service providers can trade spectrum with the secondary service providers. The proposed pricing model incorporates the reliability of the primary service providers and allowable coverage area, quality of the signal along with the pricing and spectrum bandwidth availability. An iterative distributed algorithm is used to reach the market equilibrium so that both the primary and the secondary service providers are satisfied with the allocated spectrum bandwidth and negotiated price. The performance of the proposed model is demonstrated using extensive numerical results with the stability analysis in reaching the market equilibrium.

Spectrum utilization in cognitive radio ad hoc network is a critical task due to the fluctuation of spectrum availability temporally and spatially. Reusing the same channel spatially can effectively improve the spectrum utilization as well as reduce the delay in switching and coordination in different channels. In this paper, a dynamic spectrum sharing method is proposed which allows multiple secondary users to reside in the same channel and use the channel concurrently to maximize the spectrum utilization exploiting variable transmission power and location information, while guaranteeing acceptable level of interference protection to the primary users. Results show that the proposed method successfully outperforms the existing method in maximizing the number of concurrent transmissions as well as the spectrum utilization.