Narrow Results

In the development of the Internet of Things (IoT), the server layer handles data structures and algorithms, which can successfully solve the desert island problem of heterogeneous data, but it will occupy a large amount of server resources and cause system pressure. To address the additional computational burden, it is necessary to make full use of the computing power of the edge layer. Solving problems such as communication connections, data detection and channel reasoning between large-scale IoT terminal nodes in non-ideal environments is worthy of in-depth study. Traditional frequency offset compensation algorithms and clock synchronization technology can no longer be applied to large-scale IoT solution design. A technology that can accurately reason about frequency offset and increase data transmission rate is needed. For large-scale direct connection scenarios that consider frequency offset and data transmission rate, this paper considers that the equipment required by the IoT terminals sends downlink transmission data-related information to achieve signal coverage, combines the big data scenario of large-scale direct connection, and introduces the data transmission rate to build a homomorphic encryption transmission model for asynchronous data transmission in the IoT system. To reduce the impact of data transmission rate on reconstruction quality and performance, a method that combines asynchronous data transmission processing and channel inference prediction is constructed. An optimization scheme for multi-node detection and channel inference of Raft algorithm homomorphic encryption and convex optimization is designed. In the simulation test, the paper compares the detection bit error rate, channel inference quality and performance of the traditional Lasso algorithm and the OMP algorithm based on serial communication interference signal elimination. The experimental results show that the performance of the Raft algorithm proposed by the paper is better than the Lasso algorithm by 7.52% and the OMP algorithm by 10.64%, which has a greater technical advantage. Meanwhile, the innovative use of homomorphic encryption transmission method to asynchronously process big data information will promote the IoT and big data information processing, which can enable blockchain technology to play an important role in various types of IoT systems.

An AG-group is an algebraic structure that satisfies the left invertive law and includes its left identity and inverse elements. This framework is naturally suited for representing and manipulating various real-life applications in civil engineering, information engineering, artificial intelligence, and more. In this paper, we present the structural application of AG-groups in data encryption and in the rotational transformation of water molecules. Additionally, numerous authors have explored fuzzy set theory over AG-group systems, yielding many valuable results. Spherical fuzzy set theory, an extension of fuzzy set theory, allows for the representation of uncertainty in decision-making, where there may be multiple possible choices or uncertainty about the degree of membership of an element in a set. However, no prior work has combined spherical fuzzy set theory with AG-groups, which motivates our study. In this paper, we apply spherical fuzzy set theory to AG-groups and introduce the concept of spherical fuzzy AG-subgroupoids. We provide the characterization of spherical fuzzy AG-subgroupoids over AG-groupoids and examine their related properties. As an application of spherical fuzzy sets over AG-groups, we develop the concept of normal spherical fuzzy groups over AG-groups and investigate their various properties.

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago.

This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project.

The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

Several nonterminal nodes in the ad-hoc sensor network architecture are involved in effectively communicating data. There are not enough nodes other than the terminals to process sensor data and send it between nodes. Because of this, the exchange of sensor data relies on devices capable of predicting events and responding quickly. Identifying the cluster head is essential to the network’s long-term viability and operational efficiency. This paper proposes a robust probabilistic buckshot approach to identify the appropriate nodes, and the smooth handover mechanism in the corresponding cycles is mechanized. The proposed model also employs a heuristic algorithm named HARIS to identify the best cluster head by analyzing the residual energy associated with each sensor node over multiple iterations. The data exchanged among the nodes is encrypted using a lightweight accumulative data encryption model to ensure the confidentiality of the data. The proposed model is evaluated using various statistical analysis metrics like node availability, computational delay, throughput, and network lifetime. The proposed model outperforms the existing energy-sensitive sensor network models by 20–23%.

In this paper, we present a novel technique for security of two-dimensional data with the help of cryptography and steganography. The presented approach provides multilayered security of two-dimensional data. First layer security was developed by cryptography and second layer by steganography. The advantage of steganography is that the intended secret message does not attract attention to itself as an object of scrutiny. This paper proposes a novel approach for encryption and decryption of information in the form of Word Data (.doc file), PDF document (.pdf file), Text document, Gray-scale images, and RGB images, etc. by using Vigenere Cipher (VC) associated with Discrete Fourier Transform (DFT) and then hiding the data behind the RGB image (i.e. steganography). Earlier developed techniques provide security of either PDF data, doc data, text data or image data, but not for all types of two-dimensional data and existing techniques used either cryptography or steganography for security. But proposed approach is suitable for all types of data and designed for security of information by cryptography and steganography. The experimental results for Word Data, PDF document, Text document, Gray-scale images and RGB images support the robustness and appropriateness for secure transmission of these data. The security analysis shows that the presented technique is immune from cryptanalytic. This technique further provides security while decryption as a check on behind which RGB color the information is hidden.

In this cryptosystem, we have considered RGB images for two-dimensional (2D) data security. Security of RGB images during transmission is a major concern, discussed globally. This paper proposes a novel technique for color image security by random hill cipher (RHC) over SL_n(𝔽) domain associated with 2D discrete wavelet transform. Existing techniques have discussed the security of image data on the basis of the keys only (which provide only one layer of security for image data), but in the proposed cryptosystem, the keys and the arrangement of RHC parameters are imperative for correct decryption of color image data. Additionally, key multiplication side (pre or post) with the RGB image data should inevitably be known, to correctly decrypt the encrypted image data. So, the proposed cryptosystem provides three layers of security for RGB image data. In this approach, we have considered keys from the special linear group over a field 𝔽, which provides enormous key-space for the proposed cryptosystem. A computer simulation on standard examples and results is given to support the fixture of the scheme. Security analysis, and detailed comparison between formerly developed techniques and proposed cryptosystem are also discussed for the robustness of the technique. This method will have large potential usage in the digital RGB image processing and the security of image data.

Cloud storage has seen an increasing trend with the development of social networks, but its security remains an important problem to be solved. In this paper, a new encryption scheme based on dynamic attributes is proposed to solve the problem in the attribute based encryption scheme. In the scheme, a data encryption access control strategy is generated by the sender attributes according to certain logical relationships. Additionally, an access control tree structure is used to describe the access control policy. Only when the attribute set of receiver meets the access policy can the data be decrypted; to achieve this, the access control tree structure is dynamically adjusted simultaneously with changes in the attribute set of sender.