Recent Advances in Computer Science and Communications - Volume 17, Issue 7, 2024

The extensive use of electricity and the increasing number of consumers challenge matching power consumption with the power generated. Having a traditional way of power generation and distribution, power is also widely fetched through renewable energy sources. So, to have improved efficiency and reliable means of the power source, to be able to integrate multiple sources of power generation like PV Cells, Solar Power, and Wind Power into the existing standards of the power source, precise calculations of the power consumption in the multisource environment, provision to scale up the smart and electric vehicle and most importantly, to reduce the carbon emissions, several attempts have been made to convert the traditional grids into smart grids. A tiny step in the smart grid's development is the smart metering infrastructure, in which smart meters are deployed through the consumer end. Through smart meters, it is possible to establish the link, either through wireless media or wired connections, between the consumer and the grid. Once the smart meters are deployed through the Advanced Metering Infrastructure (AMI), the meters remain active round the clock, giving a window to hackers. Through this window, utility bill manipulations, payment transaction information, and other significant data can be accessed by unethical approaches and threaten the consumer's privacy. This review-research paper discusses various methods presented by distinct authors to address the issues related to customer privacy protection in the smart grid.

The Internet of Things (IoT) has revolutionized our society and become indispensable to modern existence. The IoT allows users to access their electronic gadgets from any location. The widespread adoption of IoT across sectors, from manufacturing to surveillance to elder care, has contributed to its rising profile. New security risks and challenges arise with the growth of the IoT. With the development of IoT, the likelihood of an attack by hackers has increased. The burden of addressing these dangers falls on researchers and security professionals. This article looks into the challenges of IoT security in a real-world Ambient Assisted Living (AAL) environment. This work discusses the numerous security attacks employed by cybercriminals in AAL IoT. In addition, this research investigates the varied responses to the risks. We discussed the state-of-the-art technologies available for protecting AAL IoT networks. This work analyses and compares the majority of the latest technologies available. In conclusion, we offer a few suggestions for where the field could go from the current scenario.

Background: Data authentication is vital nowadays, as the development of the internet and its applications allow users to have all-time data availability, attracting attention towards security and privacy and leading to authenticating legitimate users. Methods: We have diversified means to gain access to our accounts, like passwords, biometrics, and smartcards, even by merging two or more techniques or various factors of authentication. This paper presents a systematic literature review of papers published from 2010 to 2022 and gives an overview of all authentication techniques available in the market. Results: Our study provides a comprehensive overview of all three authentication techniques with all performance metrics (Accuracy, Equal Error Rate (EER), False Acceptance Rate (FAR)), security, privacy, memory requirements, and usability (Acceptability by user)) that will help one choose a perfect authentication technique for an application. Conclusion: In addition, the study also explores the performance of multimodal and multifactor authentication and the application areas of authentication.

Background: Knowledge representation learning aims at mapping entity and relational data in knowledge graphs to a low-dimensional space in the form of vectors. The existing work has mainly focused on structured information representation of triples or introducing only one additional kind of information, which has large limitations and reduces the representation efficiency. Objective: This study aims to combine entity description information and textual relationship description information with triadic structure information, and then use the linear mapping method to linearly transform the structure vector and text vector to obtain the joint representation vector. Methods: A knowledge representation learning (DRKRL) model that fuses external information for semantic enhancement is proposed, which combines entity descriptions and textual relations with a triadic structure. For entity descriptions, a vector representation is performed using a Bi-directional Long- and Short-term Memory Network (Bi-LSTM) model and an attention mechanism. For the textual relations, a convolutional neural network is used to vectorially encode the relations between entities, and then an attention mechanism is used to obtain valuable information as complementary information to the triad. Results: Link prediction and triadic group classification experiments were conducted on the FB15K, FB15K-237, WN18, WN18RR, and NELL-995 datasets. Theoretical analysis and experimental results show that the DRKRL model proposed in this paper has higher accuracy and efficiency compared with existing models. Conclusion: Combining entity description information and textual relationship description information with triadic structure information can make the model have better performance and effectively improve the knowledge representation learning ability.

Objective: Considering that some image encryption algorithms have the disadvantages of complex structure and high computational cost, and there are not many commonly used chaotic systems, which are easy to crack by attacks, to solve these problems, this paper proposes an image encryption algorithm based on three-dimensional nonlinear functions to solve these problems. Methods: The algorithm mainly combines the sinusoidal chaotic map with the ternary nonlinear function system to encrypt the image. Firstly, multiple ternary nonlinear function chaotic systems are designed. Then, the function iteration system is changed to invoke the computation of a specific expression under a random number; it is a chaotic sequence generated according to a chaotic mapping such as sine, and then the value of this chaotic sequence is used to select a ternary nonlinear function for iteration to obtain a chaotic sequence. Finally, the chaotic sequence performs the XOR and scrambling operations on the grey image. Results: The algorithm has a simple structure, a better encryption effect, and more incredible difficulty deciphering. Moreover, through the phase diagram and bifurcation diagram, it can be seen that the system has good chaotic characteristics. Conclusion: The method in this paper is novel; this method is a random variable order composite operation, which can not only be applied to image encryption but also can be used for fractal map generation and so on, and in some other chaotic fields will have a wide range of applications. It has essential research value.