Hamid Barati

Maryam Ataei Nezhad, Hamid Barati, Ali Barati

Internet of Things means connecting different devices through the Internet. The Internet of things enables humans to remotely manage and control the objects they use with the Internet infrastructure. After the advent of the Internet of Things in homes, organizations, and private companies, privacy and information security are the biggest concern. This issue has challenged the spread of the Internet of things as news of the users theft of information by hackers intensified. The proposed method in this paper consists of three phases. In the first phase, a star structure is constructed within each cluster, and a unique key is shared between each child and parent to encrypt and secure subsequent communications. The second phase is for intracluster communications, in which members of the cluster send their data to the cluster head in a multi hop manner. Also, in this phase, the data is encrypted with different keys in each hop, and at the end of each connection, the keys are updated to ensure data security. The third phase is to improve the security of inter cluster communications using an authentication protocol. In this way, the cluster heads are authenticated before sending information to prevent malicious nodes in the network. The proposed method is also simulated using NS2 software. The results showed that the proposed method has improved in terms of energy consumption, end-to-end delay, flexibility, packet delivery rate, and the number of alive nodes compared to other methods.

Pouriya Alimoradi, Ali Barati, Hamid Barati

The rapid advancement of Artificial Intelligence has enabled the development of cruise missiles endowed with high levels of autonomy, adaptability, and precision. These AI driven missiles integrating deep learning algorithms, real time data processing, and advanced guidance systems pose critical threats to strategic infrastructures, especially under complex geographic and climatic conditions such as those found in Irans Khuzestan Province. In this paper, we propose a multi layer interference model, encompassing electronic warfare, cyberattacks, and deception strategies, to degrade the performance of AI guided cruise missiles significantly. Our experimental results, derived from 400 simulation runs across four distinct scenarios, demonstrate notable improvements when employing the integrated multi layer approach compared to single layer or no interference baselines. Specifically, the average missile deviation from its intended target increases from 0.25 to 8.65 under multi layer interference a more than 3300 increase in angular deviation. Furthermore, the target acquisition success rate is reduced from 92.7 in the baseline scenario to 31.5, indicating a 66 decrease in successful strikes. While resource consumption for multi layer strategies rises by approximately 25 compared to single layer methods, the significant drop in missile accuracy and reliability justifies the more intensive deployment of jamming power, cyber resources, and decoy measures. Beyond these quantitative improvements, the proposed framework uses a deep reinforcement learning based defense coordinator to adaptively select the optimal configuration of EW, cyber, and deception tactics in real time.

Mohammad Reza Akbari, Hamid Barati, Ali Barati

Fog computing integrates cloud and edge resources. According to an intelligent and decentralized method, this technology processes data generated by IoT sensors to seamlessly integrate physical and cyber environments. Internet of Things uses wireless and smart objects. They communicate with each other, monitor the environment, collect information, and respond to user requests. These objects have limited energy resources since they use batteries to supply energy. Also, they cannot replace their batteries. As a result, the network lifetime is limited and short. Thus, reducing energy consumption and accelerating the data transmission process are very important challenges in IoT networks to reduce the response time. In the data transmission process, selecting an appropriate cluster head node is very important because it can reduce the delay when sending data to the fog. In this paper, cluster head nodes are selected based on several important criteria such as distance, residual energy, received signal strength, and link expiration time. Then, objects send the processed data to the server hierarchically through a balanced tree. The simulation results show that the proposed method outperforms the energy-efficient centroid-based routing protocol (EECRP) and the Emergency Response IoT based on Global Information Decision (ERGID) in terms of packet delivery rate, delay, response time, and network lifetime.

Mohammad Reza Akbari, Hamid Barati, Ali Barati

Due to the big data exchange on the Internet of Things, proper routing and selecting the best routes for fast data transmission improve network performance. There are major challenges, like high delay, when cloud computing is used. Therefore, one solution is to use other schemes, such as fog computing. In fog computing, all data is not sent to the cloud and the fog nodes close to objects are used for data processing. This reduces the network delay. In this paper, we propose an overlapping clustering method called MFCT-IoT to select the best cluster head nodes to guarantee the fast data transfer from objects to fog nodes. The selected cluster head nodes are responsible for sending the collected data to the closest fog nodes in the network edge. Upon receiving the data, the fog nodes process it, and if a response is ready, they respond immediately to the object. Otherwise, they merge and transmit the data to the cloud servers, which are considered as the root node of the proposed hierarchical tree. After processing, the merged data is sent to the object. We compare the proposed scheme with two schemes, including ERGID and EECRP. These schemes are evaluated based on various criteria, including the response time, packet delivery ratio, end-to-end delay, network lifetime, and energy consumption. The results indicate that the proposed method outperforms others in terms of all criteria.

Shiva Sattarpoor, Hamid Barati

As digital content can be copied easily, Copyright infringement has become a concern nowadays. Providing a solution to prevent the abuse of such contents is very necessary. One of the most common methods to solve this problem is watermarking. In this method, a logo belongs to the owner of the media is embedded in the media. So, they can prove the originality or ownership of the media content. Images are one of the most important digital media. Therefore, in this study, a method for digital image watermarking is proposed. The proposed method is based on Graph-based Transform (GBT), Singular Value Decomposition (SVD), and Discrete Wavelet Transform (DWT) which uses a Whale Optimization Algorithm (WOA) to find the best value for the embedding coefficient in the images as well as optimal blocks. The image is first transformed to a transform domain using the DWT and GBT, and then the watermark logo embedded onto the singular values of the cover image. The objective function defined for this task is based on the three parameters PSNR and NC, in the presence of image attacks. The results of the proposed algorithm on some known images show a high performance of this method compared to other similar methods.