Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes del

Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the

Tchebichef polynomials (TPs) play a crucial role in various fields of mathematics and applied sciences, including numerical analysis, image and signal processing, and computer vision. This is due to the unique properties of the TPs and their remarkable performance. Nowadays, the demand for high-quality images (2D signals) is increasing and is expected to continue growing. The processing of these signals requires the generation of accurate and fast polynomials. The existing algorithms generate the TPs sequentially, and this is considered as computationally costly for high-order and larger-sized polynomials. To this end, we present a new efficient solution to overcome the limitation of sequential algorithms. The presented algorithm us

We conducted a theoretical study on the potential use of amorphous hydrogenated silicon (a-Si:H) as the high-index material in quarter-wave-stack Bragg mirrors for cavity quantum electrodynamics applications. Compared to conventionally employed T a 2

In this study, synthesised new ligand: potassium 2,2'-(quinoxaline-2,3- diyl)bis(1-phenylhydrazinecarbodithioate) (L). The ligand synthesised by reacting N1,N2-dip-tolyloxalamide as the starting material with CS2 and KOH to add the CS2 group and then with phenylendiammine to achieve (L). The ligand used in the synthesis of complexes with (CoII, NiII and CdII). The new ligand and its complexes characterised by FT-IR, UV-Vis, 1H, 13C-NMR, Mass spectroscopy, and elemental analysis, in addition to the above techniques were using magnetic moment, atomic absorption, chloride content, and melting point to describe the metal complexes.

The aim of this research was to indicate the opinion of the Iraqi consumer awareness of the risks associated with consuming canned food, the questionnaire was included 20 questions for label information, consumer culture, shopping, marketing, awareness and knowledge as a tool to survey the opinions of 300 consumers in Baghdad, the data was analyzed by using percentage, weighted mean, and weight percent, the results obtained showed that the Iraqi consumer need more information, training and guidance programs in food safety handling issue for canned food, especially in analysis of label information and growing of consumer culture for shopping, right marketing, awareness and knowledge.