Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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The current research aims to identify the psychological security of students in the kindergarten department and identify if there is a significant difference between stage one and stage four students. To do this, the researcher adopted the psychological research scale of (Al-mohamdawi, 2007) that consisted of (30) items. It was administered to (120) female students chosen randomly from the kindergarten department in the college of education for women for the academic year (2029-2021). The results revealed that students in the kindergarten department have psychological security. There is a significant difference between stage one and four students in favor of stage four students.

Since Internet Protocol version 6 is a new technology, insecure network configurations are inevitable. The researchers contributed a lot to spreading knowledge about IPv6 vulnerabilities and how to address them over the past two decades. In this study, a systematic literature review is conducted to analyze research progress in IPv6 security field following the Preferred Reporting Items for the Systematics Review and Meta-Analysis (PRISMA) method. A total of 427 studies have been reviewed from two databases, IEEE and Scopus. To fulfil the review goal, several key data elements were extracted from each study and two kinds of analysis were administered: descriptive analysis and literature classification. The results show positive signs of t

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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                 This research aims to define the roles of auditors by clarifying the concept and risks of cyber security in protecting information and financial data in economic units. Najaf, Babylon and Karbala, then the results were analyzed and the results were presented and analyzed to show that adopting cyber security improves the quality of reports Finance through what it achieves in displaying information with credibility and transparency, in a way that suits the needs of users, and cyber security has a role in managing economic resources more effectively to obtain benefits that would have been lost in the event of an

Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The