With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

Abstracts:

The Central Bank is the backbone of the banking system as a whole, and in order to maintain the banking system, one of the most important functions that the Central Bank performs is the function of supervising and controlling banks, with several tools and methods, and one of the most important of these tools is its creation of the function of a compliance observer, which obligated commercial banks to appoint a person in A bank that performs this function according to certain conditions and granting it some powers that would build a sound and compliant banking system. The function of the compliance observer is to follow up on the bank’s compliance with the instructions and decisions issued by

There is a set of economic factors that affect the rationalization of decisions on unexploited resources within the economic unit and here determines the problem of the search for the question of what economic factors cause the emergence of asymmetric costs, and aims to identify these factors in the costs of adjustment to resources, change in The size of the activity of the economic unit, the general trend of sales change in the previous period, and the economic level of the country. Rh measure the impact of these factors on economic unity, and taking into consideration the impact when formulating decisions.