In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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

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

he study aimed to purify of Leucine aminopeptidase (LAP) from sera of hyperthyroidism patients and its relation to some thyroid hormones (TSH, T 3 , T 4 ) of subclinical hyperthyroidism and hyperthyroidism patients with lipid peroxidation levels that may be play a role in this diseases. Specimens were collected during the time from Nov 2017 until Jan 2018 from Endocrine and Diabetes Center, blood samples were collected from fifty healthy control and one hundred patients, patients were divided into two groups consisted of (50) with hyperthyroidism and (50) with subclinical hyperthyroidism. The aged for all subjects ranged (15-60) years with body mass ranged ((25- 29) kg/m 2 . The purification is done by addition of ammonium sulfate, dial

Background. Colorectal cancer, ranking second place in global cancer mortality, arises from diverse causes. There is growing recognition of the substantial involvement of the epigenetic modifications of histones at the DNA level in the occurrence of CRC. Aim. To assess the expression of p53, HDAC1, and HDAC3 proteins in a cohort of CRC patients and to analyze potential relationship between their expression and the stages of CRC progression. Materials and Methods. The retrospective investigation was carried out on 95 paraffin-embedded CRC tissue samples. The expression of p53, HDAC1, and HDAC3 was assessed immunohistochemically. Results. Notably, the expression of the p53 protein in CRC tissue samples exhibited a prominent correlatio