Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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

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

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

The  use  of  blended  cement  in  concrete  provides economic, energy savings,  and ecological  benefits, and also  provides. Improvement in the properties of materials incorporating blended cements. The  major  aim  of  this  investigation  is  to  develop  blended  cement  technology using  grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement.

The main conclusion of this study was that all ty

The use of blended cement in concrete provides economic, energy savings, and ecological benefits, and also provides. Improvement in the properties of materials incorporating blended cements. The major aim of this investigation is to develop blended cement technology using grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement. The main conclusion of this study was that all types of manufactured blended cement conformed to the specification according to ASTM C595-12 (chemical and physical requirements). The percentage of the compress

The use of blended cement in concrete provides economic, energy savings, and ecological benefits, and also provides. Improvement in the properties of materials incorporating blended cements. The major aim of this investigation is to develop blended cement technology using grinded local rocks . The research includes information on constituent materials, manufacturing processes and performance characteristics of blended cements made with replacement (10 and 20) % of grinded local rocks (limestone, quartzite and porcelinite) from cement. The main conclusion of this study was that all types of manufactured blended cement conformed to the specification according to ASTM C595-12 (chemical and physical requirements). The percentage of the compress