Fabrication of copper sulfide nanoparticles from b

A nanomaterial has played a major role in protecting the environment-related issues. The prime reason for that nanomaterials synthetics approach is greener pathway, without using any hazardous chemicals and solvents. A huge number of plant-mediated metal sulfide nanoparticle (especially, Copper sulfide) synthesis has been reported and is still successfully continuing, because of its cost effective manner, eco-friendly nature, simple approach, reaction was carried out room temperatur. The current reports to synthesis of Copper sulfide nanostuctured materials through the green patch way, using Boswellia Ovalifoliolata leaves extract. From the UV-Visible spectroscopy noticed nanoparticles absorbance value is around 325 nm. As identified by FT-IR spectroscopy, a variety sources of phytochemicals in the extract which are responsible for the reduction of metal ions and stabilizing of the nanoparticles. X-ray diffraction studies revealed that nanomaterials were crystalline in nature, average crystalline size around 11 nm. SEM revealed that nanoparticles are spherical in nature and average size is 38.43 nm. The current report emphasizes that the materials are an excellent catalyst activity for the reduction of environmental pollutant azo dyes, antibacterial and antioxidant activity. The current article highlights the reduction of the azo dyes, antibacterial and antioxidant activity so the nanomaterials are apromising for the reduction of polluntat dyes

Ensemble Framework of Artificial immune system based on Network Intrusion Detection System for Network Security Sustainability

The popularity and rapid growth of the internet have reemphasized the importance of intrusion detection systems (IDS) significance in the network security. IDS decreases hacking, data theft risk, privacy intrusion, and others. To save the system from external and internal intruders, the primary approaches of IDS are used. Many techniques[13], like genetic algorithms, artificial neural networks, and artificial immune systems, have been applied to IDS. This paper describes an Ensemble Framework of Artificial Immune System (AIS) based on Network Intrusion Detection System. Without placing a significant additional load on networks and monitoring systems, the large volume of data is analysed by a network-based Intrusion Detection System (NIDS). For determining the connection type, data from KDD Cup 99 competitions is utilized. To differentiate between attacks and valid connections, IDS can be utilized. Optimized feature selection is used to speed up the time-consuming rough set. The results obtained from the IDS system indicate that it can effectively identify the attacking connections with a high success rate