An Intelligent Agent Based Intrusion Detection System Using Fuzzy Rough Set Based Outlier Detection

Since existing Intrusion Detection Systems (IDS) including misuse detection and anomoly detection are generally incapable of detecting new type of attacks. However, all these systems are capable of detecting intruders with high false alarm rate. It is an urgent need to develop IDS with very high Detection rate and with low False alarm rate. To satisfy this need we propose a new intelligent agent based IDS using Fuzzy Rough Set based outlier detection and Fuzzy Rough set based SVM. In this proposed model we intorduced two different inteligent agents namely feature selection agent to select the required feature set using fuzzy rough sets and decision making agent manager for making final decision. Moreover, we have introduced fuzzy rough set based outlier detection algorithm to detect outliers. We have also adopted Fuzzy Rough based SVM in our system to classify and detect anomalies efficiently. Finally, we have used KDD Cup 99 data set for our experiment, the experimental result show that the proposed intelligent agent based model improves the overall accuracy and reduces the false alarm rate

Development of Derivatives of 3, 3′-Diindolylmethane as Potent Leishmania donovani Bi-Subunit Topoisomerase IB Poisons

Background: The development of 3, 39-diindolyl methane (DIM) resistant parasite Leishmania donovani (LdDR50) by adaptation with increasing concentrations of the drug generates random mutations in the large and small subunits of heterodimeric DNA topoisomerase I of Leishmania (LdTOP1LS). Mutation of large subunit of LdTOP1LS at F270L is responsible for resistance to DIM up to 50 mM concentration. Methodology/Principal Findings: In search of compounds that inhibit the growth of the DIM resistant parasite and inhibit the catalytic activity of mutated topoisomerase I (F270L), we have prepared three derivatives of DIM namely DPDIM (2,29diphenyl 3,39-diindolyl methane), DMDIM (2,29-dimethyl 3,39-diindolyl methane) and DMODIM (5,59-dimethoxy 3,39diindolyl methane) from parent compound DIM. All the compounds inhibit the growth of DIM resistant parasites, induce DNA fragmentation and stabilize topo1-DNA cleavable complex with the wild type and mutant enzyme. Conclusion: The results suggest that the three derivatives of DIM can act as promising lead molecules for the generation of new anti-leishmanial agents

Medical representatives: The struggles

The Covid-19 has influenced in the job medical representatives at a large extent. The private employees are the persons those who are participating their contribution in the growth and the development of the nation. It is a highly risk job. Long travelling, convincing tactics, lack of food stress, the target, emotional stability are making them more and more tired. Sometimes they become frustrated about their job. Many of them are switching over to other jobs. They need more training also. So the enterprises or organization should pay the attention to prevent and eliminate such problems of an employee in the lockdown period. This study analyzed the issues faced by the sales representatives while achieving their given target. Controlling anger and maintaining patience is the best characteristics of the medical representatives in the lockdown period

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Cognitive Radio (CR) is a wireless communication system that is used for intelligent vehicles to solve spectrum scarcity and improve the utilization of the spectrum. However, spectrum sensing and data sharing are difficult due to the presence of malicious nodes which degrades the performance. To overcome these issues, we proposed the BlockCRN-IoCV method which includes authentication, density aware clustering, dual agent based spectrum access and secure beamforming. Here, authentication is performed for both Primary Users (PUs) and Secondary Users (SUs) using the Hybrid Advanced Encryption Standard and Hyper-elliptic Curve Cryptography (AES-HCC) algorithm by considering ID, PUF and location which ensures the legitimacy of the users. To address the mobility of the vehicle we perform density aware clustering using Density aware Dynamic Radius Clustering (DADRC) by considering location, distance and direction for increasing throughput. After completing clustering, we perform efficient spectrum access by using the Dual Agent based Twin Delayed (DA-TD3) algorithm which includes two agents, the first agent performs spectrum sensing by considering SNR, noise level and trust, and the second agent performs spectrum allocation by considering Channel State Information (CSI), in which the CSI is predicted by Quasi-Newton Iterative Unscented Kalman Filter (QNIUKF) algorithm for effective data transmission. Finally, secure beamforming is performed using Bi-Gated Recurrent Neural Network (BiGRU-CapsNet) by considering CSI, beam score, array factor, and direction of angle. The simulation is carried out by OMNET++ and SUMO simulation tools and the performance of this work is evaluated by throughput, packet delivery ratio, SNR, detection accuracy, BER, and delay. The simulation result shows that the proposed work achieves superior performance compared to existing work for secure spectrum sensing and beamforming