WSN has been exhilarated in many application areas such as military, medical, environment, etc. Due to the rapid increase in applications, it causes proportionality to security threats because of its wireless communication. Since nodes used are supposed to be independent of human reach and dependent on their limited resources, the major challenges can be framed as energy consumption and resource reliability. Ensuring security, integrity, and confidentiality of the transmitted data is a major concern for WSN. Due to the limitation of resources in the sensor nodes, the traditionally intensive security mechanism is not feasible for WSNs. This limitation brought the concept of digital watermarking in existence. Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. In this paper, several issues and challenges, as well as the various threats of WMSN, is briefly discussed. Also, we have discussed the digital watermarking techniques and its role in WMSN. Read more:https://bit.ly/3Q19uc2
Introduction: Intrusion detection systems play a key role in system security by identifying potential attacks and giving appropriate responses. As new attacks are always emerging, intrusion detection systems must adapt to these attacks, and more work is continuously needed to develop and propose new methods and techniques that can improve efficient and effective adaptive intrusion systems. Feature selection is one of the challenging areas that need more work because of its importance and impact on the performance of intrusion detection systems. This paper applies an evolutionary search algorithm in feature subset selection for intrusion detection systems.
Methods: The evolutionary search algorithm for the feature subset selection is applied and two classifiers are used, Naïve Bayes and decision tree J48, to evaluate system performance before and after features selection. NSL-KDD dataset and its subsets are used in all evaluation experiments.
Results: The results show that feature selection using the evolutionary search algorithm enhances the intrusion detection system with respect to detection accuracy and detection of unknown attacks. Furthermore, time performance is achieved by reducing training time, which is reflected positively in overall system performance.
Discussion: The evolutionary search applied to select IDS algorithm features can be developed by modifying and enhancing mutation and crossover operators and applying new enhanced techniques in the selection process, which can give better results and enhance the performance of intrusion detection for rare and complicated attacks.
Conclusion: The evolutionary search algorithm is applied to find the best subset of features for the intrusion detection system. In conclusion, it is a promising approach to be used as a feature selection method for intrusion detection. The results showed better performance for the intrusion detection system in terms of accuracy and detection rate. Read now:https://bit.ly/3zf9mhV
Micro and Nano-systems publishes significant original work, topical reviews and guest edited issues ranging from technologies and systems to product innovation and new manufacturing processes with features at the micro and nanoscale. Applications for micro and nano-systems in areas such as health, environment, food, security and consumer goods are covered. The topics to be addressed include lab-on-a-chip, microfluidics, nano-biotechnology, micro and nano manufacturing, printed electronics and MEMS.
Articles from the journal Micro and Nanosystems Volume 10, Issue 1: