Author
Abstract
There is a broad scope of interdisciplinary crossing points between Artificial Intelligence (AI) and Cybersecurity. On the one hand, AI advancements, such as deep learning, can be introduced into cybersecurity to develop innovative models for executing malware classification, intrusion detection, and threatening intelligent detecting. Then again, AI models will confront different cyber threats, affecting their sample, learning, and decision-making. Along these lines, AI models need specific cybersecurity defense and assurance advances to battle ill-disposed machine learning, preserve protection in AI, secure united learning, and so forth. Because of the above two angles, we audit the crossing point of AI and Cybersecurity. To begin, we summarize existing research methodologies regarding fighting cyber threats utilizing artificial intelligence, including receiving traditional AI techniques and living deep learning solutions. At that point, we analyze the counterattacks that AI itself may endure, divide their qualities, and characterize the related protection techniques. And finally, from the aspects of developing encrypted neural networks and understanding safe deep learning, we expand the current analysis on the most proficient method to create a secure AI framework. This paper centers mainly around a central question: "By what means can artificial intelligence applications be utilized to upgrade cybersecurity?" From this question rises the accompanying set of sub-questions: What is the idea of artificial intelligence, and what are its fields? What are the main areas of artificial intelligence that can uphold cybersecurity? What is the concept of data mining, and how might it be utilized to upgrade cybersecurity? Hence, this paper is planned to reveal insight into the idea of artificial intelligence and its fields and how it can profit by applications of AI brainpower to upgrade and improve cybersecurity. Using a distinct analytical approach to past writing on the matter, the significance of the need to utilize AI strategies to strengthen cybersecurity was featured, and the main fields of application of artificial intelligence that upgrade cybersecurity, for example, machine learning, data mining, deep learning, and expert systems.
Suggested Citation
Donepudi, Praveen Kumar, 2015.
"Crossing Point of Artificial Intelligence in Cybersecurity,"
American Journal of Trade and Policy, Asian Business Consortium, vol. 2(3), pages 121-128.
Handle:
RePEc:ris:ajotap:0106
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:ajotap:0106. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alim Al Ayub Ahmed (email available below). General contact details of provider: https://abc.us.org/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.