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Author

Monisha Gottam

Bio: Monisha Gottam is an academic researcher. The author has contributed to research in topics: Computer science & Security through obscurity. The author has co-authored 2 publications.

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Journal ArticleDOI
TL;DR: Machine learning is an important part of predictive analytics and can increase the speed of data analysis and processing. But there are a few things you need to know before you begin to use these algorithms as discussed by the authors .
Abstract: Abstract: Machine learning algorithms are being used to improve predictive analytics. These algorithms are getting better at predicting future data. This is a great thing. But there are a few things you need to know before you begin to use these algorithms. Machine learning is an important part of predictive analytics and can increase the speed of data analysis and processing. It also allows predictive analytics algorithms to learn on larger data sets and conduct deep analysis on multiple variables. As a result, machine learning has become an important part of many businesses. Though there is still some controversy regarding its use, many industries are successfully implementing it. This technique has a long history of use in the financial sector, particularly in banking and investing, E-commerce, Customer service, Medical Diagnosis, Sales and Marketing, Financial Services, Cybersecurity and can help organizations forecast asset values. Additionally, it can help users understand the relationships between variables.
Journal ArticleDOI
TL;DR: In this article , the authors examine the importance of security performance, the role of the cloud, machine learning-based security models, and incident response, and identify five critical areas in which intelligence attacks pose a high risk to organizations.
Abstract: Abstract: An outlook on the status of security performance in light of intelligence focuses on the business aspects and needs of organizations. The security plan needs to be integrated with the business and should be developed in collaboration with different groups within an organization. Organizations need to have a culture that embraces security and intelligence. Security performance is one of the top concerns of modern businesses. Companies must look at the underlying causes of their problems in order to fix them. A good cybersecurity posture is often measured by a lack of data breaches. Lack of specific metrics, however, may be an indication that a company does not have a strategic mindset. Attacks and malfunctions are extremely costly. Detection involves identifying suspicious behaviors and alerting the appropriate personnel. An important challenge in detecting suspicious activity is finding the right balance between false alarms and coverage. An effective security program must be able to mitigate attacks while reducing false alarms. The growing reliance on artificial intelligence (AI) is creating a new kind of cybervulnerability. Developers often overlook AI security, leaving it open to attack by adversaries. Attacks can take the form of basic manipulations and probes or adversarial AI. As the number of computer systems increases, so do the risks they pose to the security of data and systems. This article examines the importance of security performance, the role of the cloud, machine learning-based security models, and incident response. We also look at the importance of a security model that incorporates intelligence. Finally, this report also identifies five critical areas in which Intelligence attacks pose a high risk to organizations.