With the rise of technology and the use of digital tools, cybersecurity risks have also increased, as there are more and more hackers.
This article presents the latest developments in cloud security technology and how they appear to be shaping up for 2024. We recommend that workspaces keep them on their radar to identify how to leverage them and thus increase the security of their operations and products.
Hybrid and multi-cloud models
Hybrid and multi-cloud models are increasingly popular options among companies. These allow them to take advantage of the benefits of the cloud without giving up control and flexibility of their own resources.
A hybrid model combines public cloud with private cloud or on-premises data center, while a multi-cloud model uses different public cloud providers to distribute data and tasks.
These types of models seek to offer storage or cloud solutions according to each department. In this way, companies can work in a hybrid way, each with its own cloud and its own solution.
Cybersecurity measures suggested for these models
Some of the steps you can korea telegram mobile phone number list take to improve security in hybrid and multi-cloud models include:
Choose cloud providers that meet the most complex security and privacy standards with solutions compatible with your IT infrastructure.
Use unified management tools that allow you to monitor, audit and manage cloud resources from a single platform.
Implement consistent and coherent security policies across all environments, applying the principle of least privilege and encryption of data in transit and at rest.
Perform regular backups and disaster recovery plans that allow you to restore data and applications in the event of incidents or attacks.
Professional hands searching a laptop for cloud security measures
Artificial Intelligence and Machine Learning
Artificial intelligence (AI) and machine learning (ML) are technologies that enable machines to learn from data and perform complex tasks without explicit programming.
If executed properly, AI and machine learning will analyze threats and learn from them. In this way, they will be able to create much more robust and predictive security measures. This will allow the cloud to protect itself according to the type of threat.
Applications of AI and Machine Learning for Cloud Security
Detect and prevent advanced threats by analyzing anomalies and suspicious patterns.
Automate and optimize security processes such as data classification, permission assignment, incident response, and reporting.
Improve the user experience by offering personalized , agile and secure services such as facial recognition, voice control or biometric authentication.
Learning from threats or attacks received, as well as predicting when one will occur in order to prevent them from being successful.
API Security Strategies
APIs are sets of rules that allow applications to communicate and exchange information with each other. APIs are essential to the functioning of the cloud, as they facilitate integration, interoperability, and innovation between different services and platforms.
However, APIs can also be a weak point in cloud security , as they can be exploited by cybercriminals to access sensitive data, compromise systems, or perform DNS attacks.