AI and ML are effective tools for data crunching, and thus one should expect to see the growth of exploit tools based on these; both systems can be defeated or influenced to give anomalous results.
FREMONT, CA: With criminals becoming more organized, they will continue to take advantage of human error and commit security attacks. Thus, cybersecurity will unavoidably become a global priority due to increased threats and a heightened sense of susceptibility to unlicensed access to confidential data.
The following three predictions offer to focus on where developments can be made and what must be considered to strengthen security systems:
1. Increase in Multi-Cloud, Multi-Deployment Environments To Safeguard Data:
There will be an extended focus on technologies that cater to on-premises, public, and private cloud environments. One can attribute this to the boomerang effect. A couple of years ago, many organizations were preparing to go 100 percent public cloud, and, in some cases, firms moved a number of their applications to the cloud.
Nevertheless, many others discovered that the public cloud did not meet their requirements on some occasions, including security issues and re-write applications. Thus, the applications boomeranged back on-premises. As a result of this experience, businesses are now gradually choosing to embrace multi-cloud, multi-deployment settings. They are deploying applications as they provide secure and superlative technology regardless of whether they are on-premises or in the cloud.
2. A Rise in Business Applications That Imitate Cloud Settings
Even if they technically do not fall under the public cloud umbrella, enterprises will build infrastructures and architect in a way that permits them to stretch and expand tools and turn on and turn off workloads. These settings will look extraordinarily similar to the public cloud but will be assembled on-premise or in a private cloud.
3. AI For IoT Space
Moving forward, one will see the first wave of leaders in the Artificial Intelligence (AI) for the Internet of Things (IoT) space. Still, cyber offenders will leverage AI and Machine Learning (ML) to find exploits on systems that will lead to prolific and public data security breaches.
AI and ML are effective tools for data crunching, and thus one should expect to see the growth of exploit tools based on these; both systems can be defeated or influenced to give anomalous results. Besides, most of the data being deployed for AI and ML is not usually under the control of a single body. There are several sources and owners, so protecting data integrity used to train intelligent systems is not an easy problem to solve as attackers can effortlessly exploit this loophole.
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