New technological transformation with AI and machine learning helps enterprises to unburden the risks that are brought up with malware and unwanted intrusions in an enterprise.
FREMONT, CA: Cyberattacks have become more complicated in recent years, expanding its effectiveness and speed. The trend is likely to continue unless more companies make a shift as to how they think about their safety and security strategies. With the velocity, volume, and sophistication of today's global threat landscape, companies must be able to respond in real-time at machine speed to effectively aggressive attacks. Advances in AI and threat intelligence will be significant in this fight.
Funding AI not only enables organizations to automate tasks, but it also enables an automated system that can look for discovering attacks, after and before they occur. Integrating machine learning with statistical analysis will enable organizations to develop customized action planning tied to AI to improve threat detection and response. These threat playbooks will allow the AI system to predict an attacker's next move, forecast, and also decide which threat actors are the most likely the culprits. If the information is added into an AI learning system, the remote learning nodes will help to produce advanced and proactive protection, where they not only discover a threat, also forecast movements, combine with other nodes to simultaneously shut down all avenues of attack, and also proactively intervene.
Over the past years, the rise of swarm technology, that utilizes machine learning and AI to attack networks and devices, has shown a new change of path. Progress in swarm technology has powerful implications in the fields of medicine, transportation and engineering. But, if used maliciously, it may also be a game-changer for enemies if organizations do not update their security strategies. When used by cybercriminals, the bot swarms could be used to infiltrate a network, overwhelm internal defences, and efficiently find and extract information. Gradually, specialized bots, armed with specific functions, will help to share and exchange the intelligence collected in real-time to simulate a swarm's ability to select and modify attacks to settle a target or even multiple targets together.
The entry of 5G is going to be the initial catalyst for the development of functional swarm-based attacks. By using the 5G and edge computing, individually exploited devices can become a channel for malicious code, and organizations of compromised devices could work in concert to target victims at 5G speeds.
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