The rise of Artificial Intelligence (AI) has disrupted the security and threat scene. To combat, organizations all over the world are taking diverse measures including threat intelligence sharing, malware attribution, and data privacy to keep cybercriminals at bay.
Internet of Things (IoT) has increased the security weak points in an organization radically. The degree of rising security issues is so enormous that it is impossible for a single resource or a small team to watch over these threats. This is where AI comes in.
Advanced AI/ML applications are comparable to an army of cybersecurity experts scrutinizing numerous business operations. AI is usually implemented to identify simple threats and attacks. Systems and applications which are AI-powered can remediate issues on their own. The most effective AI applications being used for cybersecurity include Network intrusion detection, Fraud detection, Botnet detection, Hacking Forecasting, and Anomaly Detection.
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Stoodnt.com got in touch with Piyush Bansal, Cybersecurity Expert, SmartGaon Development Foundation, to delve deeper into the topic. According to Bansal, with quick development in AI, all the fundamental assumptions of cybersecurity are breaking, and a new paradigm shift is happening in the cyberattack and there is now a need for renewed ways to handle it.
“We have seen in history criminals are among the first adopter of any cutting edge technology. With the tremendous growth in AI, computing power and storage, the cyberattack has become more sophisticated, swifter and powerful. Modern cyber-criminals are integrating machine learning and AI in their cyber attacks. With the highly connected world, massive compute power, storage and AI these cyber-attacks can have far-reaching consequences,” he shared.
To tackle these challenges cybersecurity needs AI-driven threat detection and response. Machine learning and AI gives an opportunity to seamlessly detect and handle massive cyberattack. “It could be a big boon to cybersecurity if security experts can effectively use AI with massive compute and big data to proactively identify potential threats and ensure near-instant response, containment, mitigation, and remediation,” notified Bansal, who feels almost all the major companies integrate machine learning with cybersecurity to keep malicious users away from their platform.
“For example, to prevent hackers access the user account and gain personal information these companies have a threat model running on their side. Even if hackers have credentials to user account these models keep them out of the platform. These models are powered by machine learning that detects any anomaly and blocks hackers,” he cited.
These models can be applied to any sensitive information on the platform. Logins, registration, payments, user data, and other sensitive information are all protected using these models.
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Bansal further maintained that many companies have stepped up investments in building solutions and platforms for cybersecurity intelligence. “Palo Alto Networks has a behavioral analytics solution called Magnifier that uses structured and unstructured machine learning to model network behavior and improve threat detection. Alphabet, Google’s parent company has a cybersecurity intelligence platform called “Chronicle”, that throws massive amounts of storage, processing power, and advanced analytics at cybersecurity data to accelerate the search and discovery of needles in a rapidly growing haystack,” he informed.
A mobile app can serve crucial purposes on macro levels like bringing about rural development, which is imperative for India, with the integration of AI-based Cybersecurity, to build trust amongst users. Such secure operations can be deployed to benefit millions through various functions served by mobile apps that can serve to bring about a sea change in national development.
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