Problem Statement
Addressing Cyber Security Challenges with AI
A company was facing issues with securing sensitive data and systems against cyber threats. Traditional security measures such as passwords and firewalls are no longer sufficient to protect against sophisticated attacks, and detecting suspicious activities in real-time can be difficult for human analysts. Even if companies implement advanced security features like Multi-Factor Authentication (MFA) or Risk-Based Authentication, they all use rule-based systems. These Rule-based systems are static and generic for all cases. Hence, a lot of anomalies go unnoticed which poses some malicious security threats. To counter these threats and loopholes, the company requires a more dynamic solution combining artificial intelligence models to enhance security measures like Multi-Factor Authentication & Risk-Based Authentication. They wanted to implement a solution capable of analyzing real-time user behavior and access patterns to identify any anomalies or suspicious activity. This data was then utilized to determine whether access should be granted or denied.
Solution
Redefining Cyber Security with Scalifi Ai's AI-Powered User Behavior Analysis
Risk factors reduce when the outdated rule-based system is nullified with modern AI models which are dynamic and can easily learn user behavioral patterns & find anomalies. Scalifi Ai’s, AI-powered system uses machine learning algorithms to analyze user behavior and access patterns in real-time. Since AI models are dynamic and can identify hidden patterns and even learn the behavior of different users, they can increase the efficiency of Multi-Factor Authentication and Risk-Based Authentication to provide an enhanced security posture. The Scalifi Ai’s AI engines can be integrated with your Identity Providers (IDPs), firewalls, gateways, etc. to provide better accuracy for determining risk factors for Adaptive authentication. We offer hybrid deployment options where our AI engine runs in your cloud environment so that all the data remains within your VPC or Virtual Private Cloud to ensure the highest level of privacy. Even the entire training & retraining pipelines of our AI engines or AI models can be easily done in your cloud environment without any human intervention.
Benefits
Eradicate the Loopholes of Risk-Based Authentication
The AI-powered system offers real-time analysis of user behavior and access patterns which is not possible in the case of rule-based systems traditionally used in risk-based & multi-factor authentication. AI models when integrated with risk-based authentication enable quick detection of anomalies and suspicious activities which makes the security posture more effective.
Real-Time Dynamic Protection
AI models can be trained periodically with updated user data and they can detect minute patterns in user behavior. As user behavior can be prone to changes with time, so does the security threats increase if you are using the same set of rules to determine risk, but AI models are periodically trained and you can select how often they need to be trained. This dynamic approach of AI models ensures better threat detection in specific use cases and leaves no margin of error.
Easy Integration & Secure Deployment
Our AI Engines can be easily integrated with your existing Identity Providers (IDPs) and make your existing security systems like risk-based authentication more effective without any margin of error. We provide multiple deployment models like On-Premise, cloud, and Hybrid. In a hybrid deployment, the AI models are deployed in your Virtual Private Cloud to keep your privacy secure and also, the re-training of AI models happens in your VPC without the need of any human intervention.
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