Wherever You Are Find Full Visibility Of Your Network And Endpoints
In recent times cyber-criminal groups are known for their innovative multistaged attacks. Their attacks are focused on the core banking systems, the trading platforms, and ATMs.
Our engineers at SB Analytics are proficient in developing applications based on artificial intelligence to model a strategic intelligence framework for the identification and mitigation of these attacks deployed in the area of cyber security.
Our objective is to assemble a comprehensive strategic threat intelligence system that provides answers to the ever-evolving cyber-attacks targeted.
Our threat intelligence model strategically adapts relevant data to estimate the risks, prioritize the threats and thereafter prepare for the new threats, providing critical information that is tailored, analytical and verified to the organization.
As an AI development company, we understand the need for cyber threat intelligence solutions to adopt strategic, and advanced detection response models, to meet the cybersecurity needs of today.
In recent years, cybercriminal groups have grown smarter to scale up their activities and avoid threat detection with the use of multi-staged threats ranging from Denial of Service (DoS) attacks to www attacks, Structured Query Language (SQL) Injections, Stealth scanning techniques, Coordinated distributed denial of service (DDoS) attacks, Botnets attacks, Mobile malware attacks, and more.
After that, once all the relevant raw data has been gathered, sorted, and organized, as AI consultants we use Natural Language Processing (NLP) and machine learning techniques to analyze materials from a myriad of unorganized data sources over various programming languages to categorize them using ontologies and actions, independent of language that helps to equip our analysts to execute more robust and intelligent searches beyond simple key phrases and tags using rules of correlation. This way the feedback loop enables the threat intelligence process to become dynamic rather than static by using feedback from analysts and other stakeholders to add context and re-evaluate the ingested data sources both internally and externally to create a foolproof system.
We help create a digital immune system to avoid cyber disruptions, without impacting the regular business operations of our customers.
Here Are Some Of The Benefits Of Using AI In Cybersecurity
- Risk and Compliance Management
- Data Loss Prevention
- Unified Threat Management
- Security and Vulnerability Management
- Antivirus/Antimalware
- Fraud Detection/Anti-Fraud
- Intrusion Detection