Though hacking of any kind is always costly. We already have existing anti-hacking methodologies for Network, Internet, & OS hacking, Phishing, Steganography, Social Engineering Attack, DOS Attack, Fake Emails, Session Hijacking, and SQL Injection. But evolution of AI created new challenges. Centroid of AI is the machine learning. Machine is trained on data set. Just think and consider you data set is hacked. Even a single bit will train machine in unexpected output. Machine learning is used to detect and track possible incoming threats. If machine is itself corrupt then nothing can be said. We cover predictive cyber security based on machine learning algorithms and data science. Though we use traditional cyber security methodologies to collect data for SIEM (Security Information and Event Management), VPN, Proxy, Flow, Endpoint, and LDAP. We include UEBA(User and Entity Behavior Analytics) to analyse about Registration, Logins, Transactions, and Logouts. Our overall analysis covers Corporate Data, Financial Data, Customer Data, and Personally Identifiable Data.
Key features include the following,
- Data Integration
- Baseline Creation
- Data Insights
- Visualization
- Finding Alerts and Anomalies
We are reinventing ourself to a better version, stay tuned!