Abstract: Disclosed herein are systems and methods for automatically mitigating potential network services attacks based on service usage patterns learned using Machine Learning (ML) comprising, collecting operational data indicative of resource utilization of one or more network services serving a plurality of connections and of a plurality of operational factors of the plurality of connections, detecting degradation of the network service(s) based on analysis of the operational data, applying trained ML model(s) to the operational data in order to identify negative operational factor(s) of one or more suspected connections to the network service estimated to induce the degradation where the one or more ML model is trained to predict an impact pattern induced by each of a plurality of operational factors on the resource utilization of the one or more network services, and disconnecting, at least temporarily, the suspected connection(s) from the network service(s).

Abstract: Provided herein are systems and methods for configuring a segmented cloud based network based on separate Internet Protocol (IP) segments, comprising receiving instructions to create one or more additional private virtual networks as respective additional segments in a multi-tenant multi-regional cloud based network segmented to a plurality of segments each mapped by a respective IP address range, calculating one or more non-conflicting new IP address range based on analysis of the IP address range of each of the segments, allocating a respective new IP address range to each additional segment, and deploying automatically one or more gateways. The gateways are configured to connect one or more client devices to the additional segment(s) by assigning each client device an IP address in the respective new IP address range and routing network packets between the client devices and the respective additional segment according to mapping of the respective new IP address range.