State of the art deep learning algorithms are susceptible to adversarial input which cause them malfunction with high confidence. This would become a serious threat for classification algorithms deployed by intrusion detection, anomaly detection, and scene analysis system. We examine the robustness of machine learning algorithms and design defense mechanisms.
A complex vector attack includes a sequence of temporally and spatially separated actions that each can evade detection systems but as a whole they constitute a powerful attack. Mitigation of such attacks require deployment of intelligent and customized technologies at premise that is fine tuned and tailored to the customer specifics.
Cybermatix offers fully customized solutions that combine artificial intelligence with cyber analysis. Our goal is not to replace a human analyst but to build a virtual assistant that can automate the analysis and reduce the work load. VCA can help in prediction and diagnosis and provide reasoning.
Signature based static malware analysis algorithms are not effective in detecting modern malware. Dynamic analysis is more reliable but also more complicated and time consuming. Cybermatix builds solutions that reduce the overhead and provide speed.
We provide novel technologies to detect stolen information from deep-web as well as monitoring suspicious behavior of cybercriminals. Our technology allows us to solve complex problems which are specific to deep-web environments.