Visible to the public The Burden of Artificial Intelligence on Internal Security Detection

TitleThe Burden of Artificial Intelligence on Internal Security Detection
Publication TypeConference Paper
Year of Publication2020
AuthorsHo, Tsung-Yu, Chen, Wei-An, Huang, Chiung-Ying
Conference Name2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET)
Keywordsartificial intelligence, artificial intelligence security, composability, Computer crime, DGA, Human Behavior, learning, Malware, Metrics, Prediction algorithms, Predictive models, pubcrawl, reliability, resilience, Resiliency, security
AbstractOur research team have devoted to extract internal malicious behavior by monitoring the network traffic for many years. We applied the deep learning approach to recognize the malicious patterns within network, but this methodology may lead to more works to examine the results from AI models production. Hence, this paper addressed the scenario to consider the burden of AI, and proposed an idea for long-term reliable detection in the future work.
Citation Keyho_burden_2020