Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...
This paper presents a case study on the application of data mining to the problem of detecting ecosystem disturbances from vegetation cover data obtained from satellite observatio...
Haibin Cheng, Pang-Ning Tan, Christopher Potter, S...
Intrusion detection, as a complementary mechanism to intrusion prevention, is necessary to secure wireless Mobile Ad hoc Networks (MANETs). In this paper we propose a practical age...
Hongmei Deng, Roger Xu, Frank Zhang, Chiman Kwan, ...
Most current anomaly Intrusion Detection Systems (IDSs) detect computer network behavior as normal or abnormal but cannot identify the type of attacks. Moreover, most current intr...
Abstract— The increasing computing and communication capabilities of multi-function devices (MFDs) have enabled networks of such devices to provide value-added services. This has...
Andres Quiroz, Manish Parashar, Nathan Gnanasamban...