Reconciling malware labeling discrepancy via consensus learning
Ting Wang, Xin Hu, et al.
ICDEW 2014
Consider the problem of reliable multicast over a network in the presence of adversarial errors. In contrast to traditional network error correction codes designed for a given network capacity and a given number of errors, we study an arguably more realistic setting that prior knowledge on the network and adversary parameters is not available. For this setting we propose efficient and throughput-optimal error correction schemes, provided that the source and terminals share randomness that is secret form the adversary. We discuss an application of cryptographic pseudorandom generators to efficiently produce the secret randomness, provided that a short key is shared between the source and terminals. Finally we present a secure key distribution scheme for our network setting.
Ting Wang, Xin Hu, et al.
ICDEW 2014
Xin Hu, Jiyong Jang, et al.
IBM J. Res. Dev
Ting Wang, Shicong Meng, et al.
CIKM 2014
Wei Gao, Yong Li, et al.
ICNP 2014