TY - JOUR
T1 - Feature Selection of Denial-of-Service Attacks Using Entropy and Granular Computing
AU - Khan, Suleman
AU - Gani, Abdullah
AU - Wahid Abdul Wahab, Ainuddin
AU - Singh, Prem Kumar
PY - 2018/2/1
Y1 - 2018/2/1
N2 - Recently, many researchers have paid attention toward denial of services (DoS) and its malicious handling. The Intrusion detection system is one of the most common detection techniques used to detect malicious attack which attempts to compromise the security goals. To deal with such an issue, some of the researchers have used entropy calculation recently to detect malicious attacks. However, it fails to identify the most potential feature for DoS attack which needs to be addressed on its early occurrence. Therefore, this paper focused on identifying some of the potential attributes of a DoS attack based on computed weight for each of the attributes using entropy calculation. In addition, the selection of potential attributes based on user-defined chosen granulation is also given using NSL KDD dataset.
AB - Recently, many researchers have paid attention toward denial of services (DoS) and its malicious handling. The Intrusion detection system is one of the most common detection techniques used to detect malicious attack which attempts to compromise the security goals. To deal with such an issue, some of the researchers have used entropy calculation recently to detect malicious attacks. However, it fails to identify the most potential feature for DoS attack which needs to be addressed on its early occurrence. Therefore, this paper focused on identifying some of the potential attributes of a DoS attack based on computed weight for each of the attributes using entropy calculation. In addition, the selection of potential attributes based on user-defined chosen granulation is also given using NSL KDD dataset.
KW - Intrusion detection systems
KW - DoS attack
KW - Entropy
U2 - 10.1007/s13369-017-2634-8
DO - 10.1007/s13369-017-2634-8
M3 - Article
VL - 43
SP - 499
EP - 508
JO - Arabian Journal for Science and Engineering
JF - Arabian Journal for Science and Engineering
SN - 2193-567X
IS - 2
ER -