TY - GEN
T1 - Cybersecurity
T2 - 1st International Conference on Intelligent Cloud Computing, ICC 2019
AU - Elsaid, Shaimaa Ahmed
AU - Maeeny, Samerah
AU - Alenazi, Azhar
AU - Alenazi, Tahani
AU - Alzaid, Wafa
AU - Algahtani, Ghada
AU - Aldossari, Amjad
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Cyber security [1, 2] addresses several important issues in network security and performance including intrusion detection, cipher design, security overhead analysis, and tracing. In this article, an intrusion detection and prevention system (IDPS) is proposed and implemented using SNORT and Security Onion tools to detect and prevent anomaly intrusion; misuse of protocol and service ports, DoS based on crafted payloads, DoS based on volume (DDoS), buffer overflow or other cyber-attacks. The proposed system monitors the network or system activities, finds if any malicious operations occur and then prevents it. To show the efficiency of the proposed system, experiments have been done on numerous anomaly intrusion attacks using KDD database. The experimental results yield 96% detection accuracy. The detection and prevention processes take less than 3 s. The results show the feasibility of the methodology followed in this paper under different attack conditions and show the high robustness of the proposed system.
AB - Cyber security [1, 2] addresses several important issues in network security and performance including intrusion detection, cipher design, security overhead analysis, and tracing. In this article, an intrusion detection and prevention system (IDPS) is proposed and implemented using SNORT and Security Onion tools to detect and prevent anomaly intrusion; misuse of protocol and service ports, DoS based on crafted payloads, DoS based on volume (DDoS), buffer overflow or other cyber-attacks. The proposed system monitors the network or system activities, finds if any malicious operations occur and then prevents it. To show the efficiency of the proposed system, experiments have been done on numerous anomaly intrusion attacks using KDD database. The experimental results yield 96% detection accuracy. The detection and prevention processes take less than 3 s. The results show the feasibility of the methodology followed in this paper under different attack conditions and show the high robustness of the proposed system.
KW - Anomaly detection
KW - Cyber security
KW - Intrusion Detection System (IDS)
KW - Intrusion Prevention System (IPS)
KW - Security onion
KW - SNORT
UR - http://www.scopus.com/inward/record.url?scp=85087166932&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-36365-9_3
DO - 10.1007/978-3-030-36365-9_3
M3 - Conference contribution
AN - SCOPUS:85087166932
SN - 9783030363642
T3 - Communications in Computer and Information Science
SP - 15
EP - 42
BT - Advances in Data Science, Cyber Security and IT Applications - 1st International Conference on Computing, ICC 2019, Proceedings
A2 - Alfaries, Auhood
A2 - Mengash, Hanan
A2 - Yasar, Ansar
A2 - Shakshuki, Elhadi
PB - Springer
Y2 - 10 December 2019 through 12 December 2019
ER -