TY - GEN
T1 - Developing an intelligent filtering technique for bring your own device network access control
AU - Muhammad, Musa Abubakar
AU - Ayesh, Aladdin
AU - Zadeh, Pooneh Bagheri
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/7/19
Y1 - 2017/7/19
N2 - With the rapid increase in smartphones and tablets, Bring Your Own Devices (BYOD) has simplified computing by introducing the use of personally owned devices. These devices can be utilised in accessing business enterprise contents and networks. The effectiveness of BYOD offers several business benefits like employee job satisfaction, increased job efficiency and ?exibility. However, allowing employees to bring their own devices could lead to a plethora of security issues; like data the unauthorised access and data leakage. this paper investigates the current security approaches and how organisations can leverage on these techniques regarding policies, risks and existing security techniques to mitigate or halt the security challenges. This research aimed to fill up the access control gap in the BYOD environment by developing an Intelligent Filtering Technique (IFT) using Artificial Intelligence (AI) Technique. Based on the behavioural patterns of device packets Inter-Arrival-Time (IAT) features through network traffic flow packet headers (Such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP) and Internet Control Messaging Protocol (ICMP)).
AB - With the rapid increase in smartphones and tablets, Bring Your Own Devices (BYOD) has simplified computing by introducing the use of personally owned devices. These devices can be utilised in accessing business enterprise contents and networks. The effectiveness of BYOD offers several business benefits like employee job satisfaction, increased job efficiency and ?exibility. However, allowing employees to bring their own devices could lead to a plethora of security issues; like data the unauthorised access and data leakage. this paper investigates the current security approaches and how organisations can leverage on these techniques regarding policies, risks and existing security techniques to mitigate or halt the security challenges. This research aimed to fill up the access control gap in the BYOD environment by developing an Intelligent Filtering Technique (IFT) using Artificial Intelligence (AI) Technique. Based on the behavioural patterns of device packets Inter-Arrival-Time (IAT) features through network traffic flow packet headers (Such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP) and Internet Control Messaging Protocol (ICMP)).
KW - Anomaly detection
KW - Behaviour profiling
KW - Bring your own device
KW - BYOD frameworks
KW - BYOD security issues
KW - Data mining
KW - Intelligent filtering
KW - Machine learning
KW - Network access control
UR - http://www.scopus.com/inward/record.url?scp=85030455592&partnerID=8YFLogxK
U2 - 10.1145/3102304.3105573
DO - 10.1145/3102304.3105573
M3 - Published conference contribution
AN - SCOPUS:85030455592
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
PB - Association for Computing Machinery
T2 - 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017
Y2 - 19 July 2017 through 20 July 2017
ER -