Abstract
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)).
Original language | English |
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Title of host publication | Proceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017 |
Publisher | Association for Computing Machinery |
Number of pages | 8 |
ISBN (Electronic) | 9781450348447 |
DOIs | |
Publication status | Published - 19 Jul 2017 |
Externally published | Yes |
Event | 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 - Cambridge, United Kingdom Duration: 19 Jul 2017 → 20 Jul 2017 |
Publication series
Name | ACM International Conference Proceeding Series |
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Volume | Part F130522 |
Conference
Conference | 2017 International Conference on Future Networks and Distributed Systems, ICFNDS 2017 |
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Country/Territory | United Kingdom |
City | Cambridge |
Period | 19/07/17 → 20/07/17 |
Bibliographical note
Publisher Copyright:© 2017 Association for Computing Machinery.
Keywords
- Anomaly detection
- Behaviour profiling
- Bring your own device
- BYOD frameworks
- BYOD security issues
- Data mining
- Intelligent filtering
- Machine learning
- Network access control