Journal ArticleDOI
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Anna L. Buczak,Erhan Guven +1 more
TLDR
The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/ DM for cyber security is presented, and some recommendations on when to use a given method are provided.Abstract:
This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection. Short tutorial descriptions of each ML/DM method are provided. Based on the number of citations or the relevance of an emerging method, papers representing each method were identified, read, and summarized. Because data are so important in ML/DM approaches, some well-known cyber data sets used in ML/DM are described. The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/DM for cyber security is presented, and some recommendations on when to use a given method are provided.read more
Citations
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Architectural Tactics for Big Data Cybersecurity Analytic Systems: A Review
Faheem Ullah,M. Ali Babar +1 more
TL;DR: In this paper, a systematic review aimed at identifying the most frequently reported quality attributes and architectural tactics for Big Data Cybersecurity Analytic Systems was conducted, which revealed that despite the significance of interoperability, modifiability, adaptability, generality, stealthiness, and privacy assurance, these quality attributes lack explicit architectural support in the literature.
Journal ArticleDOI
Survey of Public Safety Communications: User-Side and Network-Side Solutions and Future Directions
TL;DR: A layered structure is designed, consisting of the public safety service layer, time-critical information delivery layer, and physical object layer, from which to consider the public health system and its key components, and extensively review research efforts on both D2D and DWN as complimentary user-side and network-side communication techniques toward effective public safety communications.
Journal ArticleDOI
Network intrusion detection based on deep learning model optimized with rule-based hybrid feature selection
Femi Emmanuel Ayo,Sakinat Oluwabukonla Folorunso,Adebayo Abayomi-Alli,Adebola Olayinka Adekunle,Joseph Bamidele Awotunde +4 more
TL;DR: Results proved that the proposed NIDS based on deep learning model optimized with rule-based hybrid feature selection outperforms other related methods with reduction of false alarm rate, high accuracy rate, reduced training and testing time and is suitable for attack classification in NIDS.
Journal ArticleDOI
Towards Near-Real-Time Intrusion Detection for IoT Devices using Supervised Learning and Apache Spark
TL;DR: A hybrid approach for the detection of SYN-DOS cyber-attacks on IoT devices is proposed: the application of an explicit Random Forest model, implemented directly on the IoT device, along with a second level analysis performed in the Cloud.
Journal ArticleDOI
A Survey on Cyber Physical System Security for IoT: Issues, Challenges, Threats, Solutions
TL;DR: This paper analyzes security issues, threats, and solutions for IoT-CPS, and addresses the CPS vulnerabilities and attacks, and recommends solutions for each system of CPS security threats.
References
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