Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Threat Detection for General Social Engineering Attack Using Machine
  Learning Techniques   This paper explores the threat detection for general Social Engineering (SE)
attack using Machine Learning (ML) techniques, rather than focusing on or
limited to a specific SE attack type, e.g. email phishing. Firstly, this paper
processes and obtains more SE threat data from the previous Knowledge Graph
(KG), and then extracts different threat features and generates new datasets
corresponding with three different feature combinations. Finally, 9 types of ML
models are created and trained using the three datasets, respectively, and
their performance are compared and analyzed with 27 threat detectors and 270
times of experiments. The experimental results and analyses show that: 1) the
ML techniques are feasible in detecting general SE attacks and some ML models
are quite effective; ML-based SE threat detection is complementary with
KG-based approaches; 2) the generated datasets are usable and the SE domain
ontology proposed in previous work can dissect SE attacks and deliver the SE
threat features, allowing it to be used as a data model for future research.
Besides, more conclusions and analyses about the characteristics of different
ML detectors and the datasets are discussed.

19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat