Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Practical Machine Learning for Cloud Intrusion Detection: Challenges and
  the Way Forward   Operationalizing machine learning based security detections is extremely
challenging, especially in a continuously evolving cloud environment.
Conventional anomaly detection does not produce satisfactory results for
analysts that are investigating security incidents in the cloud. Model
evaluation alone presents its own set of problems due to a lack of benchmark
datasets. When deploying these detections, we must deal with model compliance,
localization, and data silo issues, among many others. We pose the problem of
"attack disruption" as a way forward in the security data science space. In
this paper, we describe the framework, challenges, and open questions
surrounding the successful operationalization of machine learning based
security detections in a cloud environment and provide some insights on how we
have addressed them.

13
The categories of this paper are: quant-ph
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
3
The categories of this paper are: physics