Intrusion detection attack patterns in cloud computing: trust and risk assessment

Chrysikos, Alexandros (2018) Intrusion detection attack patterns in cloud computing: trust and risk assessment. In: The 12th Advanced Summer School on Service-Oriented Computing, June 24 - June 29 2018, Hersonissos, Crete, Greece.

[img]
Preview
Text (IBM Research Report Papers From the 12th Advanced Summer School on Service-Oriented Computing (SummerSOC’18))
Intrusion-Detection-Attack-Patterns-in-Cloud-Computing-Trust-and-Risk-Assessment.pdf - Accepted Version

Download (381kB) | Preview
Official URL: https://domino.research.ibm.com/library/cyberdig.n...

Abstract / Description

Dependence on cloud services has been steadily increasing in recent years, as cloud services are an attractive option to offer flexibility and cost effectiveness through economies of scale. Cloud services are also exposed to security incidents, such as data breaches and other malicious activities. To mitigate risks to the confidentiality, integrity, and availability of assets, but also minimise loss to cloud service providers and users, the attack trust and risk elements need to be identified, classified, and prioritised. The aim of the proposed conceptual framework is to combine trust and risk assessment sources with data of risk assessment related to each attack pattern. This novel approach is a new qualitative solution to examine and determine symptoms, indicators, and vulnerabilities to detect the impact and likelihood of distributed attacks directed at cloud computing environments. The proposed framework might help to reduce false positive alarms and improve performance in Intrusion Detection Systems.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cloud computing, Trust Assessment, Risk Assessment, Attack Pattern, IDS, Ontology
Subjects: 000 Computer science, information & general works
Department: School of Computing and Digital Media
Depositing User: Alexandros Chrysikos
Date Deposited: 21 Nov 2018 16:30
Last Modified: 21 Nov 2018 16:30
URI: http://repository.londonmet.ac.uk/id/eprint/3884

Actions (login required)

View Item View Item