Cybersecurity as a Service

• URL: http://arxiv.org/abs/2402.13965v1
• Date: Wed, 21 Feb 2024 17:49:53 GMT
• Title: Cybersecurity as a Service
• Authors: John Morris, Stefan Tatschner, Michael P. Heinl, Patrizia Heinl, Thomas Newe, Sven Plaga,
• Abstract summary: This chapter gives an overview of common cybersecurity as a service functions and their providers. It provides guidance especially for small- and medium-sized businesses, for asking the appropriate questions when it comes to the selection of a specific MSSP.
• Score: 0.43981305860983705
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the increasing sophistication and sheer number of cyberattacks, more and more companies come to the conclusion that they have to strengthen their cybersecurity posture. At the same time, well-educated Information technology (IT) security personnel are scarce. Cybersecurity as a service (CSaaS) is one possible solution to tackle this problem by outsourcing security functions to managed security service providers (MSSP). This chapter gives an overview of common CSaaS functions and their providers. Moreover, it provides guidance especially for small- and medium-sized businesses, for asking the appropriate questions when it comes to the selection of a specific MSSP.

Related papers

• We need to aim at the top: Factors associated with cybersecurity awareness of cyber and information security decision-makers [0.0]
  We study cybersecurity awareness of cyber and information security decision-makers. Our findings indicate that awareness of well-known threats and solutions seems to be quite low for individuals in decision-making roles.
  arXiv  Detail & Related papers  (2024-04-06T20:32:19Z)
• The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective [64.36680481458868]
  Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge. This paper provides a survey of security and privacy in MEC from the perspective of Artificial Intelligence (AI) We focus on new security and privacy issues, as well as potential solutions from the viewpoints of AI.
  arXiv  Detail & Related papers  (2024-01-03T07:47:22Z)
• A Systematization of Cybersecurity Regulations, Standards and Guidelines for the Healthcare Sector [5.121113572240309]
  This paper contributes a systematization of the significant cybersecurity documents relevant to the healthcare sector. We collected the 49 most significant documents and used the NIST cybersecurity framework to categorize key information.
  arXiv  Detail & Related papers  (2023-04-28T16:19:21Z)
• Graph Mining for Cybersecurity: A Survey [61.505995908021525]
  The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Traditional Machine Learning (ML) based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities. With the proliferation of graph mining techniques, many researchers investigated these techniques for capturing correlations between cyber entities and achieving high performance.
  arXiv  Detail & Related papers  (2023-04-02T08:43:03Z)
• Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022 [55.573187938617636]
  The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
  arXiv  Detail & Related papers  (2022-02-28T18:27:41Z)
• A System for Automated Open-Source Threat Intelligence Gathering and Management [53.65687495231605]
  SecurityKG is a system for automated OSCTI gathering and management. It uses a combination of AI and NLP techniques to extract high-fidelity knowledge about threat behaviors.
  arXiv  Detail & Related papers  (2021-01-19T18:31:35Z)
• Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
  Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance. We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems. We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
  arXiv  Detail & Related papers  (2020-10-19T13:09:31Z)
• Elicitation of SME Requirements for Cybersecurity Solutions by Studying Adherence to Recommendations [1.138723572165938]
  Small and medium-sized enterprises (SME) have become the weak spot of our economy for cyber attacks. One of the reasons for why many SME do not adopt cybersecurity is that developers of cybersecurity solutions understand little the SME context. This poster describes the challenges of SME regarding cybersecurity and introduces our proposed approach to elicit requirements for cybersecurity solutions.
  arXiv  Detail & Related papers  (2020-07-16T08:36:40Z)
• Automating the Communication of Cybersecurity Knowledge: Multi-Case Study [1.138723572165938]
  This paper explores an alternative do-it-yourself (DIY) approach to bringing cybersecurity to small businesses. Our method implements the Self-Determination Theory (SDT) guide and motivate to adopt good cybersecurity practices. The results of this study indicate that automated counselling can help many SMB in security adoption.
  arXiv  Detail & Related papers  (2020-07-15T10:30:20Z)
• Secure Byzantine-Robust Machine Learning [61.03711813598128]
  We propose a secure two-server protocol that offers both input privacy and Byzantine-robustness. In addition, this protocol is communication-efficient, fault-tolerant and enjoys local differential privacy.
  arXiv  Detail & Related papers  (2020-06-08T16:55:15Z)
• Cyber Security Incident Handling, Warning and Response System for the European Critical Information Infrastructures (CyberSANE) [0.29005223064604074]
  This paper aims to enhance the security and resilience of Critical Information Infrastructures (CIIs) by providing a dynamic collaborative, warning and response system (CyberSANE system) The proposed solution provides a first of a kind approach for handling cyber security incidents in the digital environments with highly interconnected, complex and diverse nature.
  arXiv  Detail & Related papers  (2020-03-11T15:25:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.