A predictive model for risk and trust assessment in cloud computing: taxonomy and analysis for attack pattern detection

Cloud computing environments consist of many entities that have different roles, such as provider and customer, and multiple interactions amongst them. Trust is an essential element to develop confidence-based relationships amongst the various components in such a diverse environment. The current chapter presents the taxonomy of trust models and classification of information sources for trust assessment. Furthermore, it presents the taxonomy of risk factors in cloud computing environment. It analyses further the existing approaches and portrays the potential of enhancing trust development by merging trust assessment and risk assessment methodologies. The aim of the proposed solution is to combine information sources collected from various trust and risk assessment systems deployed in cloud services, with data related to attack patterns. Specifically, the approach suggests a new qualitative solution that could analyse each symptom, indicator, and vulnerability in order to detect the impact and likelihood of attacks directed at cloud computing environments. Therefore, possible implementation of the proposed framework might help to minimise false positive alarms, as well as to improve performance and security, in the cloud computing environment

Determining Training Needs for Cloud Infrastructure Investigations using I-STRIDE

As more businesses and users adopt cloud computing services, security vulnerabilities will be increasingly found and exploited. There are many technological and political challenges where investigation of potentially criminal incidents in the cloud are concerned. Security experts, however, must still be able to acquire and analyze data in a methodical, rigorous and forensically sound manner. This work applies the STRIDE asset-based risk assessment method to cloud computing infrastructure for the purpose of identifying and assessing an organization's ability to respond to and investigate breaches in cloud computing environments. An extension to the STRIDE risk assessment model is proposed to help organizations quickly respond to incidents while ensuring acquisition and integrity of the largest amount of digital evidence possible. Further, the proposed model allows organizations to assess the needs and capacity of their incident responders before an incident occurs.Comment: 13 pages, 3 figures, 3 tables, 5th International Conference on Digital Forensics and Cyber Crime; Digital Forensics and Cyber Crime, pp. 223-236, 201

Taxonomy of Technological IT Outsourcing Risks: Support for Risk Identification and Quantification

The past decade has seen an increasing interest in IT outsourcing as it promises companies many economic benefits. In recent years, IT paradigms, such as Software-as-a-Service or Cloud Computing using third-party services, are increasingly adopted. Current studies show that IT security and data privacy are the dominant factors affecting the perceived risk of IT outsourcing. Therefore, we explicitly focus on determining the technological risks related to IT security and quality of service characteristics associated with IT outsourcing. We conducted an extensive literature review, and thoroughly document the process in order to reach high validity and reliability. 149 papers have been evaluated based on a review of the whole content and out of the finally relevant 68 papers, we extracted 757 risk items. Using a successive refinement approach, which involved reduction of similar items and iterative re-grouping, we establish a taxonomy with nine risk categories for the final 70 technological risk items. Moreover, we describe how the taxonomy can be used to support the first two phases of the IT risk management process: risk identification and quantification. Therefore, for each item, we give parameters relevant for using them in an existing mathematical risk quantification model

DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments

With the growing popularity of cloud computing, the exploitation of possible vulnerabilities grows at the same pace; the distributed nature of the cloud makes it an attractive target for potential intruders. Despite security issues delaying its adoption, cloud computing has already become an unstoppable force; thus, security mechanisms to ensure its secure adoption are an immediate need. Here, we focus on intrusion detection and prevention systems (IDPSs) to defend against the intruders. In this paper, we propose a Distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP). Its goal is to make use of the resources in the cloud and provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks. We present the DCDIDP framework, whose infrastructure level is composed of three logical layers: network, host, and global as well as platform and software levels. Then, we review its components and discuss some existing approaches to be used for the modules in our proposed framework. Furthermore, we discuss developing a comprehensive trust management framework to support the establishment and evolution of trust among different cloud service providers. © 2011 ICST

Assessing database and network threats in traditional and cloud computing

Cloud Computing is currently one of the most widely-spoken terms in IT. While it offers a range of technological and financial benefits, its wide acceptance by organizations is not yet wide spread. Security concerns are a main reason for this and this paper studies the data and network threats posed in both traditional and cloud paradigms in an effort to assert in which areas cloud computing addresses security issues and where it does introduce new ones. This evaluation is based on Microsoft’s STRIDE threat model and discusses the stakeholders, the impact and recommendations for tackling each threat

Security challenges of small cell as a service in virtualized mobile edge computing environments

Research on next-generation 5G wireless networks is currently attracting a lot of attention in both academia and industry. While 5G development and standardization activities are still at their early stage, it is widely acknowledged that 5G systems are going to extensively rely on dense small cell deployments, which would exploit infrastructure and network functions virtualization (NFV), and push the network intelligence towards network edges by embracing the concept of mobile edge computing (MEC). As security will be a fundamental enabling factor of small cell as a service (SCaaS) in 5G networks, we present the most prominent threats and vulnerabilities against a broad range of targets. As far as the related work is concerned, to the best of our knowledge, this paper is the first to investigate security challenges at the intersection of SCaaS, NFV, and MEC. It is also the first paper that proposes a set of criteria to facilitate a clear and effective taxonomy of security challenges of main elements of 5G networks. Our analysis can serve as a staring point towards the development of appropriate 5G security solutions. These will have crucial effect on legal and regulatory frameworks as well as on decisions of businesses, governments, and end-users

Medical Cyber-Physical Systems Development: A Forensics-Driven Approach

The synthesis of technology and the medical industry has partly contributed to the increasing interest in Medical Cyber-Physical Systems (MCPS). While these systems provide benefits to patients and professionals, they also introduce new attack vectors for malicious actors (e.g. financially-and/or criminally-motivated actors). A successful breach involving a MCPS can impact patient data and system availability. The complexity and operating requirements of a MCPS complicates digital investigations. Coupling this information with the potentially vast amounts of information that a MCPS produces and/or has access to is generating discussions on, not only, how to compromise these systems but, more importantly, how to investigate these systems. The paper proposes the integration of forensics principles and concepts into the design and development of a MCPS to strengthen an organization's investigative posture. The framework sets the foundation for future research in the refinement of specific solutions for MCPS investigations.Comment: This is the pre-print version of a paper presented at the 2nd International Workshop on Security, Privacy, and Trustworthiness in Medical Cyber-Physical Systems (MedSPT 2017

Secure Cloud-Edge Deployments, with Trust

Assessing the security level of IoT applications to be deployed to heterogeneous Cloud-Edge infrastructures operated by different providers is a non-trivial task. In this article, we present a methodology that permits to express security requirements for IoT applications, as well as infrastructure security capabilities, in a simple and declarative manner, and to automatically obtain an explainable assessment of the security level of the possible application deployments. The methodology also considers the impact of trust relations among different stakeholders using or managing Cloud-Edge infrastructures. A lifelike example is used to showcase the prototyped implementation of the methodology