Search

Software systems are invariably vulnerable to exploits, thus the need to assess their security in order to quantify the associated risk their usage entails. However, existing vulnerability assessment approaches e.g., vulnerability analyzers, have two major constraints: (a) they need the system to be already deployed to perform the analysis and, (b) they do not consider the criticality of the system within the business processes of the organization. As a result, many users, in particular small and medium-sized enterprizes are often unaware about assessing the actual technical and economical impact of vulnerability exploits in their own organizations, before the actual system's deployment. Drawing upon threat modeling techniques (i.e., attack trees), we propose a user-centric methodology to quantitatively perform a software configuration's security assessment based on (i) the expected economic impact associated with compromising the system's security goals and, (ii) a method to rank available configurations with respect to security. This paper demonstrates the feasibility and usefulness of our approach in a real-world case study based on the Amazon EC2 service. Over 2000 publicly available Amazon Machine Images are analyzed and ranked with respect to a specific business profile, before deployment in the Amazon's Cloud. © 2014 Springer International Publishing Switzerland.

Because the Internet of Things (IoT) pervasively extends to all facets of life, the "things" are increasingly extending to include the interconnection of the Internet to critical infrastructures (CIs) such as telecommunication, power grid, transportation, e-commerce systems, and others. The objective of this paper is twofold: (i) addressing IoT from a CI protection (CIP) and connectivity viewpoint, and (ii) highlighting the need for security quantification to improve the quality of protection (QoP) of CIs. Using a financial infrastructure as an example, a CIP and trust quantification perspective is built up. To this end, we are developing a novel security metrics-based approach to assess and thereon enhance the CIP. We focus on the communication level of the CI where IoT is playing an increasingly important role with respect to sensing and communication across CI elements. Determining the security and dependability level of the communication over the CI constitutes a basic precondition for assessing the QoP of the whole CI, which is needed for any efforts to improve this QoP. Because metrics play a central role for such quantification, this paper develops their QoP use from an IoT perspective, and a reference implementation along with experimental results is presented.

Multiple databases and repositories exist for collecting known vulnerabilities for different systems and on different levels. However, it is not unusual that extensive time elapses, in some cases more than a year, in order to collect all information needed to perform/publish vulnerability scoring calculations for security management groups to assess and prioritize vulnerabilities for remediation. Scoring a vulnerability also requires broad knowledge about its characteristics, which is not always provided. As an alternative, this paper targets the quantitative understanding of security vulnerabilities in the context of insufficient vulnerability information. We propose a novel approach for the predictive assessment of security vulnerabilities, taking into consideration the relevant scenarios, e.g., zero day vulnerabilities, for which there is limited or no information to perform a typical vulnerability scoring. We propose a new analytical model, the Vulnerability Assessment Model (VAM), which is inspired by the Linear Discriminant Analysis and uses publicly available vulnerability databases such as the National Vulnerability Database (NVD) as a training data set. To demonstrate the applicability of our approach, we have developed a publicly available web application, the VAM Calculator. The experimental results obtained using real-world vulnerability data from the three most widely used Internet browsers show that by reducing the amount of required vulnerability information by around 50%, we can maintain the misclassification rate at approximately 5%. © 2013 IEEE.

Vulnerability exploits cost organizations large amounts of resources, mainly due to disruption of ICT services, and thus loss of confidentiality, integrity and availability. As security managers in the industry usually have to operate with limited budgets allocated to information security, they need to prioritize their investment efforts regarding the response mechanisms to the existing vulnerabilities. The utilization of quantitative security vulnerability assessment methods enables efficient prioritization of security efforts and investments to mitigate the discovered vulnerabilities and thus an opportunity to lower expected losses. State of the art approaches for vulnerability assessment such as the Common Vulnerability Scoring System (CVSS), which is the de facto standard quantifying the severity of vulnerabilities, do not consider the economic impact in case of a vulnerability exploit. To this end, our paper targets the quantitative understanding of vulnerability severity taking into account the potential economic damage a successful vulnerability exploit can cause. We propose a novel approach for a systematic consideration of the relevant cost units (associated costs) for the economic damage estimation of vulnerability exploits. Our approach utilizes Multiple Criteria Decision Analysis (MCDA) methods to perform a prioritization of the existing vulnerabilities within the target system. The evaluation results show the potential cost savings w.r.t. the mitigation costs using our approach. Our method supports managers and decision makers in the process of prioritizing security investments to mitigate the discovered vulnerabilities. © 2013 IEEE.

The cloud paradigm, based on the idea of delegating to the network any kind of computational resources, is showing a considerable success. The estimated trend is that the number of different cloud-based solutions, approaches, and service providers (CSP) will continue growing. Despite the big number of different cloud solutions that currently exist, most of them are "walled gardens" unable to interoperate. On the other side, a large effort is taking place in the cloud community to develop and identify open solutions and standards. In such a context the concept of cloud federation, an architecture that combines the functionalities of different CSP, is a hot topic. This chapter presents an overview of the cloud federation topic, with special focus on its most important security challenges. Furthermore, it proposes a taxonomy of possible approaches to federation. Then it proposes a comparison of security problems in cloud and grid environment, and a detailed analysis of two relevant security problems, identity management and Cyber Attacks analysis, trying to outline how they can be applied in a federated context. © 2012, IGI Global.

The CoMiFin framework can be considered as a highly dynamic controlled system that evolves over time according to SR interactions and the event processing activities performed within SRs. SR event processing requires the ability to allocate and manage online the resources that are necessary for the processing itself, and for meeting the SR business level objectives. These objectives are usually specified in the SR contracts as service level agreements. Accordingly, it is crucial to continuously monitor the operation of the CoMiFin framework in order to ensure its compliance with the specifications of the expected behavior. This chapter describes an efficient monitoring system that (a) collects vital infrastructure metrics (e.g., CPU/memory utilization) and application data (e.g., the number of processed events) from the set of resources and services used for event processing purposes, and (b) processes those metrics to detect violations of the SR contract. The monitoring architecture is model-driven so that changes in the resources or the system objectives can be automatically mapped to monitoring assets. It is implemented in a plugin-based fashion, which enables the flexible extension of evaluation features to capture the complex behavior of the system. © Springer-Verlag Berlin Heidelberg 2012.

The users of Cloud Service Providers (CSP) often motivate their choice of providers based on criteria such as the offered service level agreements (SLA) and costs, and also recently based on security aspects (i.e., due to regulatory compliance). Unfortunately, it is quite uncommon for a CSP to specify the security levels associated with their services, hence impeding users from making security relevant informed decisions. Consequently, while the many economic and technological advantages of Cloud computing are apparent, the migration of key sector applications has been limited, in part, due to the lack of security assurance on the CSP. In order to achieve this assurance and create trustworthy Cloud ecosystems, it is desirable to develop metrics and techniques to compare, aggregate, negotiate and predict the trade-offs (features, problems and the economics) of security. This paper contributes with a quantitative security assessment case study using the CSP information found on the Cloud Security Alliance's Security, Trust & Assurance Registry (CSA STAR). Our security assessment rests on the notion of Cloud Security Level Agreements - SecLA - and, a novel set of security metrics used to quantitatively compare SecLAs.

Cloud computing is redefining the on-demand usage of remotely-located, and highly available computing resources to the user. Unfortunately, while the many economic and technological advantages are apparent, the migration of key sector applications to the Cloud has been limited due to a major show-stopper: the paucity of quantifiable metrics to evaluate the tradeoffs (features, problems and the economics) of security. Despite the obvious value ofmetrics in different scenarios to evaluate such tradeoffs, a formal and standard-based approach for the addressing of security metrics in the Cloud is a much harder and very much an open issue. This paper presents our views on the importance and challenges for developing a security metrics framework for the Cloud, also taking into account our ongoing research with organizations like the Cloud Security Alliance and European projects like ABC4Trust, CoMiFin and INSPIRE. This paper also introduces the basic building blocks of a proposed security metrics framework for elements such as a Cloud provider's security assessment, taking into account the different service and deployment models of the Cloud.