36,718 research outputs found
Understanding Security Threats in Cloud
As cloud computing has become a trend in the computing world, understanding its security concerns becomes essential for improving service quality and expanding business scale. This dissertation studies the security issues in a public cloud from three aspects. First, we investigate a new threat called power attack in the cloud. Second, we perform a systematical measurement on the public cloud to understand how cloud vendors react to existing security threats. Finally, we propose a novel technique to perform data reduction on audit data to improve system capacity, and hence helping to enhance security in cloud. In the power attack, we exploit various attack vectors in platform as a service (PaaS), infrastructure as a service (IaaS), and software as a service (SaaS) cloud environments. to demonstrate the feasibility of launching a power attack, we conduct series of testbed based experiments and data-center-level simulations. Moreover, we give a detailed analysis on how different power management methods could affect a power attack and how to mitigate such an attack. Our experimental results and analysis show that power attacks will pose a serious threat to modern data centers and should be taken into account while deploying new high-density servers and power management techniques. In the measurement study, we mainly investigate how cloud vendors have reacted to the co-residence threat inside the cloud, in terms of Virtual Machine (VM) placement, network management, and Virtual Private Cloud (VPC). Specifically, through intensive measurement probing, we first profile the dynamic environment of cloud instances inside the cloud. Then using real experiments, we quantify the impacts of VM placement and network management upon co-residence, respectively. Moreover, we explore VPC, which is a defensive service of Amazon EC2 for security enhancement, from the routing perspective. Advanced Persistent Threat (APT) is a serious cyber-threat, cloud vendors are seeking solutions to ``connect the suspicious dots\u27\u27 across multiple activities. This requires ubiquitous system auditing for long period of time, which in turn causes overwhelmingly large amount of system audit logs. We propose a new approach that exploits the dependency among system events to reduce the number of log entries while still supporting high quality forensics analysis. In particular, we first propose an aggregation algorithm that preserves the event dependency in data reduction to ensure high quality of forensic analysis. Then we propose an aggressive reduction algorithm and exploit domain knowledge for further data reduction. We conduct a comprehensive evaluation on real world auditing systems using more than one-month log traces to validate the efficacy of our approach
Evolution Oriented Monitoring oriented to Security Properties for Cloud Applications
Internet is changing from an information space to a dynamic computing
space. Data distribution and remotely accessible software
services, dynamism, and autonomy are prime attributes. Cloud technology
offers a powerful and fast growing approach to the provision
of infrastructure (platform and software services) avoiding the high
costs of owning, operating, and maintaining the computational
infrastructures required for this purpose. Nevertheless, cloud technology
still raises concerns regarding security, privacy, governance,
and compliance of data and software services offered through it.
Concerns are due to the difficulty to verify security properties of
the different types of applications and services available through
cloud technology, the uncertainty of their owners and users about
the security of their services, and the applications based on them,
once they are deployed and offered through a cloud. This work
presents an innovative and novel evolution-oriented, cloud-specific
monitoring model (including an architecture and a language) that
aim at helping cloud application developers to design and monitor
the behavior and functionality of their applications in a cloud
environment.Universidad de MĂĄlaga. Campus de Excelencia Internacional AndalucĂa Tech
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 Microsoftâs STRIDE threat model and discusses the stakeholders, the impact and recommendations for tackling each threat
The future of Cybersecurity in Italy: Strategic focus area
This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management
Privacy in the Genomic Era
Genome sequencing technology has advanced at a rapid pace and it is now
possible to generate highly-detailed genotypes inexpensively. The collection
and analysis of such data has the potential to support various applications,
including personalized medical services. While the benefits of the genomics
revolution are trumpeted by the biomedical community, the increased
availability of such data has major implications for personal privacy; notably
because the genome has certain essential features, which include (but are not
limited to) (i) an association with traits and certain diseases, (ii)
identification capability (e.g., forensics), and (iii) revelation of family
relationships. Moreover, direct-to-consumer DNA testing increases the
likelihood that genome data will be made available in less regulated
environments, such as the Internet and for-profit companies. The problem of
genome data privacy thus resides at the crossroads of computer science,
medicine, and public policy. While the computer scientists have addressed data
privacy for various data types, there has been less attention dedicated to
genomic data. Thus, the goal of this paper is to provide a systematization of
knowledge for the computer science community. In doing so, we address some of
the (sometimes erroneous) beliefs of this field and we report on a survey we
conducted about genome data privacy with biomedical specialists. Then, after
characterizing the genome privacy problem, we review the state-of-the-art
regarding privacy attacks on genomic data and strategies for mitigating such
attacks, as well as contextualizing these attacks from the perspective of
medicine and public policy. This paper concludes with an enumeration of the
challenges for genome data privacy and presents a framework to systematize the
analysis of threats and the design of countermeasures as the field moves
forward
- âŠ