1,497 research outputs found
CONSERVE: A framework for the selection of techniques for monitoring containers security
Context:\ua0Container-based virtualization is gaining popularity in different domains, as it supports continuous development and improves the efficiency and reliability of run-time environments.\ua0Problem:\ua0Different techniques are proposed for monitoring the security of containers. However, there are no guidelines supporting the selection of suitable techniques for the tasks at hand.\ua0Objective:\ua0We aim to support the selection and design of techniques for monitoring container-based virtualization environments.\ua0Approach: First, we review the literature and identify techniques for monitoring containerized environments. Second, we classify these techniques according to a set of categories, such as technical characteristic, applicability, effectiveness, and evaluation. We further detail the pros and cons that are associated with each of the identified techniques.\ua0Result:\ua0As a result, we present CONSERVE, a multi-dimensional decision support framework for an informed and optimal selection of a suitable set of container monitoring techniques to be implemented in different application domains.\ua0Evaluation:\ua0A mix of eighteen researchers and practitioners evaluated the ease of use, understandability, usefulness, efficiency, applicability, and completeness of the framework. The evaluation shows a high level of interest, and points out to potential benefits
MiniCPS: A toolkit for security research on CPS Networks
In recent years, tremendous effort has been spent to modernizing
communication infrastructure in Cyber-Physical Systems (CPS) such as Industrial
Control Systems (ICS) and related Supervisory Control and Data Acquisition
(SCADA) systems. While a great amount of research has been conducted on network
security of office and home networks, recently the security of CPS and related
systems has gained a lot of attention. Unfortunately, real-world CPS are often
not open to security researchers, and as a result very few reference systems
and topologies are available. In this work, we present MiniCPS, a CPS
simulation toolbox intended to alleviate this problem. The goal of MiniCPS is
to create an extensible, reproducible research environment targeted to
communications and physical-layer interactions in CPS. MiniCPS builds on
Mininet to provide lightweight real-time network emulation, and extends Mininet
with tools to simulate typical CPS components such as programmable logic
controllers, which use industrial protocols (Ethernet/IP, Modbus/TCP). In
addition, MiniCPS defines a simple API to enable physical-layer interaction
simulation. In this work, we demonstrate applications of MiniCPS in two example
scenarios, and show how MiniCPS can be used to develop attacks and defenses
that are directly applicable to real systems.Comment: 8 pages, 6 figures, 1 code listin
Securing Infrastructure-as-a-Service Public Clouds Using Security Onion
The shift to Cloud computing has brought with it its specific security challenges concerning the loss of control, trust and multi-tenancy especially in Infrastructure-as-a-Service (IaaS) Cloud model. This article focuses on the design and development of an intrusion detection system (IDS) that can handle security challenges in IaaS Cloud model using an open source IDS. We have implemented a proof-of-concept prototype on the most deployed hypervisor—VMware ESXi—and performed various real-world cyber-attacks, such as port scanning and denial of service (DoS) attacks to validate the practicality and effectiveness of our proposed IDS architecture. Based on our experimental results we found that our Security Onion-based IDS can provide the required protection in a reasonable and effective manner
Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study
Cloud computing has emerged as a popular paradigm and an attractive model for
providing a reliable distributed computing model.it is increasing attracting
huge attention both in academic research and industrial initiatives. Cloud
deployments are paramount for institution and organizations of all scales. The
availability of a flexible, free open source cloud platform designed with no
propriety software and the ability of its integration with legacy systems and
third-party applications are fundamental. Open stack is a free and opensource
software released under the terms of Apache license with a fragmented and
distributed architecture making it highly flexible. This project was initiated
and aimed at designing a secured cloud infrastructure called BradStack, which
is built on OpenStack in the Computing Laboratory at the University of
Bradford. In this report, we present and discuss the steps required in
deploying a secured BradStack Multi-node cloud infrastructure and conducting
Penetration testing on OpenStack Services to validate the effectiveness of the
security controls on the BradStack platform. This report serves as a practical
guideline, focusing on security and practical infrastructure related issues. It
also serves as a reference for institutions looking at the possibilities of
implementing a secured cloud solution.Comment: 38 pages, 19 figures
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
Simulating Windows-Based Cyber Attacks Using Live Virtual Machine Introspection
Static memory analysis has been proven a valuable technique for digital forensics. However, the memory capture technique halts the system causing the loss of important dynamic system data. As a result, live analysis techniques have emerged to complement static analysis. In this paper, a compiled memory analysis tool for virtualization (CMAT-V) is presented as a virtual machine introspection (VMI) utility to conduct live analysis during simulated cyber attacks. CMAT-V leverages static memory dump analysis techniques to provide live system state awareness. CMAT-V parses an arbitrary memory dump from a simulated guest operating system (OS) to extract user information, network usage, active process information and registry files. Unlike some VMI applications, CMAT-V bridges the semantic gap using derivation techniques. This provides increased operating system compatibility for current and future operating systems. This research demonstrates the usefulness of CMAT-V as a situational awareness tool during simulated cyber attacks and measures the overall performance of CMAT-V
A Security Monitoring Framework For Virtualization Based HEP Infrastructures
High Energy Physics (HEP) distributed computing infrastructures require
automatic tools to monitor, analyze and react to potential security incidents.
These tools should collect and inspect data such as resource consumption, logs
and sequence of system calls for detecting anomalies that indicate the presence
of a malicious agent. They should also be able to perform automated reactions
to attacks without administrator intervention. We describe a novel framework
that accomplishes these requirements, with a proof of concept implementation
for the ALICE experiment at CERN. We show how we achieve a fully virtualized
environment that improves the security by isolating services and Jobs without a
significant performance impact. We also describe a collected dataset for
Machine Learning based Intrusion Prevention and Detection Systems on Grid
computing. This dataset is composed of resource consumption measurements (such
as CPU, RAM and network traffic), logfiles from operating system services, and
system call data collected from production Jobs running in an ALICE Grid test
site and a big set of malware. This malware was collected from security
research sites. Based on this dataset, we will proceed to develop Machine
Learning algorithms able to detect malicious Jobs.Comment: Proceedings of the 22nd International Conference on Computing in High
Energy and Nuclear Physics, CHEP 2016, 10-14 October 2016, San Francisco.
Submitted to Journal of Physics: Conference Series (JPCS
Guardauto: A Decentralized Runtime Protection System for Autonomous Driving
Due to the broad attack surface and the lack of runtime protection, potential
safety and security threats hinder the real-life adoption of autonomous
vehicles. Although efforts have been made to mitigate some specific attacks,
there are few works on the protection of the self-driving system. This paper
presents a decentralized self-protection framework called Guardauto to protect
the self-driving system against runtime threats. First, Guardauto proposes an
isolation model to decouple the self-driving system and isolate its components
with a set of partitions. Second, Guardauto provides self-protection mechanisms
for each target component, which combines different methods to monitor the
target execution and plan adaption actions accordingly. Third, Guardauto
provides cooperation among local self-protection mechanisms to identify the
root-cause component in the case of cascading failures affecting multiple
components. A prototype has been implemented and evaluated on the open-source
autonomous driving system Autoware. Results show that Guardauto could
effectively mitigate runtime failures and attacks, and protect the control
system with acceptable performance overhead
IntelliFlow : um enfoque proativo para adicionar inteligência de ameaças cibernéticas a redes definidas por software
Orientador: Christian Rodolfo Esteve RothenbergDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Segurança tem sido uma das principais preocupações enfrentadas pela computação em rede principalmente, com o aumento das ameaças à medida que a Internet comercial e economias afins crescem rapidamente. Tecnologias de virtualização que permitem serviços em nuvem em escala colocam novos desafios para a segurança das infraestruturas computacionais, exigindo novos mecanismos que combinem o best-of-breed para reagir contra as metodologias de ataque emergentes. Nosso trabalho busca explorar os avanços na Cyber Threat Intelligence (CTI) no contexto da arquitetura de redes definidas por software, ou em inglês, Software Defined Networking (SDN). Enquanto a CTI representa uma abordagem recente para o combate de ameaças baseada em fontes confiáveis, a partir do compartihamento de informação e conhecimento sobre atividades criminais virtuais, a SDN é uma tendência recente na arquitetura de redes computacionais baseada em princípios de modulação e programabilidade. Nesta dissertação, nós propomos IntelliFlow, um sistema de detecção de inteligência para SDN que segue a abordagem proativa usando OpenFlow para efetivar contramedidas para as ameaças aprendidas a partir de um plano de inteligência distribuida. Nós mostramos a partir de uma implementação de prova de conceito que o sistema proposto é capaz de trazer uma série de benefícios em termos de efetividade e eficiência, contribuindo no plano geral para a segurança de projetos de computação de rede modernosAbstract: Security is a major concern in computer networking which faces increasing threats as the commercial Internet and related economies continue to grow. Virtualization technologies enabling scalable Cloud services pose further challenges to the security of computer infrastructures, demanding novel mechanisms combining the best-of-breed to counter certain types of attacks. Our work aims to explore advances in Cyber Threat Intelligence (CTI) in the context of Software Defined Networking (SDN) architectures. While CTI represents a recent approach to combat threats based on reliable sources, by sharing information and knowledge about computer criminal activities, SDN is a recent trend in architecting computer networks based on modularization and programmability principles. In this dissertation, we propose IntelliFlow, an intelligent detection system for SDN that follows a proactive approach using OpenFlow to deploy countermeasures to the threats learned through a distributed intelligent plane. We show through a proof of concept implementation that the proposed system is capable of delivering a number of benefits in terms of effectiveness and efficiency, altogether contributing to the security of modern computer network designsMestradoEngenharia de ComputaçãoMestre em Engenharia Elétrica159905/2013-3CNP
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