22,288 research outputs found
Analyzing audit trails in a distributed and hybrid intrusion detection platform
Efforts have been made over the last decades in order to design and perfect Intrusion
Detection Systems (IDS). In addition to the widespread use of Intrusion Prevention
Systems (IPS) as perimeter defense devices in systems and networks, various IDS solutions are used together as elements of holistic approaches to cyber security incident detection and prevention, including Network-Intrusion Detection Systems
(NIDS) and Host-Intrusion Detection Systems (HIDS). Nevertheless, specific IDS and
IPS technology face several effectiveness challenges to respond to the increasing scale and complexity of information systems and sophistication of attacks. The use of isolated IDS components, focused on one-dimensional approaches, strongly limits a common analysis based on evidence correlation. Today, most organizations’ cyber-security operations centers still rely on conventional SIEM (Security Information and Event Management) technology. However, SIEM platforms also have significant drawbacks in dealing with heterogeneous and specialized security event-sources, lacking the support for flexible and uniform multi-level analysis of security audit-trails involving distributed and heterogeneous systems.
In this thesis, we propose an auditing solution that leverages on different intrusion
detection components and synergistically combines them in a Distributed and Hybrid IDS (DHIDS) platform, taking advantage of their benefits while overcoming the effectiveness drawbacks of each one. In this approach, security events are detected
by multiple probes forming a pervasive, heterogeneous and distributed monitoring
environment spread over the network, integrating NIDS, HIDS and specialized Honeypot probing systems. Events from those heterogeneous sources are converted to a canonical representation format, and then conveyed through a Publish-Subscribe
middleware to a dedicated logging and auditing system, built on top of an elastic and
scalable document-oriented storage system. The aggregated events can then be queried and matched against suspicious attack signature patterns, by means of a proposed declarative query-language that provides event-correlation semantics
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
Adding Contextual Information to Intrusion Detection Systems Using Fuzzy Cognitive Maps
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In the last few years there has been considerable increase in the efficiency of Intrusion Detection Systems (IDSs). However, networks are still the victim of attacks. As the complexity of these attacks keeps increasing, new and more robust detection mechanisms need to be developed. The next generation of IDSs should be designed incorporating reasoning engines supported by contextual information about the network, cognitive information and situational awareness to improve their detection results. In this paper, we propose the use of a Fuzzy Cognitive Map (FCM) in conjunction with an IDS to incorporate contextual information into the detection process. We have evaluated the use of FCMs to adjust the Basic Probability Assignment (BPA) values defined prior to the data fusion process, which is crucial for the IDS that we have developed. The experimental results that we present verify that FCMs can improve the efficiency of our IDS by reducing the number of false alarms, while not affecting the number of correct detections
Wireless and Physical Security via Embedded Sensor Networks
Wireless Intrusion Detection Systems (WIDS) monitor 802.11 wireless frames (Layer-2) in an attempt to detect misuse. What distinguishes a WIDS from a traditional Network IDS is the ability to utilize the broadcast nature of the medium to reconstruct the physical location of the offending party, as opposed to its possibly spoofed (MAC addresses) identity in cyber space. Traditional Wireless Network Security Systems are still heavily anchored in the digital plane of "cyber space" and hence cannot be used reliably or effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts, for example by escorting an intruder off the premises based on physical evidence. In this paper, we argue that Embedded Sensor Networks could be used effectively to bridge the gap between digital and physical security planes, and thus could be leveraged to provide reciprocal benefit to surveillance and security tasks on both planes. Toward that end, we present our recent experience integrating wireless networking security services into the SNBENCH (Sensor Network workBench). The SNBENCH provides an extensible framework that enables the rapid development and automated deployment of Sensor Network applications on a shared, embedded sensing and actuation infrastructure. The SNBENCH's extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the SNBENCH framework, while high-level languages and compilers allow novice SN programmers to compose SN service logic, unaware of the lower-level implementation details of tools on which their services rely. In this paper we convey the simplicity of the service composition through concrete examples that illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CIES/CNS 0520166, CNS/ITR 0205294, CISE/ERA RI 0202067
Why We Cannot (Yet) Ensure the Cybersecurity of Safety-Critical Systems
There is a growing threat to the cyber-security of safety-critical systems.
The introduction of Commercial Off The Shelf (COTS) software, including
Linux, specialist VOIP applications and Satellite Based Augmentation Systems
across the aviation, maritime, rail and power-generation infrastructures has created
common, vulnerabilities. In consequence, more people now possess the technical
skills required to identify and exploit vulnerabilities in safety-critical systems.
Arguably for the first time there is the potential for cross-modal attacks
leading to future ‘cyber storms’. This situation is compounded by the failure of
public-private partnerships to establish the cyber-security of safety critical applications.
The fiscal crisis has prevented governments from attracting and retaining
competent regulators at the intersection of safety and cyber-security. In particular,
we argue that superficial similarities between safety and security have led
to security policies that cannot be implemented in safety-critical systems. Existing
office-based security standards, such as the ISO27k series, cannot easily be integrated
with standards such as IEC61508 or ISO26262. Hybrid standards such as
IEC 62443 lack credible validation. There is an urgent need to move beyond
high-level policies and address the more detailed engineering challenges that
threaten the cyber-security of safety-critical systems. In particular, we consider
the ways in which cyber-security concerns undermine traditional forms of safety
engineering, for example by invalidating conventional forms of risk assessment.
We also summarise the ways in which safety concerns frustrate the deployment of
conventional mechanisms for cyber-security, including intrusion detection systems
DCDIDP: A Distributed, Collaborative, and Data-driven IDP Framework for the Cloud
Recent advances in distributed computing, grid computing, virtualization mechanisms, and utility computing led into Cloud Computing as one of the industry buzz words of our decade. As the popularity of the services provided in the cloud environment grows exponentially, the exploitation of possible vulnerabilities grows with the same pace. Intrusion Detection and Prevention Systems (IDPSs) are one of the most popular tools among the front line fundamental tools to defend the computation and communication infrastructures from the intruders. In this poster, we propose a distributed, collaborative, and data-driven IDP (DCDIDP) framework for cloud computing environments. Both cloud providers and cloud customers will benefit significantly from DCDIDP that dynamically evolves and gradually mobilizes the resources in the cloud as suspicion about attacks increases. Such system will provide homogeneous IDPS for all the cloud providers that collaborate distributively. It will respond to the attacks, by collaborating with other peers and in a distributed manner, as near as possible to attack sources and at different levels of operations (e.g. network, host, VM). We present the DCDIDP framework and explain its components. However, further explanation is part of our ongoing work
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A survey of intrusion detection techniques in Cloud
Cloud computing provides scalable, virtualized on-demand services to the end users with greater flexibility and lesser infrastructural investment. These services are provided over the Internet using known networking protocols, standards and formats under the supervision of different managements. Existing bugs and vulnerabilities in underlying technologies and legacy protocols tend to open doors for intrusion. This paper, surveys different intrusions affecting availability, confidentiality and integrity of Cloud resources and services. It examines proposals incorporating Intrusion Detection Systems (IDS) in Cloud and discusses various types and techniques of IDS and Intrusion Prevention Systems (IPS), and recommends IDS/IPS positioning in Cloud architecture to achieve desired security in the next generation networks
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