35,216 research outputs found
Real-time detection of grid bulk transfer traffic
The current practice of physical science research has yielded a continuously growing demand for interconnection network bandwidth to support the sharing of large datasets. Academic research networks and internet service providers have provisioned their networks to handle this type of load, which generates prolonged, high-volume traffic between nodes on the network. Maintenance of QoS for all network users demands that the onset of these (Grid bulk) transfers be detected to enable them to be reengineered through resources specifically provisioned to handle this type of traffic. This paper describes a real-time detector that operates at full-line-rate on Gb/s links, operates at high connection rates, and can track the use of ephemeral or non-standard ports
ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems
We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network services. The false positives raised by the NIDS analyzing the incoming traffic (which can be either signature- or anomaly-based) are reduced by correlating them with the output anomalies. We designed our architecture for TCP-based network services which have a client/server architecture (such as HTTP). Benchmarks show a substantial reduction of false positives between 50% and 100%
A Survey on Handover Management in Mobility Architectures
This work presents a comprehensive and structured taxonomy of available
techniques for managing the handover process in mobility architectures.
Representative works from the existing literature have been divided into
appropriate categories, based on their ability to support horizontal handovers,
vertical handovers and multihoming. We describe approaches designed to work on
the current Internet (i.e. IPv4-based networks), as well as those that have
been devised for the "future" Internet (e.g. IPv6-based networks and
extensions). Quantitative measures and qualitative indicators are also
presented and used to evaluate and compare the examined approaches. This
critical review provides some valuable guidelines and suggestions for designing
and developing mobility architectures, including some practical expedients
(e.g. those required in the current Internet environment), aimed to cope with
the presence of NAT/firewalls and to provide support to legacy systems and
several communication protocols working at the application layer
Secure Vehicular Communication Systems: Implementation, Performance, and Research Challenges
Vehicular Communication (VC) systems are on the verge of practical
deployment. Nonetheless, their security and privacy protection is one of the
problems that have been addressed only recently. In order to show the
feasibility of secure VC, certain implementations are required. In [1] we
discuss the design of a VC security system that has emerged as a result of the
European SeVeCom project. In this second paper, we discuss various issues
related to the implementation and deployment aspects of secure VC systems.
Moreover, we provide an outlook on open security research issues that will
arise as VC systems develop from today's simple prototypes to full-fledged
systems
Securing personal distributed environments
The Personal Distributed Environment (PDE) is a new concept being developed by Mobile VCE allowing future mobile users flexible access to their information and services. Unlike traditional mobile communications, the PDE user no longer needs to establish his or her personal communication link solely through one subscribing network but rather a diversity of disparate devices and access technologies whenever and wherever he or she requires. Depending on the services’ availability and coverage in the location, the PDE communication configuration could be, for instance, via a mobile radio system and a wireless ad hoc network or a digital broadcast system and a fixed telephone network. This new form of communication configuration inherently imposes newer and higher security challenges relating to identity and authorising issues especially when the number of involved entities, accessible network nodes and service providers, builds up. These also include the issue of how the subscribed service and the user’s personal information can be securely and seamlessly handed over via multiple networks, all of which can be changing dynamically. Without such security, users and operators will not be prepared to trust their information to other networks
AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments
This report considers the application of Articial Intelligence (AI) techniques to
the problem of misuse detection and misuse localisation within telecommunications
environments. A broad survey of techniques is provided, that covers inter alia
rule based systems, model-based systems, case based reasoning, pattern matching,
clustering and feature extraction, articial neural networks, genetic algorithms, arti
cial immune systems, agent based systems, data mining and a variety of hybrid
approaches. The report then considers the central issue of event correlation, that
is at the heart of many misuse detection and localisation systems. The notion of
being able to infer misuse by the correlation of individual temporally distributed
events within a multiple data stream environment is explored, and a range of techniques,
covering model based approaches, `programmed' AI and machine learning
paradigms. It is found that, in general, correlation is best achieved via rule based approaches,
but that these suffer from a number of drawbacks, such as the difculty of
developing and maintaining an appropriate knowledge base, and the lack of ability
to generalise from known misuses to new unseen misuses. Two distinct approaches
are evident. One attempts to encode knowledge of known misuses, typically within
rules, and use this to screen events. This approach cannot generally detect misuses
for which it has not been programmed, i.e. it is prone to issuing false negatives.
The other attempts to `learn' the features of event patterns that constitute normal
behaviour, and, by observing patterns that do not match expected behaviour, detect
when a misuse has occurred. This approach is prone to issuing false positives,
i.e. inferring misuse from innocent patterns of behaviour that the system was not
trained to recognise. Contemporary approaches are seen to favour hybridisation,
often combining detection or localisation mechanisms for both abnormal and normal
behaviour, the former to capture known cases of misuse, the latter to capture
unknown cases. In some systems, these mechanisms even work together to update
each other to increase detection rates and lower false positive rates. It is concluded
that hybridisation offers the most promising future direction, but that a rule or state
based component is likely to remain, being the most natural approach to the correlation
of complex events. The challenge, then, is to mitigate the weaknesses of
canonical programmed systems such that learning, generalisation and adaptation
are more readily facilitated
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