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Searching for authors named Christopher Leckie – sorted by Relevance.

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  • Characterising Optical Amplitude Histograms  
  • by Christopher Leckie
  • …Abstract — We present a method of characterising amplitude histograms for optical network monitoring. We demonstrate that our approach can detect the signature of several common types of impairments in a robust and computationally efficient manner. I.…
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  • Anomaly Detection for Internet Worms  
  • by Yousof Al-hammadi, Christopher Leckie — 1993 — In Proceedings to the 9 th IFIP/IEEE International Symposium on Integrated Network Management
  • …Internet worms have become a major threat to the Internet due to their ability to rapidly compromise large numbers of computers. In response to this threat, there is a growing demand for effective techniques to detect the presence of worms and to reduce the worms’ spread. Furthermore, existing appro…
  • Cited by 4 (0 self) – Add To MetaCart
  • Learning to share distributed probabilistic beliefs  
  • by Christopher Leckie, Kotagiri Ramamohanarao — 2002 — In Proceedings of the Nineteenth International Conference on Machine Learning (ICML-2002
  • …In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approach can generally be applied to domains that use a probabilistic model for evaluating hypotheses, and have a method for com…
  • Cited by 6 (4 self) – Add To MetaCart
  • Unsupervised Anomaly Detection in Network Intrusion Detection Using Clusters  
  • by Kingsly Leung, Christopher Leckie — 2005 — In Proc. 28th Australasian CS Conf., volume 38 of CRPITV
  • …Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically expensive to produce. Moreover, these methods have difficulty in detecting new types of attack. Using unsupervised anomal…
  • Cited by 9 (0 self) – Add To MetaCart
  • Detecting Distributed Denial of Service Attacks Using Source IP Address Monitoring  
  • by Tao Peng, Christopher Leckie, Kotagiri Ramamohanarao — 2002 — In Proceedings of the Third International IFIP-TC6 Networking Conference (Networking 2004
  • …In this paper, we propose a simple but robust scheme to detect denial of service attacks (including distributed denial of service attacks) by monitoring the increase of new IP addresses. Unlike previous proposals for bandwidth attack detection schemes which are based on monitoring the traffic volume…
  • Cited by 12 (2 self) – Add To MetaCart
  • Adjusted Probabilistic Packet Marking for IP Traceback  
  • by Tao Peng, Christopher Leckie, Kotagiri Ramamohanarao — 2002
  • …Distributed denial-of-service attack is one of the greatest threats to the Internet today. One of the biggest difficulties in defending against this attack is that attackers always use incorrect, or "spoofed" IP source addresses to disguise their true origin. In this paper, we present a packet marki…
  • Cited by 11 (4 self) – Add To MetaCart
  • Detecting Reflector Attacks by Sharing Beliefs  
  • by Tao Peng, Christopher Leckie, Kotagiri Ramamohanarao — 2003 — In Proceedings of the IEEE GLOBECOM
  • …In this paper, we present a distributed approach to detecting a type of distributed denial of service attack known as reflector attacks. In our approach, every potential reflector monitors the incoming packets and broadcasts a warning message to other potential reflectors if any abnormal traffic is …
  • Cited by 4 (1 self) – Add To MetaCart
  • Distributed Anomaly Detection in Wireless Sensor Networks. To appear  
  • by Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami — 2006 — in Proceedings of Tenth IEEE International Conference on Communications Systems (IEEE ICCS 2006), 30 October-1
  • …Identifying misbehaviors is an important challenge for monitoring, fault diagnosis and intrusion detection in wireless sensor networks. A key problem is how to minimise the communication overhead and energy consumption in the network when identifying misbehaviors. Our approach to this problem is bas…
  • Cited by 1 (1 self) – Add To MetaCart
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