Securing distributed adaptation
Open architecture networks provide applications with fine-grained control over network elements. With this control comes the risk of misuse and new challenges to security beyond those present in conventional networks. One particular security requirement is the ability of applications to protect the secrecy and integrity of transmitted data while still allowing trusted active elements within the network to operate on that data. This paper describes mechanisms for identifying trusted nodes within a network and securely deploying adaptation instructions to those nodes while protecting application data from unauthorized access and modification. Promising experimental results of our implementation within the conductor adaptation framework are also presented, suggesting that such features can be incorporated into real networks.

title: Simulation and analysis on the resiliency and efficiency of malnets
abstract: Future network intruders will probably use an organized army of malicious nodes (here called "malnodes", or collectively a "malnet") to deliver many different attacks, rather than recruiting a disorganized set of compromised nodes per attack. However, partly due to the lack of understanding of the resiliency and efficiency a malnet can have, countering malnets has been ineffective. This paper begins to address this deficiency. Through calculation and simulation for three representative malnets-random, small-world, and Gnutella-like-we show that extremely resilient malnets can be formed to deliver attack code quickly. In particular, we show that disconnecting malnets is possible, but extremely naive approaches such as randomly disinfecting malnodes will not suffice, and effective defenses must either happen very quickly during a second-wave attack, or take effect prior to it.

title: mSSL: extending SSL to support data sharing among collaborative clients
abstract: Client-server applications often do not scale well when a large number of clients access a single server. To solve this, a new trend is to allow a client to download data from other peer clients, in addition to from the server directly. This paradigm, which we call the hybrid peer-to-peer paradigm, is friendly to the server's scalability, but also faces new security challenges. For example, how can the server authenticate its clients and support data confidentiality? How can a client trust the data downloaded from other clients? What if a client refuses to acknowledge the service it received or overstates the service it offered? In this paper, we present a protocol, called mSSL, that provides a set of security functions to enable secure sharing of the data of a server among its clients. In addition to access control and confidentiality support, mSSL provides an original design on supporting data integrity and proof of service in this new context. Our evaluation further shows that mSSL has a reasonable overhead

title: BGP routing dynamics revisited
abstract: Understanding BGP routing dynamics is critical to the solid growth and maintenance of the Internet routing infrastructure. However, while the most extensive study on BGP dynamics is nearly a decade old, many factors that could affect BGP dynamics have changed considerably. We revisit this important topic in this paper, focusing on not only comparing with the previous results, but also issues not well explored before. We have found that, compared to almost a decade ago, although certain characteristics remain unchanged (such as some temporal properties), BGP dynamics are now â busier,â and more importantly, now have much less pathological behavior and are â healthierâ ; for example, forwarding dynamics are now not only dominant, but also more consistent across different days. Contributions to BGP dynamics by different BGP peersâ which are not proportional to the size of a peerâ s ASâ are also more stable, and dynamics due to policy changes or duplicate announcements are usually from specific peers

title: SAVE: source address validity enforcement protocol
abstract: Forcing all IP packets to carry correct source addresses can greatly help network security, attack tracing, and network problem debugging. However, due to asymmetries in today's Internet routing, routers do not have readily available information to verify the correctness of the source address for each incoming packet. In this paper we describe a new protocol, named SAVE, that can provide routers with the information needed for source address validation. SAVE messages propagate valid source address information from the source location to all destinations, allowing each router along the way to build an incoming table that associates each incoming interface of the router with a set of valid source address blocks. This paper presents the protocol design and evaluates its correctness and performance by simulation experiments. The paper also discusses the issues of protocol security, the effectiveness of partial SAVE deployment, and the handling of unconventional forms of network routing, such as mobile IP and tunneling.

title: An internet routing forensics framework for discovering rules of abnormal BGP events
abstract: Abnormal BGP events such as attacks, misconfigurations, electricity failures, can cause anomalous or pathological routing behavior at either global level or prefix level, and thus must be detected in their early stages. Instead of using ad hoc methods to analyze BGP data, in this paper we introduce an Internet Routing Forensics framework to systematically process BGP routing data, discover rules of abnormal BGP events, and apply these rules to detect the occurrences of these events. In particular, we leverage data mining techniques to train the framework to learn rules of abnormal BGP events, and our results from two case studies show that these rules are effective. In one case study, rules of worm events discovered from the BGP data during the outbreaks of the CodeRed and Nimda worms were able to successfully detect worm impact on BGP when an independent worm, the Slammer, subsequently occurred. Similarly, in another case study, rules of electricity blackout events obtained using BGP data from the 2003 East Coast blackout were able to detect the BGP impact from the Florida blackout caused by Hurricane Frances in 2004.

title: A computationally efficient approach to the estimation of two- and three-dimensional hidden Markov models
abstract: Statistical modeling methods are becoming indispensable in today's large-scale image analysis. In this paper, we explore a computationally efficient parameter estimation algorithm for two-dimensional (2-D) and three-dimensional (3-D) hidden Markov models (HMMs) and show applications to satellite image segmentation. The proposed parameter estimation algorithm is compared with the first proposed algorithm for 2-D HMMs based on variable state Viterbi. We also propose a 3-D HMM for volume image modeling and apply it to volume image segmentation using a large number of synthetic images with ground truth. Experiments have demonstrated the computational efficiency of the proposed parameter estimation technique for 2-D HMMs and a potential of 3-D HMM as a stochastic modeling tool for volume images.

title: A semantics-based routing scheme for grid resource discovery
abstract: Grid technologies enable the sharing of a wide variety of distributed resources. To fully utilize these resources, effective resource discovery mechanisms are necessities. However, the complicated and dynamic characteristics of grid resources make sharing and discovering them a challenging issue. In this paper, we propose a peer-to-peer (P2P) based overlay network to assist the efficient resource discovery and query. The framework is based on the RDF metadata infrastructure, allowing a rich and extensible description of resources. To avoid flooding the network with a query, we propose a comprehensive semantics-based query forwarding strategy, which only forwards queries to semantically related nodes. After the related nodes have been located, the original RDF query is used to do the final query and retrieval. Results from simulation experiments demonstrate that this architecture is scalable and efficient

title: Construct robust rule sets for classification
abstract: We study the problem of computing classification rule sets from relational databases so that accurate predictions can be made on test data with missing attribute values. Traditional classifiers perform badly when test data are not as complete as the training data because they tailor a training database too much. We introduce the concept of one rule set being more robust than another, that is, able to make more accurate predictions on test data with missing attribute values. We show that the optimal class association rule set is as robust as the complete class association rule set. We then introduce the k-optimal rule set, which provides predictions exactly the same as the optimal class association rule set on test data with up to k missing attribute values. This leads to a hierarchy of k-optimal rule sets in which decreasing size corresponds to decreasing robustness, and they all more robust than a traditional classification rule set. We introduce two methods to find k-optimal rule sets, i.e. an optimal association rule mining approach and a heuristic approximate approach. We show experimentally that a k-optimal rule set generated by the optimal association rule mining approach performs better than that by the heuristic approximate approach and both rule sets perform significantly better than a typical classification rule set (C4.5Rules) on incomplete test data.

title: Some properties of Ramsey numbers
abstract: In this paper, some properties of Ramsey numbers are studied, and the following results are presented. 
1. 
(1) For any positive integers k1, k2, …, km l1, l2, …, lm (m > 1), we have 
r ∏i=1m ki + 1, ∏i=1m li + 1 ≥ ∏i=1m [ r (ki + 1,li + 1) − 1] + 1 
. 
 
2. 
(2) For any positive integers k1, k2, …, km, l1, l2, …, ln , we have 
r ∑i=1m ki + 1, ∑j=1n lj + 1 ≥ ∑i=1m∑j=1n r (ki + 1,lj + 1) − mn + 1 
. Based on the known results of Ramsey numbers, some results of upper bounds and lower bounds of Ramsey numbers can be directly derived by those properties.

title: RACCOON: a peer-based system for data integration and sharing
abstract: Recent database applications see the emerging need to support data integration in distributed, peer-to-peer environments, in which autonomous peers (sources) connected by a network are willing to exchange data and services with each other. To address related research challenges, we are developing a system called "RACCOON", which allows different sources to integrate and share their data. We use an application to show several important features of the RACCOON system. The system also suggests semantic mappings for the user to choose. We show the two different querying modes, particularly how a query is expanded using the semantic mappings in the extended querying mode to compute as many answers to the query as possible.