In a Service-Oriented Architecture, a service contains a set of operations with clearly defined input and output parameters. In addition to these operations and traditional QoS, offered services need to publish different levels of intrusion tolerance for two reasons. First, software vulnerabilities can expose services to malicious actors, and make them susceptible to attacks. So, intrusion tolerance will help services to provide continuity of service to clients. Second, clients may require different levels of intrusion tolerance, depending on their non-functional requirements and operating environments. In this paper, we present an approach to model and publish Intrusion Tolerance Quality of Service, which characterizes the level of resilience of a service to survive in the face of malicious intrusions. Then, we will show how a cross-cutting intrusion tolerance architecture layer with its components and algorithms is able to ensure services with differentiated classes of S-Reliability (security-related reliability). Our proposed scheme to provide multilevel S-Reliability is applicable to atomic services, service orchestrations, and multi-tier software architecture.

The formidable difficulty in securing systems stems in large part from the increasing complexity of the systems we build but also the degree to which we now depend on information systems. Complex systems cannot be fully verified under all possible conditions. Self cleansing intrusion tolerance (SCIT) servers go through periodic cleaning. SCIT can be used to create secure and robust cluster of servers without the impossible requirement of having perfect security on each server in the cluster. In this paper, we identify six SCIT security primitives that must be satisfied. We present a SCIT hardware enhanced (SCIT/HES) implementation that guarantees the incorruptibility of SCIT operations

Domain name systems (DNS) provide the mapping between easily-remembered host names and their IP addresses. Popular DNS implementations however contain vulnerabilities that are exploited by frequent, targeted attacks. The software vulnerabilities of DNS together with the constant innovation and morphing of cyber attack techniques necessitate the consideration of the worst case scenarios: there will be successful but undetected attacks against DNS servers. In this work, we develop a secure DNS architecture that contains the damage of successful, undetected attacks. This formidable end is achieved by constantly cleansing the servers and rotating the role of individual servers. Moreover, the server rotation process itself is protected against corruption by hardware. We will show the advantages of our design in the following areas: (1) protection of the DNS master file and cryptographic keys, (2) incorruptible intrusion tolerance, (3) high availability, and (4) scalability, the support of using of high degrees of hardware/server redundancy to improve both system security and service dependability. Due to the critical importance of DNS, such a dependable and intrusion-resilient design contributes significantly to the overall security of the Internet.

Despite the increased focus on security, critical information systems remain vulnerable to cyber attacks. The problem stems in large part from the constant innovation and evolution of attack techniques. The trend leads importance to the concept of intrusion tolerance a critical system must fend off or at least limit the damage caused by unknown and/or undetected attacks. In prior work, we developed a self-cleansing intrusion tolerance (SCIT) architecture that achieves the above goal by constantly cleansing the servers and rotating the rule of individual servers. In this paper, we show that, with simple hardware enhancements strategically placed in a SCIT system, incorruptible intrusion containment can be realized. We then present an incorruptible SCIT design for use by one of the most critical infrastructures of the Internet, the domain name services. It is our belief that incorruptible intrusion containment as presented here constitutes a new, effective layer of system defense for critical information system

Automatic segmentation of objects in images is an ongoing research problem with applications in many fields. If a scene is imaged serially over time, an advantage can be gained by using segmentation results from previous and subsequent images when segmenting the current image. This paper discusses a probabilistic framework for making use of temporal information in the segmentation process. A subset of dynamic Bayesian networks, the hidden Markov model is described as a means to improve segmentation over statistical classification techniques that use static pixel intensity information alone. An application of this technique to the segmentation of tumors in magnetic resonance images (MRIs) is described. The segmentation accuracy was increased compared to a popular 3D spatial only segmentation method.

The focus of this paper is the analysis of threshold-based admission control policies for distributed video-on-demand (VoD) systems. Traditionally, admission control methods control access to a resource based on the resource capacity. We have extended that concept to include the significance of an arriving request to the VoD system by enforcing additional threshold restrictions in the admission control process on request classes deemed less significant. We present an analytical model for computing blocking performance of the VoD system under threshold-based admission control. Extending the same methodology to a distributed VoD architecture we show through simulation that the threshold performance conforms to the analytical model. We also show that threshold-based analysis can work in conjunction with other request handling policies and are useful for manipulating the VoD performance since we are able to distinguish between different request classes based on their merit. Enforcing threshold restrictions with the option of downgrading blocked requests in a multirate service environment results in improved performance at the same time providing different levels of quality of service (QoS). In fact, we show that the downgrade option combined with threshold restrictions is a powerful tool for manipulating an incoming request mix over which we have no control into a workload that the VoD system can handle.

The focus of the research presented in this paper is the end-to-end analysis of a distributed Video-on-Demand (VoD) system. We analyze the distributed architecture of a VoD system to design global request handling and admission control strategies and evaluate them using global metrics. The performance evaluation methodology developed in this paper helps in determining efficient ways of using all resources in the VoD architecture within the constraints of providing guaranteed high quality service to each request. For instance, our simulation results show that request handling policies based on limited redirection of blocked requests to other resources perform better than load sharing policies. We also show that request handling policies based on redirection have simpler connection establishment semantics than load sharing policies and, therefore, are easily incorporated into reservation or signaling protocols.

This paper describes our approach to building a scalable, flexible agent-based architecture for imagery and geospatial processing. Central to this approach is the agent discovery and composition mechanism which scales to support networks with thousands of agents. The agent architecture implements over 100 imagery and geospatial processing agents based on the Java Advanced Imaging and OpenMap(TM) APIs. The agents are distributed over a Jini enabled network, and communicate with one another via JavaSpaces. We discuss our "atomic" approach in this paper: developing low-level processing agents that are used by application of specific agents. We discuss several concepts in this approach: agent lookup and discovery through traditional information retrieval techniques, the ability to rapidly prototype agents based on commercial software products, and a knowledge management approach that reuses prior processing approaches and results. We present results demonstrating the scalability of our agent discovery and composition mechanism to compare them with other traditional discovery mechanisms, and demonstrate how the discovery mechanism scales to support thousands of agents.

An important class of multimedia applications involve real-time distributed collaboration or distributed control. This paper examines some of the issues in network support for this class of applications and presents Collaborative Load-Balanced Routing (CLBR), a new technique for routing and call establishment of distributed collaborative and control multimedia applications. CLBR substantially reduces the overhead of communication establishment in the network between two-party distributed multimedia applications. This is achieved through an adaptive load-balancing and single source single pass approach to routing and call establishment. A large scale simulation study comparing CLBR to other types of uni-cast routing shows that this speed up can be achieved without any corresponding decrease in the networks ability to support new communication requests.

We present a new coarse grain parallel genetic algorithm (PGA}for the Multiprocessor Document Allocation Problem (MDAP, an NP-complete problem). The problem is to find an optimal mapping of a collection of documents onto the multiprocessor nodes such that the average cluster diameter is kept to a minimum while providing for an even document distribution across the nodes. Our algorithm has been implemented on a 16-node Intel iPSC/2 hypercube and the performance was evaluated. As part of the experimental analysis, the effects of varying the number of documents and their distribution across the clusters are studied. We also investigate the impact of varying two PGA parameters - the migration period and the migration volume

The authors propose four scale-space object detection algorithms for separating objects from the background. These algorithms do not need thresholding at any of the scales. The different algorithms are applicable to images with different noise and clutter characteristics. Statistical analysis of the four algorithms is conducted for noisy and cluttered backgrounds.>

It is shown that the existence of duplicate values in some attribute columns has a significant impact on the computational complexity of the sorting and joining operations. This is especially true when the number of distinct tuple values is a small fraction of the total number of tuples. The authors characterize a multirelation M(n, L) by its cardinality n and the number of distinct elements L it contains. Under this characterization, the worst time complexity of sorting such a multirelation with binary comparisons as basic operations is investigated. Upper and lower bounds on the number of three-branch comparisons needed to sort such a multirelation are established. Thereafter, the methodology used to study the complexity of sorting is applied to the natural join operation. It is shown that the existence of duplicate values in the join attribute columns can be exploited to reduce the computational complexity of the natural join operation.>

A new segmentation algorithm that can be used for robot applications is presented. The input images are dense range data of industrial parts. The image is segmented into a number of surfaces. The segmentation algorithm uses residual analysis to detect edges, then a region-growing technique is used to obtain the final segmented image. The use of the segmentation output for determining the best holdsite position and orientation of objects is studied. As compared to techniques based on intensity images, the use of range images simplifies the holdsite determination. This information can then be used to instruct the robot to grip the object and move it to the required position. The performance of the algorithm on a number of range images is presented.>

A motion parameter estimation technique is presented for image sequence analysis of several frames. A dynamic scene model is developed in which image sequences are processed as a temporally correlated complex. Using this model, measurement of the position of the object in a set of consecutive frames permits the estimation of motion as a function of time. The measurement consists of a sequence of image coordinates of three or more feature correspondence points in each frame. The motion sequence is represented as a discrete-time time-varying system. An iterative mathematical parameter estimation technique is used to minimize the projection error. The fundamental concept of this analysis is based on optimal control theory. Motion parameter estimates are extracted from the sequence of image correspondence by modeling the motion dynamics using motion transformation and viewing projection. Object positions are estimated by iteratively refining the parameters by small perturbations. This methodology is suitable for processing a long sequence in situations where a high rate of imagery is available. Results are presented for generalized rigid-body motion of synthesized images and real images.>

Using the odd-even network topology, a parallel bit-level pipelined VLSI processing unit is designed for the histogramming operation. In this approach, histogramming is divided into two stages, the counting and marking process and the filtering process. The filtering process is computationally inexpensive compared to the counting and marking phase. The proposed processing unit is composed of one type of bit-serial structure (processing element) operating in parallel. The architecture and VLSI implementation of the processing unit is considered. The performance of the design is compared with the implementation of the histogramming operation on the Massively Parallel Processor. The comparative analysis shows that the odd-even network based approach has significant advantages in terms of both processing speed and performance/cost ratio.>

A network environment is considered that can exist in commercial and military products, such as automatic guided vehicles, that use sensors and processors for movement, attack, defense and communication. A bus protocol called IMAP (improved token bus multiaccess protocol) is proposed for these embedded networks. Two modes of operation are defined for the protocol. The normal mode occurs when token passing is done in a random order and the token remains within a cluster of active stations. For a nonuniform traffic condition, this mode of operation can be interrupted by a mode in which token bus operation is carried out and the token is passed through every station. The performance (channel utilization and delay characteristics) of IMAP are compared to those of the token bus and CSMA/CD (carrier sense multiaccess with collision detection) and shown to be superior.>

The(M, L)-algorithm has been widely used in speech and image encoding. Recently, use of(M, L)-Iike algorithms has been suggested for decoding phase codes. With its ever-increasing use, there arises a need to explore architectures suitable for real-time applications. Toward this end, we present a multiprocessor architecture for the(M, L)algorithm that employs an SIMD (single instruction-multiple data) machine structure. The considerations involved in interconnection network design are discussed. The main functions of the network controller are switch state selection and synchronization. The number of switching elements required is significantly less than the elements required in the universal permutation network. These features make this architecture suitable for VLSI implementation. The tradeoff between number of processors and encoding time is also discussed.