A Secure PLAN (Extended Version)

Active networks promise greater flexibility than current networks, but threaten safety and security by virtue of their programmability. We describe the design and implementation of a security architecture for the active network PLANet (Hicks et al., 1999). Security is obtained with a two-level architecture that combines a functionally restricted packet language, PLAN (Hicks et al., 1998), with an environment of general-purpose service routines governed by trust management (Blaze et al., 1996). In particular, we employ a technique which expands or contracts a packet's service environment based on its level of privilege, termed namespace-based security. As an application of our security architecture, we present the design and implementation of an active-network firewall. We find that the addition of the firewall imposes an approximately 34% latency overhead and as little as a 6.7% space overhead to incoming packets

A Logic Programming Approach to Knowledge-State Planning: Semantics and Complexity

We propose a new declarative planning language, called K, which is based on principles and methods of logic programming. In this language, transitions between states of knowledge can be described, rather than transitions between completely described states of the world, which makes the language well-suited for planning under incomplete knowledge. Furthermore, it enables the use of default principles in the planning process by supporting negation as failure. Nonetheless, K also supports the representation of transitions between states of the world (i.e., states of complete knowledge) as a special case, which shows that the language is very flexible. As we demonstrate on particular examples, the use of knowledge states may allow for a natural and compact problem representation. We then provide a thorough analysis of the computational complexity of K, and consider different planning problems, including standard planning and secure planning (also known as conformant planning) problems. We show that these problems have different complexities under various restrictions, ranging from NP to NEXPTIME in the propositional case. Our results form the theoretical basis for the DLV^K system, which implements the language K on top of the DLV logic programming system.Comment: 48 pages, appeared as a Technical Report at KBS of the Vienna University of Technology, see http://www.kr.tuwien.ac.at/research/reports

Answer Set Planning Under Action Costs

Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved

Roots and Effects of Investments' Misperception

This work deals with the problem of investors' irrational behavior and financial products' misperception. The theoretical analysis of the mechanisms driving wrong evaluations of investment performances is explored. The study is supported by the application of Monte Carlo simulations to the remarkable case of structured financial products. Some motivations explaining the popularity among retail investors of these complex financial instruments are also provided. Investors are assumed to compare the performances of different projects through stochastic dominance rules and, to pursue our scopes, a new definition of this decision criteria is introduced.

Agents in Network Management

The ubiquity and complexity of modern networks require automated management and control. With increases in scale, automated solutions based on simple data access models such as SNMP will give way to more distributed and algorithmic techniques. This article outlines present and near-term solutions based on the ideas of active networks and mobile agents, which permit sophisticated programmable control and management of ultra large scale networks

Scalable Resource Control in Active Networks

The increased complexity of the service model relative to store-and-forward routers has made resource management one of the paramount concerns in active networking research and engineering. In this paper,we address two major challenges in scaling resource management-to-many-node active networks. The first is the use of market mechanisms and trading amongst nodes and programs with varying degrees of competition and cooperation to provide a scalable approach to managing active network resources. The second is the use of a trust-management architecture to ensure that the participants in the resource management marketplace have a policy-driven "rule of law" in which marketplace decisions can be made and relied upon. We have used lottery scheduling and the Keynote trust-management system for our implementation, for which we provide some initial performance indications