17617099
Interfacing Oz with the PCTE OMS: A Case Study of Integrating a Legacy System with a Standard Object Management System
The integration of a legacy system and a standard Object Management System (OMS) is often a very challenging task. This paper details a case study, our experiment in interfacing Oz with the PCTE (Portable Common Tool Environment) Object Management System. Oz is a multi-user process-centered software development environment that has been under development in our lab since 1987, originally under the name Marvel. PCTE is a specification that defines a language-independent interface providing support mechanisms for software engineering environments (SEE). One of the premises of PCTE is that, in theory, an SEE such as Oz can be built (or extended) using the services provided by PCTE. The purpose of our experiment was to study how a legacy system such as Oz can be integrated into a new environment framework, e.g., PCTE. The architecture of the legacy system and the services of the framework are the key factors in the integration approach. Because Oz historically has included a native OMS, our experiment focused on modifying Oz to use the PCTE OMS, which has an open and standard API. This paper describes how several Oz components were changed to interface to the PCTE OMS. The resulting proof-of-concept hybrid system has process control and integration services provided by Oz, and data integration services provided in part by PCTE. We discuss in depth the solutions to the concurrency control problems that arise in such an environment, where Oz and PCTE use different approaches to transaction management (i.e., each has its own transaction manager). The PCTE implementation used in our experiment was the Emeraude PCTE V 12.5.1, and the Oz version was V 1.0.1.
15031377
Anomaly detection using call stack information
The call stack of a program execution can be a very good information source for intrusion detection. There is no prior work on dynamically extracting information from the call stack and effectively using it to detect exploits. In this paper we propose a new method to do anomaly detection using call stack information. The basic idea is to extract return addresses from the call stack, and generate an abstract execution path between two program execution points. Experiments show that our method can detect some attacks that cannot be detected by other approaches, while its convergence and false positive performance is comparable to or better than the other approaches. We compare our method with other approaches by analyzing their underlying principles and thus achieve a better characterization of their performance, in particular on what and why attacks will be missed by the various approaches.
2157536
A framework for constructing features and models for intrusion detection systems
Intrusion detection (ID) is an important component of infrastructure protection mechanisms. Intrusion detection systems (IDSs) need to be accurate, adaptive, and extensible. Given these requirements and the complexities of today's network environments, we need a more systematic and automated IDS development process rather that the pure knowledge encoding and engineering approaches. This article describes a novel framework, MADAM ID, for Mining Audit Data for Automated Models for Instrusion Detection. This framework uses data mining algorithms to compute activity patterns from system audit data and extracts predictive features from the patterns. It then applies machine learning algorithms to the audit records taht are processed according to the feature definitions to generate intrusion detection rules. Results from the 1998 DARPA Intrusion Detection Evaluation showed that our ID model was one of the best performing of all the participating systems. We also briefly discuss our experience in converting the detection models produced by off-line data mining programs to real-time modules of existing IDSs.
4680884
Statistical Causality Analysis of INFOSEC Alert Data
With the increasingly widespread deployment of security mechanisms, such as firewalls, intrusion detection systems (IDSs), antiviras software and authentication services, the problem of alert analysis has become very important. The large amount of alerts can overwhelm security administrators and prevent them from adequately understanding and analyzing the security state of the network, and initiating appropriate response in a timely fashion. Recently, several approaches for alert correlation and attack scenario analysis have been proposed. However, these approaches all have limited capabilities in detecting new attack scenarios. In this paper, we study the problem of security alert correlation with an emphasis on attack scenario analysis. In our framework, we use clustering techniques to process low-level alert data into high-level aggregated alerts, and conduct causal analysis based on statistical tests to discover new relationships among attacks. Our statistical causality approach complements other approaches that use hard-coded prior knowledge for pattern matching. We perform a series of experiments to validate our method using DARPA’s Grand Challenge Problem (GCP) datasets, the 2000 DARPA Intrusion Detection Scenario datasets, and the DEF CON 9 datasets. The results show that our approach can discover new patterns of attack relationships when the alerts of attacks are statistically correlated.
8008073
Worm detection, early warning and response based on local victim information
Worm detection systems have traditionally focused on global strategies. In the absence of a global worm detection system, we examine the effectiveness of local worm detection and response strategies. This paper makes three contributions: (1) we propose a simple two-phase local worm victim detection algorithm, DSC (Destination-Source Correlation), based on worm behavior in terms of both infection pattern and scanning pattern. DSC can detect zero-day scanning worms with a high detection rate and very low false positive rate. (2) We demonstrate the effectiveness of early worm warning based on local victim information. For example, warning occurs with 0.19% infection of all vulnerable hosts on Internet when using a /12 monitored network. (3) Based on local victim information, we investigate and evaluate the effectiveness of an automatic real-time local response in terms of slowing down the global Internet worms propagation. (2) and (3) are general results, not specific to certain detection algorithm like DSC. We demonstrate (2) and (3) with both analytical models and packet-level network simulator experiments.
15927015
Using Labeling to Prevent Cross-Service Attacks Against Smart Phones
Wireless devices that integrate the functionality of PDAs and cell phones are becoming commonplace, making different types of network services available to mobile applications. However, the integration of different services allows an attacker to cross service boundaries. For example, an attack carried out through the wireless network interface may eventually provide access to the phone functionality. This type of attacks can cause considerable damage because some of the services (e.g., the GSM-based services) charge the user based on the traffic or time of use. In this paper, we demonstrate the feasibility of these attacks by developing a proof-of-concept exploit that crosses service boundaries. To address these security issues, we developed a solution based on resource labeling. We modified the kernel of an integrated wireless device so that processes and files are marked in a way that allows one to regulate the access to different system resources. Labels are set when certain network services are accessed. The labeling is then transferred between processes and system resources as a result of either access or execution. We also defined a language for creating labeling rules, and demonstrated how the system can be used to prevent attacks that attempt to cross service boundaries. Experimental evaluation shows that the implementation introduces little overhead. Our security solution is orthogonal to other protection schemes and provides a critical defense for the growing problem of cell phone viruses and worms
15083346
Integration and Analysis of Use Cases Using Modular Petri Nets in Requirements Engineering
It is well known that requirements engineering plays a critical role in software quality. The use case approach is a requirements elicitation technique commonly used in industrial applications. Software requirements are stated as a collection of use cases, each of which is written in the user's perspective and describes a specific flow of events in the system. The use case approach offers several practical advantages in that use case requirements are relatively easy to describe, understand, and trace. Unfortunately, there are a couple of major drawbacks. Since use cases are often stated in natural languages, they lack formal syntax and semantics. Furthermore, it is difficult to analyze their global system behavior for completeness and consistency, partly because use cases describe only partial behaviors and because interactions among them are rarely represented explicitly. We propose the Constraints-based Modular Petri Nets (CMPNs) approach as an effective way to formalize the informal aspects of use cases. CMPNs, an extension of Place/Transition nets, allow the formal and incremental specification of requirements. The major contributions of the paper, in addition to the formal definitions of CMPNs, are the development of: 1) a systematic procedure to convert use cases stated in natural language to a CMPN model; and 2) a set of guidelines to find inconsistency and incompleteness in CMPNs. We demonstrate an application of our approach using use cases developed for telecommunications services.
15546337
On processing nested queries in distributed object-oriented database systems
In this paper, we discuss nested query processing in a distributed object-oriented database system. We present three query processing strategies to exploit parallelism in a distributed environment. Then, we review three access methods designed for centralized systems and discuss how they can be applied to the distributed environment. Heuristics for selecting attributes for indexing and determining where to store the indexes are also presented. Finally, a replication strategy is proposed for the path dictionary method.<<ETX>>
6881391
Evolving Complex Robot Behaviors
Building robots is a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to such diculties in designing robots is to adopt learning methods. The evolution-based approach is a special method of machine learning and it has been advocated to automate the design of robots. Yet, the tasks achieved so far are fairly simple. In this work, we ®rst analyze the diculties of applying evolutionary approaches to synthesize robot controllers for complicated tasks, and then suggest an approach to resolve them. Instead of directly evolving a monolithic control system, we propose to decompose the overall task to ®t in the behavior-based control architecture, and then to evolve the separate behavior modules and arbitrators using an evolutionary approach. Consequently, the job of de®ning ®tness functions becomes more straightforward and the tasks easier to achieve. To assess the performance of the developed approach, we evolve a control system to achieve an application task of box-pushing as an example. Experimental results show the promise and eciency of the presented approach. Ó 1999 Elsevier Science Inc. All rights reserved.
22742444
Distributed scalable location data management system based on the GALIS architecture
A challenging task in the LBS system engineering is to implement a highly scalable system architecture which can manage moderate-size configurations handling thousands of moving items as well as upper-end configurations handling millions of moving items. The architecture named the GALIS is a cluster-based distributed computing system architecture that consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone. In this paper, we explain a prototype location data management system structuring major components of GALIS by employing the TMO programming scheme, including the execution engine middleware developed to support real-time distributed object programming and real-time distributed computing system design. We present how to generate realistic location sensing reports and how to process such location reports and location-related queries. Some experimental results showing performance factors regarding distributed query processing are also explained.
15867299
Supporting XML Security Models Using Relational Databases: A Vision
As the secure distribution and sharing of information over the World Wide Web becomes increasingly important, the needs for flexible and efficient support of access control systems naturally arise. Since the eXtensible Markup Language (XML) is emerging as the format of the Internet era for storing and exchanging information, there have been, recently, many proposals to extend the XML model to incorporate security aspects. To the lesser or greater extent, however, such proposals neglect the fact that the data for XML documents will most likely reside in relational databases, and consequently do not utilize various security models proposed for and implemented in relational databases.