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
13874800
A Data Mining and CIDF Based Approach for Detecting Novel and Distributed Intrusions
As the recent distributed Denial-of-Service (DDOS) attacks on several major Internet sites have shown us, no open computer network is immune from intrusions. Furthermore, intrusion detection systems (IDSs) need to be updated timely whenever a novel intrusion surfaces; and geographically distributed IDSs need to cooperate to detect distributed and coordinated intrusions. In this paper, we describe an experimental system, based on the Common Intrusion Detection Framework (CIDF), where multiple IDSs can exchange attack information to detect distributed intrusions. The system also includes an ID model builder, where a data mining engine can receive audit data of a novel attack from an IDS, compute a new detection model, and then distribute it to other IDSs. We describe our experiences in implementing such system and the preliminary results of deploying the system in an experimental network.
10557654
Adaptive Intrusion Detection: A Data Mining Approach
In this paper we describe a data mining framework for constructingintrusion detection models. The first key idea is to mine system auditdata for consistent and useful patterns of program and user behavior.The other is to use the set of relevant system features presented inthe patterns to compute inductively learned classifiers that canrecognize anomalies and known intrusions. In order for the classifiersto be effective intrusion detection models, we need to have sufficientaudit data for training and also select a set of predictive systemfeatures. We propose to use the association rules and frequentepisodes computed from audit data as the basis for guiding the auditdata gathering and feature selection processes. We modify these twobasic algorithms to use axis attribute(s) and referenceattribute(s) as forms of item constraints to compute only therelevant patterns. In addition, we use an iterative level-wiseapproximate mining procedure to uncover the low frequency butimportant patterns. We use meta-learning as a mechanism to makeintrusion detection models more effective and adaptive. We report ourextensive experiments in using our framework on real-world audit data.
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.
9369710
Attack plan recognition and prediction using causal networks
Correlating and analyzing security alerts is a critical and challenging task in security management. Recently, some techniques have been proposed for security alert correlation. However, these approaches focus more on basic or low-level alert correlation. In this paper, we study how to conduct probabilistic inference to correlate and analyze attack scenarios. Specifically, we propose an approach to solving the following problems: 1) How to correlate isolated attack scenarios resulted from low-level alert correlation? 2) How to identify attacker's high-level strategies and intentions? 3) How to predict the potential attacks based on observed attack activities? We evaluate our approaches using DARPA's grand challenge problem (GCP) data set. The results demonstrate the capability of our approach in correlating isolated attack scenarios, identifying attack strategies and predicting future attacks.
16787004
Performance evaluation of a wireless hierarchical data dissemination system
Various techniques have been developed to improve the performance of wireless information services. Techniques such as information broadcasting, caching of frequently accessed data, and point-to-point channels for pull-based data requests are often used to reduce data access time. To efficiently utilize information broadcast, indexing and scheduling schemes are employed for the organization of data broadcast. Most of the studies in the literature focused either on individual technique or a combination of them with some restrictive assumptions. There is no study considering these techniques working together in an integrated manner. In this paper, we propose a dynamic data delivery model for wireless communication environments. An important feature of our model is that data are disseminated through various storage mediums according to the dynamically collected data access patterns. Various results are presented in a set of simulation studies, which give some of the intuitions behind the design of a wireless data delivery system.
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.
195713214
Using Signature Techniques for Information Filtering in Wireless and Mobile Environments
This paper discusses the issue of power conservation on mobile clients, e.g., palmtop, in wireless and mobile environments. It suggests that techniques using signatures are suitable for realtime information filtering on mobile clients. Three signature-based approaches, namely simple signature, integrated signature and multi-level signature schemes, are presented. The cost models for the access time and tune-in time of these three approaches are developed. We show that the multi-level signature method is in general better than the other two methods.
14599729
Combining Indexing Technique with Path Dictionary for Nested Object Queries
A path dictionary encodes the connections among objects in the aggregation hierarchy. It has been shown to be an efficient mechanism for supporting nested object queries [6]. In this paper, we present a new method, called the path dictionary index method, which combines indexing techniques with the path dictionary method. We describe the operations of the new mechanism and develop cost modeis for its storage overhead and query and update costs. Finally, we compare the new mechanism to the path index method 131. The result shows that the path dictionary index method is significantly better than the path index method over a wide range of parameters.
3800033
Exponential index: a parameterized distributed indexing scheme for data on air
Wireless data broadcast has received a lot of attention from industries and academia in recent years. Access efficiency and energy conservation are two critical performance concerns in a wireless data broadcast environment. To improve the efficiency of energy consumption on mobile devices, traditional disk-based indexing techniques such as B$^+$-tree have been extended to index broadcast data on a wireless channel. However, existing designs are mostly based on centralized tree structures. Most of these indexing techniques are not flexible in the sense that the trade-off between access efficiency and energy conservation is not adjustable based on application specific requirements. We propose in this paper a novel parameterized index, called the exponential index, which can be tuned to optimize the access latency with the tuning time bounded by a given limit, and vice versa. The proposed index is very efficient because it facilitates replication naturally by sharing links in multiple search trees and thus minimizes storage overhead. Experimental results show that the exponential index not only achieves better performance than the state-of-the-art indexes but also enables great flexibility in trade-offs between access latency and tuning time.