In automated trust negotiation (ATN), two parties exchange digitally signed credentials that contain attribute information to establish trust and make access control decisions.  Because the information in question is often sensitive, credentials are protected according to access control policies.  In traditional ATN, credentials are transmitted either in their entirety or not at all. This approach can at times fail unnecessarily, either because a cyclic dependency makes neither negotiator willing to reveal her credential before her opponent, because the opponent must be authorized for all attributes packaged together in a credential to receive any of them, or because it is necessary to fully disclose the attributes, rather than merely proving they satisfy some predicate (such as being over 21 years of age).  Recently, several cryptographic credential schemes and associated protocols have been developed to address these and other problems.  However, they can be used only as fragments of an ATN process.  This paper introduces a framework for ATN in which the diverse credential schemes and protocols can be combined, integrated, and used as needed.  A policy language is introduced that enables negotiators to specify authorization requirements that must be met by an opponent to receive various amounts of information about certified attributes and the credentials that contain it.  The language also supports the use of uncertified attributes, allowing them to be required as part of policy satisfaction, and to place their (automatic) disclosure under policy control.

This work focuses on ontological efforts to support information security applications

Secure multi-party protocols make the computation of answers and decisions that depend on multiple parties’ private data possible, without revealing anything about the private inputs (other than what unavoidably can be deduced from the outputs).  There are general results showing that any probabilistic polynomial time function can be computed in this framework in an asymptotically efficient manner, using circuit-simulation techniques. There is a frequent belief that these general circuit-simulation techniques are not practical compared to custom-built (i.e., problem-specific) solutions, unless the function being computed has a naturally circuit-like formulation. This paper carries out a quantitative empirical evaluation of this belief, for a problem that would apparently benefit from a custom-built protocol (forecasting using time series techniques). Our findings are somewhat surprising in the following aspects. First, the custom-built solution does not overcome the general circuit-simulation solution on a local network until the problem size becomes quite large. Second, relaxing (even slightly) the requirement that, instead of ``nothing’‘, the protocols reveal ``little’’ makes possible dramatic performance improvements over the solutions for the more strict requirement (whether they are custom-built or based on general circuit simulations). Third, other aspects (such as, e.g., system resources available) play a significant role in evaluation of a computational model. This paper describes the subtle implementation issues involved with this evaluation, presents its results, and talks about the lessons learned that should be valuable in future deployments of this kind of technology.

Digital watermarking is the practice of inserting a signal, known as the watermark, into an original signal in an imperceptible manner. The watermark encodes or represents information that can protect the watermarked signal, typically identifying the owner (source) or the intended recipient (destination) of the signal. The embedded watermark may be detected by using a watermark detector, which enables an application to react to the presence (or absence) of the watermark in a signal. However, the watermarked signal may be processed, or attacked, prior to watermark detection. Attacks may remove the embedded watermark or make the watermark more difficult to detect. One type of attack that has received considerable attention is synchronization attacks. A synchronization attack confuses the watermark detector by re-positioning the embedded watermark. Most watermark detectors will fail to detect the watermark embedded in the attacked signal unless the position of the watermark can be identified. This is a significant vulnerability in robust watermark detection. The process of identifying the position of the watermark is known as watermark detector synchronization. A new framework is developed for temporal synchronization in blind symmetric video watermarking. Embedding and detection models are proposed that encompass the behavior of many video watermarking techniques. These models demonstrate that synchronization is challenging when the watermark lacks redundancy, but also that efficient synchronization can be achieved by designing the watermark with temporal redundancy. The temporal synchronization models are adapted to spatial synchronization in still image watermarks. For spatial synchronization, redundancy is obtained by constructing a watermark which induces a pattern in the auto-correlation. Experimental results support the theoretical foundations for both temporal and spatial synchronization. In addition, earlier exploration in watermarking led to the development of a semifragile watermarking technique for image authentication. The semi-fragile technique is capable of detecting significant alterations to the watermarked image, but is tolerant to lossy JPEG compression and other, more subtle alterations. This earlier work is not related to watermark synchronization.

This dissertation presents an analysis of the features of network traffic commonly used in network-based anomaly detection systems. It is an examination designed to identify how the selection of a particular protocol attribute affects performance. It presents a guide for making judicious selections of features for building network-based anomaly detection models.

We introduce a protocol analysis methodology called Inter-flow versus Intra-flow Analysis (IVIA) for partitioning protocol attributes based on operational behavior. The method aids in the construction of flow models and identifies the protocol attributes that contribute to model accuracy, and those that are likely to generate false positive alerts, when used as features for network anomaly detection models.

We introduce a set of data preprocessing operations that transform these previously identified ``noisy’’ attributes into useful features for anomaly detection. We refer to these as behavioral features. The derivation of this new class of features from observed measurements is both possible and feasible without undue computational effort, and can therefore keep pace with network traffic.

Empirical results using unsupervised learning show that models based on behavioral features can achieve higher classification accuracies with markedly lower false positive rates than their traditional packet header feature counterparts. Behavioral features are also used in the context of supervised learning to build classifiers of server application flow behavior.

This dissertation investigates two research problems to protect wireless network topology and routing: (1) designing protocols with configurable overhead to defend against wormhole attacks; (2) designing an intruder identification mechanism to locate and isolate the malicious nodes in distance vector routing protocols. Previous approaches for wormhole detection in ad hoc networks assume a relationship of trust between direct neighbors and cannot detect wormholes when the attackers are legal members in the network. As a generic approach, an end-to-end mechanismis proposed that assumes trust only between the source and the destination of a route. It integrates the positions of nodes and loosely synchronized clocks to identify fake neighbor connections. An information management scheme is designed to allow a mobile node to predetermine the resources that are consumed on wormhole detection. In our experiments, the computation overhead is less than 0.28% of the CPU time for a ten-hop route. This justifies the feasibility of the proposed mechanism. For wormhole detection in sensor networks, we propose the first group of approaches that do not depend on any special hardware. A normalized variable wormhole indicator is defined based on the distortions in edge length and angles among neighboring sensors. As a centralized approach, MDS-VOW reconstructs the network layout using inaccurate distance measurements among sensors and identifies fake neighbor connections. As a distributed approach, Dis-VoW allows every sensor to detect wormholes locally when the network topology changes. The research creates a new method to solve wireless network security problems by integrating techniques from social science, computer graphics, and scientific visualization. An intruder identification mechanism is designed to locate and isolate malicious nodes that attack the AODV protocol with false destination sequence numbers. The propagation paths of false routes are marked through reverse labeling and the suspicious attackers are put into blacklists to achieve isolation. The quorum voting method is adopted to reduce false positive alarms. In our experiments, the proposed mechanism can improve the packet delivery ratio by 30% even when there are multiple malicious nodes in the network.

An essential component of effective use of distributed systems is proper task placement, or scheduling. To produce high-quality schedules, scheduling algorithms require underlying support mechanisms that provide information describing the distributed system. The work presented here makes a clear distinction between scheduling policies and the underlying mechanism, and focuses on the problem of providing general purpose mechanisms that facilitate a broad spectrum of task placement algorithms. This dissertation proposes a model for distributed scheduling support mechanisms. This model includes scalable and extensible mechanisms that support the efficient implementation of scheduling policies on distributed systems, while preserving the autonomy of the component systems. The mechanisms include provably correct information exchange protocols for system state dissemination in distributed systems. MESSIAHS is a prototype implementation of these mechanisms, including a scheduling module that implements the basic mechanism, as well as a library of function calls and a specialized programming language for writing distributed schedulers. As a demonstration of the utility of the prototype, several algorithms from the literature are implemented and their performance is analyzed. The experimental results show average overhead of approximately 10% using MESSIAHS, measured against a theoretical ideal running time. The results indicate that it is possible to build scalable, general-purpose mechanisms that support a variety of task placement algorithms while preserving autonomy.

Data mining can extract important knowledge from large data collections, but sometimes these collections are split among various parties. Data warehousing, bringing data from multiple sources under a single authority, increases risk of privacy violations. Furthermore, privacy concerns may prevent the parties from directly sharing even some meta-data. Distributed data mining and processing provide a means to address this issue, particularly if queries are processed in a way that avoids the disclosure of any information beyond the final result. This thesis presents methods to mine horizontally partitioned data without violating privacy and shows how to use the data mining results in a privacy-preserving way. The methods incorporate cryptographic techniques to minimize the information shared, while adding as little as possible overhead to the mining and processing task.

Fueled by the exponential growth in the number of people with access to the Internet, electronic-commerce (e-commerce) transactions via the Internet have become a major part of our economy. For a wider range of e-commerce applications to take advantage of the untapped business potential of the Internet, some challenging and interesting security problems need to be solved. In this thesis, we study two such problems, and provide efficient solutions for both. In the foreseeable future, some e-commerce vendors will generate revenue by providing digital streaming applications such as information broadcasts (e.g., stock quotes). For the first issue, we investigate the problem of authenticating packet streams in multicast or broadcast networks. Our approach is to encode the hash values and digital signatures with Rabin’s Information Dispersal Algorithm (IDA) to construct an authentication scheme that amortizes a single signature operation over multiple packets. This strategy is especially efficient in terms of space overhead because just the essential elements needed for authentication (i.e., one hash per packet and one signature per group of packets) are used in conjunction with an erasure code that is space optimal. We evaluate the performance of our scheme using both analytical and empirical results. Applications such as e-commerce payment protocols using electronic money require that fair exchange be assured. For the second issue, we investigate the problem of constructing fair-exchange protocols. Our approach uses a novel signature paradigm-the gradational signature scheme-to construct protocols that are efficient and scalable. Unlike previous approaches, our scheme does not employ any costly zero-knowledge proof systems in the exchange protocol. Use of zero-knowledge proofs is needed only in the protocol setup phase-this is a one-time cost. The resulting exchange protocol is more e

Most past and present intrusion detection systems architectures assume a uni-processor environment or do not explicitly make use of multiple processors when they exist.  Yet, especially in the server world, multiple processor machines are commonplace; and with the advent of technologies such as Intel and AMD’s multi-core or Hyperthreading technologies, commodity computers are likely to have multiple processors.

This research explores how explicitly dividing the system into production and security components and running the components in parallel on different processors can improve the effectiveness of the security system. The production component contains all user tasks and most of the operating system while the security component contains security monitoring and validating tasks and the parts of the O/S that pertain to security.  We demonstrate that under some circumstances this architecture allows intrusion detection systems to use monitoring models with higher fidelity, particularly with regard to the timeliness of detection, and will also increase system robustness in the face of some types of attacks.

Empirical results with a prototype co-processing intrusion detection system (CuPIDS) architecture support the feasibility of this approach. The construction of the prototype allowed us to demonstrate the implementation costs of the architecture are reasonable. Experimentation using fine-grained protection of real-world applications resulted in about a fifteen percent slowdown while demonstrating CuPIDS’ ability to quickly detect and respond to illegitimate behavior.

There has been an increasing interest in the deployment of Public Key Infrastructures, the past few years. Security issues emerge from the operation of Certification Authorities, as well as the operation of other PKI ‑ related security service providers. Most of them have been addressed and efficient solutions have been found. One of the areas which has to be studied further is the generation and dissemination of information regarding the status of a digital certificate.

In this dissertation, we present a set of evaluation criteria for mechanisms that are used to generate and disseminate Certificate Status Information (CSI). We evaluate the proposed CSI mechanisms according to the aforementioned criteria, and identify the security and performance issues that emerge from their use.

Finally, we develop a prototype specification for a CSI dissemination mechanism, which we call Alternative Dissemination of Certificate Status Information (ADOCSI). This mechanism uses the functionality offered by Software Agents in order to disseminate CSI, and also uses some of the properties and functionality offered by the other CSI mechanisms. We believe that ADOCSI addresses some of the issues that emerge from the use of the other Certificate Status Information dissemination mechanisms.

We develop solutions for the security and privacy of user identity information in a federation. By federation we mean a group of organizations or service providers which have built trust among each other and enable sharing of user identity information amongst themselves. We first propose a flexible approach to establish a single sign-on (SSO) ID in the federation. Then we show how a user can leverage this SSO ID to establish certified and un-certified user identity attributes without the dependence on PKI for user authentication. This makes the process more usable and privacy preserving. Our major contribution in this paper is a novel solution for protection against identity theft of these identity attributes. We provide protocols based on cryptographic techniques, namely zero knowledge proofs and distributed hash tables. We show how we can preserve privacy of the user identity without jeopardizing security.

We formally prove correctness and provide complexity results for our protocols. The complexity results show that our approach is efficient. In the paper we also show that the protocol is robust enough even in case semi-trusted ``honest-yet curious” service providers thus preventing against insider threat. In our analysis we give the desired properties of the cryptographic tools used and identify open problems. We believe that the approach represents a precursor to new and innovative cryptographic techniques which can provide solutions for the security and privacy problems in federated identity management.