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R.W. Bennington

Bio: R.W. Bennington is an academic researcher from Air Force Research Laboratory. The author has contributed to research in topics: Retail banking & Exploit. The author has an hindex of 3, co-authored 3 publications receiving 113 citations.

Papers
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Proceedings ArticleDOI
03 Jan 2007
TL;DR: A notional online banking system is analyzed and protection solutions are proposed for varying budgets to identify how attackers compromise accounts and develop methods to protect them.
Abstract: Online banking has become increasingly important to the profitability of financial institutions as well as adding convenience for their customers. As the number of customers using online banking increases, online banking systems are becoming more desirable targets for criminals to attack. To maintain their customers' trust and confidence in the security of their online bank accounts, financial institutions must identify how attackers compromise accounts and develop methods to protect them. Attack trees and protection trees are a cost effective way to do this. Attack trees highlight the weaknesses in a system and protection trees provide a methodical means of mitigating these weaknesses. In this paper, a notional online banking system is analyzed and protection solutions are proposed for varying budgets

79 citations

Proceedings ArticleDOI
29 Aug 2007
TL;DR: Assessment of the performance overhead of a program fragmentation engine and analysis of its effectiveness against reverse-engineering techniques show that program fragmentation has low overhead and is an effective technique to complicate disassembly of programs using two common disassembler/debugger tools.
Abstract: Unauthorized reverse-engineering of programs and algorithms is a major problem for the software industry. Reverse-engineers search for security holes in the program to exploit or try to steal competitors' vital algorithms. To discourage reverse-engineering, developers use a variety of static software protections to obfuscate their programs. Metamorphic software protections add another layer of protection to traditional static obfuscation techniques, forcing reverse-engineers to adjust their attacks as the protection changes. Program fragmentation combines two obfuscation techniques, outlining and obfuscated jump tables, into a new, metamorphic protection. Sections of code are removed from the main program flow and placed throughout memory, reducing the program's locality. These fragments move and are called using obfuscated jump tables, making program execution difficult to follow. This research assesses the performance overhead of a program fragmentation engine and provides analysis of its effectiveness against reverse-engineering techniques. Results show that program fragmentation has low overhead and is an effective technique to complicate disassembly of programs using two common disassembler/debugger tools.

24 citations

Journal ArticleDOI
01 Mar 2008
TL;DR: The state of the art in today's nonmalicious software defense protections is presented and some unorthodox approaches to defending software, including tactics that advanced malware currently uses to protect itself are expounded.
Abstract: In this article, we present the state of the art in today's nonmalicious software defense protections. We also present an overview of the tools and techniques that attackers use to defeat current defenses. Finally, we expound on some unorthodox approaches to defending software, including tactics that advanced malware currently uses to protect itself.

13 citations


Cited by
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Journal ArticleDOI
Wei Wei1, Jinjiu Li1, Longbing Cao1, Yuming Ou1, Jiahang Chen1 
TL;DR: An effective online banking fraud detection framework that synthesizes relevant resources and incorporates several advanced data mining techniques is proposed that can achieve substantially higher accuracy and lower alert volume than the latest benchmarking fraud detection system incorporating domain knowledge and traditional fraud detection methods.
Abstract: Sophisticated online banking fraud reflects the integrative abuse of resources in social, cyber and physical worlds. Its detection is a typical use case of the broad-based Wisdom Web of Things (W2T) methodology. However, there is very limited information available to distinguish dynamic fraud from genuine customer behavior in such an extremely sparse and imbalanced data environment, which makes the instant and effective detection become more and more important and challenging. In this paper, we propose an effective online banking fraud detection framework that synthesizes relevant resources and incorporates several advanced data mining techniques. By building a contrast vector for each transaction based on its customer's historical behavior sequence, we profile the differentiating rate of each current transaction against the customer's behavior preference. A novel algorithm, ContrastMiner, is introduced to efficiently mine contrast patterns and distinguish fraudulent from genuine behavior, followed by an effective pattern selection and risk scoring that combines predictions from different models. Results from experiments on large-scale real online banking data demonstrate that our system can achieve substantially higher accuracy and lower alert volume than the latest benchmarking fraud detection system incorporating domain knowledge and traditional fraud detection methods.

291 citations

Journal ArticleDOI
TL;DR: This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs), and proposes a taxonomy of the described formalisms.

262 citations

Posted Content
TL;DR: In this article, the authors present the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs), allowing for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions.
Abstract: This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements.

226 citations

Journal ArticleDOI
TL;DR: A new graphical security model called attack–defense trees is developed, which generalizes the well-known attack trees model and demonstrates the usefulness of the formal foundations of attack– Defense trees by relating attack– defense terms to other scientific research disciplines.
Abstract: The advent of the information age has notably amplified the importance of security. Unfortunately security considerations still widely occur as an afterthought. For many companies, security is not a requirement to conduct business and is therefore readily neglected. However the lack of security may obstruct, impede and even ruin an otherwise flourishing enterprise. Only when internal computer networks shut down, web portals are inaccessible, mail servers are attacked, or similar incidents affect the day to day business of an enterprise, security enters into the field of vision of companies. As such, security by design is only slowly becoming accepted practice. Amongst security researchers, there is no dispute that a reasonable approach to- wards uninterrupted business activities includes security measures and controls from the beginning. To support these efforts, many security models have been developed. Graphical security models are a type of security model that help illus- trate and guide the consideration of security throughout the lifecycle of a product, system or company. Their visual properties are especially well-suited to elucidate security requirements and corresponding security measures. During the last four years, we have developed a new graphical security model called attack–defense trees. The new framework, presented in this thesis, generalizes the well-known attack trees model. Attack–defense trees formally extend attack trees and enhance them with defenses. To be able to deploy attack–defense trees as a security support tool, we have equipped them with three different syntaxes: A visually appealing, graph-based syntax that is dedicated to representing security problems, an algebraic, term-based syntax that simplifies correct, formal and quantitative analysis of security scenarios and a textual syntax that is a compromise between succinct, visual representation and easy, computerized input. We have also equipped attack–defense trees with a variety of semantics. This became necessary, since different applications require different interpretations of attack–defense trees. Besides the very specific and problem oriented propositional, De Morgan and multiset semantics, we have introduced equational semantics. The latter semantics is, in fact, an alternative, unified presentation of semantics based on equational theory. We have expressed the propositional and the multiset seman- tics in terms of the equational semantics. This facilitates algorithmic treatment since the two different semantics have a unified formal foundation. To be able to perform quantitative security analysis, we have introduced the notion of an attribute for attack–defense trees. To guarantee that the evaluation of an attribute on two or more semantically equal attack–defense trees results in the same value, we have introduced the notion of a compatibility condition between semantics and attributes. We have also provided usability guidelines for attributes. These guidelines help a user to specify security-relevant questions that can unambiguously be answered using attributes. We have performed several case studies that allowed us to test and improve the attack–defense tree methodology. We have provided detailed explanations for our design choices during the case studies as well as extensive applicability guidelines that serve a prospective user of the attack–defense tree methodology as a user manual. We have demonstrated the usefulness of the formal foundations of attack–defense trees by relating attack–defense terms to other scientific research disciplines. Con- cretely, we have shown that attack–defense trees in the propositional semantics are computationally as complex as propositional attack trees. Moreover, we have described how to merge Bayesian networks with attack–defense trees and have il- lustrated that attack–defense trees in the propositional semantics are equivalent to a specific class of games frequently occurring in game theory. Concluding the thesis, we have related the attack–defense tree methodology to other graphical security models in an extensive literature overview over similar methodologies.

160 citations

Journal ArticleDOI
TL;DR: A careful screening of the literature made it possible to identify cross-fertilizations in various fields such as architectural concepts, graphical formalisms, structured risk analyses or fault tolerance and prevention techniques.

136 citations