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Don't even ask: database access control through query control

Summary

This paper presents a vision and description for query control, which is a paradigm for database access control. In this model, individual queries are examined before being executed and are either allowed or denied by a pre-defined policy. Traditional view-based database access control requires the enforcer to view the query, the records, or both. That may present difficulty when the enforcer is not allowed to view database contents or the query itself. This discussion of query control arises from our experience with privacy-preserving encrypted databases, in which no single entity learns both the query and the database contents. Query control is also a good fit for enforcing rules and regulations that are not well-addressed by view-based access control. With the rise of federated database management systems, we believe that new approaches to access control will be increasingly important.
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Summary

This paper presents a vision and description for query control, which is a paradigm for database access control. In this model, individual queries are examined before being executed and are either allowed or denied by a pre-defined policy. Traditional view-based database access control requires the enforcer to view the query...

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Adversarial co-evolution of attack and defense in a segmented computer network environment

Published in:
Proc. Genetic and Evolutionary Computation Conf. Companion, GECCO 2018, 15-19 July 2018, pp. 1648-1655.

Summary

In computer security, guidance is slim on how to prioritize or configure the many available defensive measures, when guidance is available at all. We show how a competitive co-evolutionary algorithm framework can identify defensive configurations that are effective against a range of attackers. We consider network segmentation, a widely recommended defensive strategy, deployed against the threat of serial network security attacks that delay the mission of the network's operator. We employ a simulation model to investigate the effectiveness over time of different defensive strategies against different attack strategies. For a set of four network topologies, we generate strong availability attack patterns that were not identified a priori. Then, by combining the simulation with a coevolutionary algorithm to explore the adversaries' action spaces, we identify effective configurations that minimize mission delay when facing the attacks. The novel application of co-evolutionary computation to enterprise network security represents a step toward course-of-action determination that is robust to responses by intelligent adversaries.
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Summary

In computer security, guidance is slim on how to prioritize or configure the many available defensive measures, when guidance is available at all. We show how a competitive co-evolutionary algorithm framework can identify defensive configurations that are effective against a range of attackers. We consider network segmentation, a widely recommended...

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Improving security at the system-call boundary in a type-safe operating system

Published in:
Thesis (M.E.)--Massachusetts Institute of Technology, 2018.

Summary

Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the system-call boundary. We then introduce a technique for providing memory safety at the boundary between userland and the kernel in Tock. We demonstrate that this technique works to prevent against the aforementioned vulnerability and a class of similar vulnerabilities, and we propose how it might be used to protect against simliar vulnerabilities in other operating systems.
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Summary

Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the...

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Dynamically correlating network terrain to organizational missions

Published in:
Proc. NATO IST-153/RWS-21 Workshop on Cyber Resilience, 23-25 October 2017.

Summary

A precondition for assessing mission resilience in a cyber context is identifying which cyber assets support the mission. However, determining the asset dependencies of a mission is typically a manual process that is time consuming, labor intensive and error-prone. Automating the process of mapping between network assets and organizational missions is highly desirable but technically challenging because it is difficult to find an appropriate proxy within available cyber data for an asset's mission utilization. In this paper we discuss strategies to automate the processes of both breaking an organization into its constituent mission areas, and mapping those mission areas onto network assets, using a data-driven approach. We have implemented these strategies to mine network data at MIT Lincoln Laboratory, and provide examples. We also discuss examples of how such mission mapping tools can help an analyst to identify patterns and develop contextual insight that would otherwise have been obscure.
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Summary

A precondition for assessing mission resilience in a cyber context is identifying which cyber assets support the mission. However, determining the asset dependencies of a mission is typically a manual process that is time consuming, labor intensive and error-prone. Automating the process of mapping between network assets and organizational missions...

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Predicting exploitation of disclosed software vulnerabilities using open-source data

Published in:
3rd ACM Int. Workshop on Security and Privacy Analytics, IWSPA 2017, 24 March 2017.

Summary

Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that software vendors quickly provide patches once vulnerabilities are known and users quickly install those patches as soon as they are available. However, most vulnerabilities are never actually exploited. Since writing, testing, and installing software patches can involve considerable resources, it would be desirable to prioritize the remediation of vulnerabilities that are likely to be exploited. Several published research studies have reported moderate success in applying machine learning techniques to the task of predicting whether a vulnerability will be exploited. These approaches typically use features derived from vulnerability databases (such as the summary text describing the vulnerability) or social media posts that mention the vulnerability by name. However, these prior studies share multiple methodological shortcomings that infl ate predictive power of these approaches. We replicate key portions of the prior work, compare their approaches, and show how selection of training and test data critically affect the estimated performance of predictive models. The results of this study point to important methodological considerations that should be taken into account so that results reflect real-world utility.
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Summary

Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that software vendors quickly provide patches once vulnerabilities are known and users quickly install those patches as soon as they are available. However, most vulnerabilities are...

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Interactive synthesis of code-level security rules

Author:
Published in:
Thesis (M.S.)--Northeastern University, 2017.

Summary

Software engineers inadvertently introduce bugs into software during the development process and these bugs can potentially be exploited once the software is deployed. As the size and complexity of software systems increase, it is important that we are able to verify and validate not only that the software behaves as it is expected to, but also that it does not violate any security policies or properties. One of the approaches to reduce software vulnerabilities is to use a bug detection tool during the development process. Many bug detection techniques are limited by the burdensome and error prone process of manually writing a bug specification. Other techniques are able to learn specifications from examples, but are limited in the types of bugs that they are able to discover. This work presents a novel, general approach for synthesizing security rules for C code. The approach combines human knowledge with an interactive logic programming synthesis system to learn Datalog rules for various security properties. The approach has been successfully used to synthesize rules for three intraprocedural security properties: (1) out of bounds array accesses, (2) return value validation, and (3) double freed pointers. These rules have been evaluated on randomly generated C code and yield a 0% false positive rate and a 0%, 20%, and 0% false negative rate, respectively for each rule.
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Summary

Software engineers inadvertently introduce bugs into software during the development process and these bugs can potentially be exploited once the software is deployed. As the size and complexity of software systems increase, it is important that we are able to verify and validate not only that the software behaves as...

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Resilience of cyber systems with over- and underregulation

Published in:
Risk Analysis, Vol. 37, No. 9, 2017, pp. 1644-51, DOI:10.1111/risa.12729.

Summary

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under- and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to use ad-hoc approaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.
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Summary

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber...

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A data-stream classification system for investigating terrorist threats

Published in:
Proc. SPIE 9851, Next-Generation Analyst IV, 98510L (May 12, 2016); doi:10.1117/12.2224104.

Summary

The role of cyber forensics in criminal investigations has greatly increased in recent years due to the wealth of data that is collected and available to investigators. Physical forensics has also experienced a data volume and fidelity revolution due to advances in methods for DNA and trace evidence analysis. Key to extracting insight is the ability to correlate across multi-modal data, which depends critically on identifying a touch-point connecting the separate data streams. Separate data sources may be connected because they refer to the same individual, entity or event. In this paper we present a data source classification system tailored to facilitate the investigation of potential terrorist activity. This taxonomy is structured to illuminate the defining characteristics of a particular terrorist effort and designed to guide reporting to decision makers that is complete, concise, and evidence-based. The classification system has been validated and empirically utilized in the forensic analysis of a simulated terrorist activity. Next-generation analysts can use this schema to label and correlate across existing data streams, assess which critical information may be missing from the data, and identify options for collecting additional data streams to fill information gaps.
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Summary

The role of cyber forensics in criminal investigations has greatly increased in recent years due to the wealth of data that is collected and available to investigators. Physical forensics has also experienced a data volume and fidelity revolution due to advances in methods for DNA and trace evidence analysis. Key...

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Secure embedded systems

Published in:
Lincoln Laboratory Journal, Vol. 22, No. 1, 2016, pp. 110-122.

Summary

Developers seek to seamlessly integrate cyber security within U.S. military system software. However, added security components can impede a system's functionality. System developers need a well-defined approach for simultaneously designing functionality and cyber security. Lincoln Laboratory's secure embedded system co-design methodology uses a security coprocessor to cryptographically ensure system confidentiality and integrity while maintaining functionality.
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Summary

Developers seek to seamlessly integrate cyber security within U.S. military system software. However, added security components can impede a system's functionality. System developers need a well-defined approach for simultaneously designing functionality and cyber security. Lincoln Laboratory's secure embedded system co-design methodology uses a security coprocessor to cryptographically ensure system confidentiality...

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Secure and resilient cloud computing for the Department of Defense

Summary

Cloud computing offers substantial benefits to its users: the ability to store and access massive amounts of data, on-demand delivery of computing services, the capability to widely share information, and the scalability of resource usage. Lincoln Laboratory is developing technology that will strengthen the security and resilience of cloud computing so that the Department of Defense can confidently deploy cloud services for its critical missions.
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Summary

Cloud computing offers substantial benefits to its users: the ability to store and access massive amounts of data, on-demand delivery of computing services, the capability to widely share information, and the scalability of resource usage. Lincoln Laboratory is developing technology that will strengthen the security and resilience of cloud computing...

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