There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Data Mining - Concepts and Techniques.

In several distributed systems a user should only be able to access data if a user posses a certain set of credentials or attributes. Currently, the only method for enforcing such policies is to employ a trusted server to store the data and mediate access control. However, if any server storing the data is compromised, then the confidentiality of the data will be compromised. In this paper we present a system for realizing complex access control on encrypted data that we call ciphertext-policy attribute-based encryption. By using our techniques encrypted data can be kept confidential even if the storage server is untrusted; moreover, our methods are secure against collusion attacks. Previous attribute-based encryption systems used attributes to describe the encrypted data and built policies into user's keys; while in our system attributes are used to describe a user's credentials, and a party encrypting data determines a policy for who can decrypt. Thus, our methods are conceptually closer to traditional access control methods such as role-based access control (RBAC). In addition, we provide an implementation of our system and give performance measurements.

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Ciphertext-Policy Attribute-Based Encryption

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

Comparing the expressive power of access control models is recognized as a fundamental problem in computer security. Such comparisons are generally based on simulations between different access control schemes. However, the definitions for simulations that are used in the literature make it impossible to put results and claims about the expressive power of access control models into a single context and to compare such models to one another in a meaningful way.We propose a theory for comparing the expressive power of access control models. We perceive access control systems as state-transition systems and require simulations to preserve security properties. We discuss the rationale behind such a theory, apply the theory to reexamine some existing work on the expressive power of access control models in the literature and present three results. We show that: (1) RBAC with a particular administrative model from the literature (ARBAC97) is limited in its expressive power; (2) ATAM (Augmented Typed Access Matrix) is more expressive than TAM (Typed Access Matrix), thereby solving an open problem posed in the literature; and (3) a trust-management language is at least as expressive as RBAC with a particular administrative model (the URA97 component of ARBAC97).

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Comparing the expressive power of access control models

One of Android’s main defense mechanisms against malicious apps is a risk communication mechanism which, before a user installs an app, warns the user about the permissions the app requires, trusting that the user will make the right decision. This approach has been shown to be ineffective as it presents the risk information of each app in a “stand-alone” fashion and in a way that requires too much technical knowledge and time to distill useful information. We discuss the desired properties of risk signals and relative risk scores for Android apps in order to generate another metric that users can utilize when choosing apps. We present a wide range of techniques to generate both risk signals and risk scores that are based on heuristics as well as principled machine learning techniques. Experimental results conducted using real-world data sets show that these methods can effectively identify malware as very risky, are simple to understand, and easy to use.

Generating Summary Risk Scores for Mobile Applications

Host compromise is a serious computer security problem today. To better protect hosts, several Mandatory Access Control systems, such as Security Enhanced Linux (SELinux) and AppArmor, have been introduced. In this paper we propose an approach to analyze and compare the quality of protection offered by these different MAC systems. We introduce the notion of vulnerability surfaces under attack scenarios as the measurement of protection quality, and implement a tool called VulSAN for computing such vulnerability surfaces. In VulSAN, we encode security policies, system states, and system rules using logic programs. Given an attack scenario, VulSAN computes a host attack graph and the vulnerability surface. We apply our approach to compare SELinux and AppArmor policies in several Linux distributions and discuss the results. Our tool can also be used by Linux system administrators as a system hardening tool. Because of its ability to analyze SELinux as well as AppArmor policies, it can be used for most enterprise Linux distributions and home user distributions.

/pdf/analyzing-and-comparing-the-protection-quality-of-security-3a6upibtfv.pdf

Analyzing and Comparing the Protection Quality of Security Enhanced Operating Systems.

The X.509 Public-Key Infrastructure has long been used in the SSL/TLS protocol to achieve authentication. A recent trend of Internet-of-Things (IoT) systems employing small footprint SSL/TLS libraries for secure communication has further propelled its prominence. The security guarantees provided by X.509 hinge on the assumption that the underlying implementation rigorously scrutinizes X.509 certificate chains, and accepts only the valid ones. Noncompliant implementations of X.509 can potentially lead to attacks and/or interoperability issues. In the literature, black-box fuzzing has been used to find flaws in X.509 validation implementations, fuzzing, however, cannot guarantee coverage and thus severe flaws may remain undetected. To thoroughly analyze X.509 implementations in small footprint SSL/TLS libraries, this paper takes the complementary approach of using symbolic execution. We observe that symbolic execution, a technique proven to be effective in finding software implementation flaws, can also be leveraged to expose noncompliance in X.509 implementations. Directly applying an off-the-shelf symbolic execution engine on SSL/TLS libraries is, however, not practical due to the problem of path explosion. To this end, we propose the use of SymCerts, which are X.509 certificate chains carefully constructed with a mixture of symbolic and concrete values. Utilizing SymCerts and some domain-specific optimizations, we symbolically execute the certificate chain validation code of each library and extract path constraints describing its accepting and rejecting certificate universes. These path constraints help us identify missing checks in different libraries. For exposing subtle but intricate noncompliance with X.509 standard, we cross-validate the constraints extracted from different libraries to find further implementation flaws. Our analysis of 9 small footprint X.509 implementations has uncovered 48 instances of noncompliance. Findings and suggestions provided by us have already been incorporated by developers into newer versions of their libraries.

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SymCerts: Practical Symbolic Execution for Exposing Noncompliance in X.509 Certificate Validation Implementations

The Sparse Vector Technique (SVT) is a fundamental technique for satisfying differential privacy and has the unique quality that one can output some query answers without apparently paying any privacy cost. SVT has been used in both the interactive setting, where one tries to answer a sequence of queries that are not known ahead of the time, and in the non-interactive setting, where all queries are known. Because of the potential savings on privacy budget, many variants for SVT have been proposed and employed in privacy-preserving data mining and publishing. However, most variants of SVT are actually not private. In this paper, we analyze these errors and identify the misunderstandings that likely contribute to them. We also propose a new version of SVT that provides better utility, and introduce an effective technique to improve the performance of SVT. These enhancements can be applied to improve utility in the interactive setting. Through both analytical and experimental comparisons, we show that, in the non-interactive setting (but not the interactive setting), the SVT technique is unnecessary, as it can be replaced by the Exponential Mechanism (EM) with better accuracy.

Ninghui Li

Papers

Comparing the expressive power of access control models

Generating Summary Risk Scores for Mobile Applications

Analyzing and Comparing the Protection Quality of Security Enhanced Operating Systems.

SymCerts: Practical Symbolic Execution for Exposing Noncompliance in X.509 Certificate Validation Implementations

Understanding the Sparse Vector Technique for Differential Privacy