waashk/dblp huggingface dataset:
lossless online ensemble learning (loel) and its application to subcortical segmentation. in this paper, we study the classification problem in the situation where large volumes of training data become available sequentially (online learning). in medical imaging, this is typical, e.g., a 3d brain mri dataset may be gradually collected from a patient population, and not all of the data is available when the analysis begins. first, we describe two common ensemble learning algorithms, adaboost and bagging, and their corresponding online learning versions. we then show why each is ineffective for segmenting a gradually increasing set of medical images. instead, we introduce a new ensemble learning algorithm, termed lossless online ensemble learning (loel). this algorithm is lossless in the online case, compared to its batch mode. loel outperformed online-adaboost and online-bagging when validated on a standardized dataset; it also performed better when used to segment the hippocampus from brain mri scans of patients with alzheimer's disease and matched healthy subjects. among those tested, loel largely outperformed the alternative online learning algorithms and gave excellent error metrics that were consistent between the online and offline case; it also accurately distinguished ad subjects from healthy controls based on automated measures of hippocampal volume.
noninvasive imaging of electrophysiological substrates in post myocardial infarction. the presence of injured tissues after myocardial infarction (mi) creates substrates responsible for fatal arrhythmia; understanding of its arrhythmogenic mechanism requires investigation of the correlation of local abnormality between phenomenal electrical functions and inherent electrophysiological properties during normal sinus rhythm. this paper presents a physiological-model-constrained framework for imaging post-mi electrophysiological substrates from noninvasive body surface potential measurements. using a priori knowledge of general cardiac electrical activity as constraints, it simultaneously reconstruct transmembrane potential dynamics and tissue excitability inside the 3d myocardium, with the central goal to localize and investigate the abnormality in these two different electrophysiological quantities. it is applied to four post-mi patients with quantitative validations by gold standards and notable improvements over existent results.
liver segmentation using automatically defined patient specific b-spline surface models. this paper presents a novel liver segmentation algorithm. this is a model-driven approach; however, unlike previous techniques which use a statistical model obtained from a training set, we initialize patient-specific models directly from their own pre-segmentation. as a result, the non-trivial problems such as landmark correspondences, model registration etc. can be avoided. moreover, by dividing the liver region into three sub-regions, we convert the problem of building one complex shape model into constructing three much simpler models, which can be fitted independently, greatly improving the computation efficiency. a robust graph-based narrow band optimal surface fitting scheme is also presented. the proposed approach is evaluated on 35 ct images. compared to contemporary approaches, our approach has no training requirement and requires significantly less processing time, with an rms error of 2.44±0.53mm against manual segmentation.
de-anonymizing social networks. operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers.privacy is typically protected by anonymization, i.e., removing names, addresses, etc.we present a framework for analyzing privacy and anonymity in social networks and develop a new re-identification algorithm targeting anonymized social-network graphs.to demonstrate its effectiveness on real-world networks, we show that a third of the users who can be verified to have accounts on both twitter, a popular microblogging service, and flickr, an online photo-sharing site, can be re-identified in the anonymous twitter graph with only a 12% error rate.our de-anonymization algorithm is based purely on the network topology, does not require creation of a large number of dummy "sybil" nodes, is robust to noise and all existing defenses, and works even when the overlap between the target network and the adversary's auxiliary information is small.
practical mitigations for timing-based side-channel attacks on modern x86 processors. this paper studies and evaluates the extent to which automated compiler techniques can defend against timing-based side-channel attacks onmodern x86 processors. we study how modern x86 processors can leak timinginformation through side-channels that relate to control flow and data flow. toeliminate key-dependent control flow and key-dependent timing behavior relatedto control flow, we propose the use of if-conversion in a compiler backend, andevaluate a proof-of-concept prototype implementation. furthermore, we demonstratetwo ways in which programs that lack key-dependent control flow and key- dependent cache behavior can still leak timing information on modern x86implementations such as the intel core 2 duo, and propose defense mechanisms against them.
the mastermind attack on genomic data. in this paper, we study the degree to which a genomic string, $q$,leaks details about itself any time it engages in comparison protocolswith a genomic querier, bob, even if those protocols arecryptographically guaranteed to produce no additional information otherthan the scores that assess the degree to which $q$ matches stringsoffered by bob.we show that such scenarios allow bob to play variantsof the game of mastermind with $q$ so as to learn the complete identityof $q$.we show that there are a number of efficient implementationsfor bob to employ in these mastermind attacks, depending on knowledgehe has about the structure of $q$, which show how quickly he candetermine $q$.indeed, we show that bob can discover $q$ using anumber of rounds of test comparisons that is much smaller than thelength of $q$, under various assumptions regarding the types of scoresthat are returned by the cryptographic protocols and whether he can useknowledge about the distribution that $q$ comes from, e.g., usingpublic knowledge about the properties of human dna.we also providethe results of an experimental study we performed on a database ofmitochondrial dna, showing the vulnerability of existing real-world dnadata to the mastermind attack.
quantifying information leaks in outbound web traffic. as the internet grows and network bandwidth continues to increase, administrators are faced with the task of keeping confidential information from leaving their networks. today’s network traffic is so voluminous that manual inspection would be unreasonably expensive. in response, researchers have created data loss prevention systems that check outgoing traffic for known confidential information. these systems stop naïve adversaries from leaking data, but are fundamentally unable to identify encrypted or obfuscated information leaks. what remains is a high-capacity pipe for tunneling data to the internet. we present an approach for quantifying information leak capacity in network traffic. instead of trying to detect the presence of sensitive data—an impossible task in the general case--our goal is to measure and constrain its maximum volume. we take advantage of the insight that most network traffic is repeated or determined by external information, such as protocol specifications or messages sent by a server. by filtering this data, we can isolate and quantify true information flowing from a computer. in this paper, we present measurement algorithms for the hypertext transfer protocol (http), the main protocol for web browsing. when applied to real web browsing traffic, the algorithms were able to discount 98.5% of measured bytes and effectively isolate information leaks.
privacy weaknesses in biometric sketches. the increasing use of biometrics has given rise to new privacy concerns. biometric encryption systems have been proposed in order to alleviate such concerns: rather than comparing the biometric data directly, a key is derived from these data and subsequently knowledge of this key is proved. one specific application of biometric encryption is the use of biometric sketches: in this case biometric template data are protected with biometric encryption. we address the question whether one can undermine a user's privacy given access to biometrically encrypted documents, and more in particular, we examine if an attacker can determine whether two documents were encrypted using the same biometric. this is a particular concern for biometric sketches that are deployed in multiple locations: in one scenario the same biometric sketch is deployed everywhere; in a second scenario the same biometric data is protected with two different biometric sketches. we present attacks on template protection schemes that can be described as fuzzy sketches based on error-correcting codes. we demonstrate how to link and reverse protected templates produced by code-offset and bit-permutation sketches.
blueprint: robust prevention of cross-site scripting attacks for existing browsers. as social networking sites proliferate across the world wide web, complex user-created html content is rapidly becoming the norm rather than the exception.user-created web content is a notorious vector for cross-site scripting (xss) attacks that target websites and confidential user data.in this threat climate, mechanisms that render web applications immune to xss attacks have been of recent research interest.a challenge for these security mechanisms is enabling web applications to accept complex html input from users, while disallowing malicious script content.this challenge is made difficult by anomalous web browser behaviors, which are often used as vectors for successful xss attacks.motivated by this problem, we present a new xss defense strategy designed to be effective in widely deployed existing web browsers, despite anomalous browser behavior.our approach seeks to minimize trust placed on browsers for interpreting untrusted content.we implemented this approach in a tool called blueprint that was integrated with several popular web applications.we evaluated blueprint against a barrage of stress tests that demonstrate strong resistance to attacks, excellent compatibility with web browsers and reasonable performance overheads.
sphinx: a compact and provably secure mix format. sphinx is a cryptographic message format used to relay anonymized messages within a mix network. it is more compact than any comparable scheme, and supports a full set of security features: indistinguishable replies, hiding the path length and relay position, as well as providing unlinkability for each leg of the message's journey over the network. we prove the full cryptographic security of sphinx in the random oracle model, and we describe how it can be used as an efficient drop-in replacement in deployed remailer systems.
automatic discovery and quantification of information leaks. information-flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. we present the first automatic method for information-flow analysis that discovers what information is leaked and computes its comprehensive quantitative interpretation. the leaked information is characterized by an equivalence relation on secret artifacts, and is represented by a logical assertion over the corresponding program variables. our measurement procedure computes the number of discovered equivalence classes and their sizes. this provides a basis for computing a set of quantitative properties, which includes all established information-theoretic measures in quantitative information-flow. our method exploits an inherent connection between formal models of qualitative information-flow and program verification techniques.we provide an implementation of our method that builds upon existing tools for program verification and information-theoretic analysis. our experimental evaluation indicates the practical applicability of the presented method.
noninterference for a practical difc-based operating system. the flume system is an implementation of decentralized information flow control (difc) at the operating system level.prior work has shown flume can be implemented as a practical extension tothe linux operating system, allowing real web applications to achieve useful security guarantees.however, the question remains if the flume system is actually secure.this paper compares flume with other recent difc systems like asbestos, arguing that the latter is inherently susceptible to certain wide-bandwidth covert channels, and proving their absence in flume by means of a noninterference proof in the communicating sequential processes formalism.
prospex: protocol specification extraction. protocol reverse engineering is the process of extracting application-level specifications for network protocols. such specifications are very useful in a number of security-related contexts, for example, to perform deep packet inspection and black-box fuzzing, or to quickly understand custom botnet command and control (c\&c) channels.since manual reverse engineering is a time-consuming and tedious process, a number of systems have been proposed that aim to automate this task. these systems either analyze network traffic directly or monitor the execution of the application that receives the protocol messages. while previous systems show that precise message formats can be extracted automatically, they do not provide a protocol specification.the reason is that they do not reverse engineer the protocol state machine.in this paper, we focus on closing this gap by presenting a system that is capable of automatically inferring state machines. this greatly enhances the results of automatic protocol reverse engineering, while further reducing the need for human interaction. we extend previous work that focuses on behavior-based message format extraction,and introduce techniques for identifying and clustering different types of messages not only based on their structure, but also according to the impact of each message on server behavior.moreover, we present an algorithm for extracting the state machine.we have applied our techniques to a number of real-world protocols, including the command and control protocol used by a malicious bot. our results demonstrate that we are able to extract format specifications for different types of messages and meaningful protocol state machines. we use these protocol specifications to automatically generate input for a stateful fuzzer,allowing us to discover security vulnerabilities in real-world applications.
formally certifying the security of digital signature schemes. we present two machine-checked proofs of the existentialunforgeability under adaptive chosen-message attacks of the fulldomain hash signature scheme. these proofs formalize the originalargument of bellare and rogaway, and an optimal reduction by coronthat provides a tighter bound on the probability of a forgery. bothproofs are developed using certicrypt, a general framework toformalize exact security proofs of cryptographic systems in thecomputational model. since certicrypt is implemented on top of thecoq proof assistant, the proofs are highly trustworthy and can beverified independently and fully automatically.
native client: a sandbox for portable, untrusted x86 native code. this paper describes the design, implementation and evaluation of native client, a sandbox for untrusted x86 native code. native client aims to give browser-based applications the computational performance of native applications without compromising safety. native client uses software fault isolation and a secure runtime to direct system interaction and side effects through interfaces managed by native client. native client provides operating system portability for binary code while supporting performance-oriented features generally absent from web application programming environments, such as thread support, instruction set extensions such as sse, and use of compiler intrinsics and hand-coded assembler. we combine these properties in an open architecture that encourages community review and 3rd-party tools.
clamp: practical prevention of large-scale data leaks. providing online access to sensitive data makes web servers lucrative targets for attackers.a compromise of any of the web server's scripts, applications, or operating system can leak the sensitive data of millions of customers.unfortunately, many systems for stopping data leaks require considerable effort from application developers, hindering their adoption.in this work, we investigate how such leaks can be prevented with minimal developer effort.we propose clamp, an architecture for preventing data leaks even in the presence of web server compromises or sql injection attacks.clamp protects sensitive data by enforcing strong access control on user data and by isolating code running on behalf of different users.by focusing on minimizing developer effort, we arrive at an architecture that allows developers to use familiar operating systems, servers, and scripting languages, while making relatively few changes to application code -- less than 50 lines in our applications.
plaintext recovery attacks against ssh. this paper presents a variety of plaintext-recovering attacks against ssh. we implemented a proof of concept of our attacks against openssh, where we can verifiably recover 14 bits of plaintext from an arbitrary block of ciphertext with probability $2^{-14}$ and 32 bits of plaintext from an arbitrary block of ciphertext with probability $2^{-18}$. these attacks assume the default configuration of a 128-bit block cipher operating in cbc mode. the paper explains why a combination of flaws in the basic design of ssh leads implementations such as openssh to be open to our attacks, why current provable security results for ssh do not cover our attacks, and how the attacks can be prevented in practice.
an epistemic approach to coercion-resistance for electronic voting protocols. coercion resistance is an important and one of themost intricate security requirements of electronicvoting protocols. several definitions of coercionresistance have been proposed in the literature,including definitions based on symbolic models.however, existing definitions in such models arerather restricted in their scope and quite complex.in this paper, we therefore propose a new definitionof coercion resistance in a symbolic setting, basedon an epistemic approach. our definition isrelatively simple and intuitive. it allows for afine-grained formulation of coercion resistance andcan be stated independently of a specific, symbolicprotocol and adversary model. as a proof of concept,we apply our definition to three votingprotocols. in particular, we carry out the firstrigorous analysis of the recently proposed civitassystem.we precisely identify those conditions underwhich this system guarantees coercion resistance orfails to be coercion resistant. we also analyzeprotocols proposed by lee et al. and okamoto.
password cracking using probabilistic context-free grammars. choosing the most effective word-mangling rules to use when performing a dictionary-based password cracking attack can be a difficult task. in this paper we discuss a new method that generates password structures in highest probability order. we first automatically create a probabilistic context-free grammar based upon a training set of previously disclosed passwords. this grammar then allows us to generate word-mangling rules, and from them, password guesses to be used in password cracking. we will also show that this approach seems to provide a more effective way to crack passwords as compared to traditional methods by testing our tools and techniques on real password sets. in one series of experiments, training on a set of disclosed passwords, our approach was able to crack 28% to 129% more passwords than john the ripper, a publicly available standard password cracking program.
secure content sniffing for web browsers, or how to stop papers from reviewing themselves. cross-site scripting defenses often focus on html documents, neglecting attacks involving the browser's content-sniffing algorithm, which can treat non-html content as html.web applications, such as the one that manages this conference, must defend themselves against these attacks or risk authors uploading malicious papers that automatically submit stellar self-reviews.in this paper, we formulate content-sniffing xss attacks and defenses.we study content-sniffing xss attacks systematically by constructing high-fidelity models of the content-sniffing algorithms used by four major browsers.we compare these models with web site content filtering policies to construct attacks.to defend against these attacks, we propose and implement a principled content-sniffing algorithm that provides security while maintaining compatibility.our principles have been adopted, in part, by internet explorer 8 and, in full, by google chrome and the html 5 working group.
automatic reverse engineering of malware emulators. malware authors have recently begun using emulation technology to obfuscate their code. they convert native malware binaries into bytecode programs written in a randomly generated instruction set and paired with a native binary emulator that interprets the bytecode. no existing malware analysis can reliably reverse this obfuscation technique.in this paper, we present the first work in automatic reverse engineering of malware emulators. our algorithms are based on dynamic analysis. we execute the emulated malware in a protected environment and record the entire x86 instruction trace generated by the emulator. we then use dynamic data-flow and taint analysis over the trace to identify data buffers containing the bytecode program and extract the syntactic and semantic information about the bytecode instruction set. with these analysis outputs, we are able to generate data structures, such as control-flow graphs, that provide the foundation for subsequent malware analysis. we implemented a proof-of-concept system calledrotalume and evaluated it using both legitimate programs and malware emulated by vmprotect and code virtualizer. the results show that rotalume accurately reveals the syntax and semantics of emulated instruction sets and reconstructs execution paths of original programs from their bytecode representations.
a logic of secure systems and its application to trusted computing. we present a logic for reasoning about properties of securesystems.the logic is built around a concurrent programminglanguage with constructs for modeling machines with sharedmemory, a simple form of access control on memory, machineresets, cryptographic operations, network communication, anddynamically loading and executing unknown(and potentially untrusted) code.the adversary's capabilities are constrained by the system interface as defined in the programming model (leading to the name csi).we develop a sound proof system for reasoning about programs without explicitly reasoning about adversary actions. we use the logic to characterize trusted computing primitives and prove code integrity and execution integrity properties of two remote attestation protocols. the proofs make precise assumptions needed for the security of these protocols and reveal an insecure interaction between the two protocols.