Showing papers by "SRI International published in 2006"

Attribute-based encryption for fine-grained access control of encrypted data

Abstract: As more sensitive data is shared and stored by third-party sites on the Internet, there will be a need to encrypt data stored at these sites. One drawback of encrypting data, is that it can be selectively shared only at a coarse-grained level (i.e., giving another party your private key). We develop a new cryptosystem for fine-grained sharing of encrypted data that we call Key-Policy Attribute-Based Encryption (KP-ABE). In our cryptosystem, ciphertexts are labeled with sets of attributes and private keys are associated with access structures that control which ciphertexts a user is able to decrypt. We demonstrate the applicability of our construction to sharing of audit-log information and broadcast encryption. Our construction supports delegation of private keys which subsumesHierarchical Identity-Based Encryption (HIBE).

Conjunctive, Subset, and Range Queries on Encrypted Data.

Abstract: We construct public-key systems that support comparison queries (x ≥ a) on encrypted data as well as more general queries such as subset queries (x ∈ S). These systems support arbitrary conjunctive queries (P1∧· · ·∧P`) without leaking information on individual conjuncts. In addition, we present a general framework for constructing and analyzing public-key systems supporting queries on encrypted data.

System and method for releasably holding a surgical instrument

Abstract: The invention is directed to a system and method for releasably holding a surgical instrument (14), such as an endoscopic instrument configured for delivery through a small percutaneous penetration in a patient. The instrument comprises an elongate shaft (100) with a pair of mounting pins (116) laterally extending from the shaft between its proximal and distal ends. An instrument holder comprises a support having a central bore (202) and an axially extending slot (204) for receiving the instrument shaft and the mounting pins. A pair of locking slots (206) are cut into the support transversely to and in communication with the axial slot so that the mounting pins can be rotated within the locking slots. The instrument support further includes a latch assembly for automatically locking the mounting pins within the locking slots to releasably couple the instrument to the instrument holder. With this twist-lock motion, the surgeon can rapidly engage and disengage various instruments from the holder during a surgical procedure, such as open surgery, laparoscopy or thoracoscopy.

The YICES SMT Solver

Abstract: SMT stands for Satisfiability Modulo Theories. An SMT solver decides the satisfiability of propositionally complex formulas in theories such as arithmetic and uninterpreted functions with equality. SMT solving has numerous applications in automated theorem proving, in hardware and software verification, and in scheduling and planning problems. This paper describes Yices, an efficient SMT solver developed at SRI International. Yices supports a rich combination of first-order theories that occur frequently in software and hardware modeling: arithmetic, uninterpreted functions, bit vectors, arrays, recursive datatypes, and more. Beyond pure SMT solving, Yices can solve weighted MAX-SMT problems, compute unsatisfiable cores, and construct models. Yices is the main decision procedure used by the SAL model checking environment, and it is being integrated to the PVS theorem prover. As a MAX-SMT solver, Yices is the main component of the probabilistic consistency engine used in SRI’s CALO system.

Escherichia coli K-12: a cooperatively developed annotation snapshot—2005

Abstract: The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles.

A fast linear-arithmetic solver for DPLL(T)

Abstract: We present a new Simplex-based linear arithmetic solver that can be integrated efficiently in the DPLL(T) framework. The new solver improves over existing approaches by enabling fast backtracking, supporting a priori simplification to reduce the problem size, and providing an efficient form of theory propagation. We also present a new and simple approach for solving strict inequalities. Experimental results show substantial performance improvements over existing tools that use other Simplex-based solvers in DPLL(T) decision procedures. The new solver is even competitive with state-of-the-art tools specialized for the difference logic fragment.

Implementation and Effects Of One-to-One Computing Initiatives: A Research Synthesis

Abstract: There are now a large number of initiatives designed to make laptops with wireless connectivity available to all students in schools. This paper synthesizes findings from research and evaluation studies that analyzed implementation and effects of one-to-one initiatives from a range of countries. Factors related to successful implementation reported in the research include extensive teacher professional development, access to technical support, and positive teacher attitudes toward student technology use. Outcome studies with rigorous designs are few, but those studies that did measure outcomes consistently reported positive effects on technology use, technology literacy, and writing skills.

Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools

Abstract: The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence-function relationships on a large scale. There are a number of applications for these data, and we have implemented web services that address three of them. The first is a protein classification service. Proteins can be classified, using only their amino acid sequences, to evolutionary groups at both the family and subfamily levels. Specific subfamilies, and often families, are further classified when possible according to their functions, including molecular function and the biological processes and pathways they participate in. The second application, then, is an expression data analysis service, where functional classification information can help find biological patterns in the data obtained from genome-wide experiments. The third application is a coding single-nucleotide polymorphism scoring service. In this case, information about evolutionarily related proteins is used to assess the likelihood of a deleterious effect on protein function arising from a single substitution at a specific amino acid position in the protein. All three web services are available at http://www.pantherdb.org/tools.

Anonymous hierarchical identity-based encryption (without random oracles)

Abstract: We present an identity-based cryptosystem that features fully anonymous ciphertexts and hierarchical key delegation. We give a proof of security in the standard model, based on the mild Decision Linear complexity assumption in bilinear groups. The system is efficient and practical, with small ciphertexts of size linear in the depth of the hierarchy. Applications include search on encrypted data, fully private communication, etc. Our results resolve two open problems pertaining to anonymous identity-based encryption, our scheme being the first to offer provable anonymity in the standard model, in addition to being the first to realize fully anonymous HIBE at all levels in the hierarchy.

Secure attribute-based systems

Abstract: Attributes define, classify, or annotate the datum to which they are assigned. However, traditional attribute architectures and cryptosystems are ill-equipped to provide security in the face of diverse access requirements and environments. In this paper, we introduce a novel secure information management architecture based on emerging attribute-based encryption (ABE) primitives. A policy system that meets the needs of complex policies is defined and illustrated. Based on the needs of those policies, we propose cryptographic optimizations that vastly improve enforcement efficiency. We further explore the use of such policies in two example applications: a HIPAA compliant distributed file system and a social network. A performance analysis of our ABE system and example applications demonstrates the ability to reduce cryptographic costs by as much as 98% over previously proposed constructions. Through this, we demonstrate that our attribute system is an efficient solution for securely managing information in large, loosely-coupled, distributed systems.

Within-class covariance normalization for SVM-based speaker recognition.

Abstract: This paper extends the within-class covariance normalization (WCCN) technique described in [1, 2] for training generalized linear kernels. We describe a practical procedure for applying WCCN to an SVM-based speaker recognition system where the input feature vectors reside in a high-dimensional space. Our approach involves using principal component analysis (PCA) to split the original feature space into two subspaces: a low-dimensional “PCA space” and a high-dimensional “PCA-complement space.” After performing WCCN in the PCA space, we concatenate the resulting feature vectors with a weighted version of their PCAcomplements. When applied to a state-of-the-art MLLR-SVM speaker recognition system, this approach achieves improvements of up to 22% in EER and 28% in minimum decision cost function (DCF) over our previous baseline. We also achieve substantial improvements over an MLLR-SVM system that performs WCCN in the PCA space but discards the PCA-complement.

5'-AMP-activated protein kinase (AMPK) is induced by low-oxygen and glucose deprivation conditions found in solid-tumor microenvironments.

Abstract: We have been studying the relationship between the activity of hypoxia-inducible factor 1 (HIF-1), the primary transcriptional regulator of the response of mammalian cells to oxygen deprivation (e.g., see references 21, 43, and 50) and the regulation of c-Jun/AP-1 transcription factors (31, 32). We determined that c-Jun N-terminal phosphorylation is induced by low-oxygen conditions (hypoxia or anoxia; called hypoxia hereafter) in an HIF-1-dependent manner (31) and showed that this HIF-1-dependent c-Jun phosphorylation absolutely requires extracellular glucose utilization (32). Together, these findings suggest that enhanced glucose absorption and/or glycolytic activity mediated by HIF-1 in response to hypoxia activates c-Jun/AP-1, as well as other targets of c-Jun N-terminal kinases. To further investigate this potential mechanism, we focused on determining the contribution of bioenergetics—ATP depletion—to hypoxia-inducible c-Jun phosphorylation in wild-type (WT) and HIF-1-null mouse embryo fibroblasts (MEFs). While exploring cellular mechanisms of ATP regulation, we observed that 5′-AMP-activated protein kinase (AMPK) activity was induced in both cell types, particularly under conditions of hypoxia and glucose deprivation. This observation suggested the hypothesis that AMPK is important for the adaptive responses of energetically stressed cells in the hypoxic and glucose-deprived microenvironments present in solid tumors (e.g., reviewed in references 35 and 59). AMPK activity is defined by a class of evolutionarily conserved serine/threonine kinases that are sensitive to various environmental stresses, especially those that perturb cellular energy status (reviewed in references 9, 19, and 47). Different members of the AMPK catalytic subunit subfamily have been characterized; the α subunits (collectively, AMPKα1 and -α2) are the most widely expressed in mammalian cells (36). AMPK is a heterotrimeric complex consisting of an α subunit and β and γ regulatory subunits, each of which is encoded by distinct genes (α1 and α2; β1 and β2; γ1, γ2, and γ3) (19). In terms of a role in ATP regulation, decreased cellular ATP levels promote AMPK activation through the allosteric binding of AMP, which in effect enables AMPK to sense increases in the cellular [AMP]/[ATP] ratio. Full activation of AMPK also requires specific phosphorylation within the activation loop of the catalytic domain of the α subunit (at Thr172 in humans and mice) by LKB1, a serine/threonine protein kinase and tumor suppressor (36, 37, 52). LKB1 is thus an AMPK kinase. Recently, mammalian Ca2+/calmodulin-dependent kinase kinases have also been identified as AMPK kinases (reviewed in reference 6). Activated AMPK phosphorylates diverse targets, including many that are directly involved in controlling cellular energy metabolism (22, 34). In cells exposed to an energy-depleting stress, AMPK is believed to function as an energy sensor that inhibits ATP-consuming processes and stimulates ATP-producing processes to optimize total cellular ATP levels for maintaining critical physiological functions (or for survival in response to extreme stress) (19). For example, in cells exposed to hypoxic or ischemic conditions that significantly deplete total ATP, activated AMPK can stimulate ATP generation by increasing both glucose absorption and glycolysis (e.g., see references 2, 19, and 22). AMPK can also generate ATP by phosphorylating and inhibiting the metabolic enzymes acetyl coenzyme A (acetyl-CoA) carboxylases 1 and 2 (ACC1/2), which synthesize malonyl-CoA (19). Malonyl-CoA synthesized by ACC1 is necessary for de novo fatty acid synthesis, whereas that synthesized by ACC2 inhibits fatty acid transport into the mitochondrion, the site of ATP production by the process of fatty acid β oxidation (18). Thus, AMPK-dependent inhibition of ACC1/2 can divert cellular metabolism from consuming ATP during fatty acid biosynthesis to producing ATP by oxidizing fatty acid stores. In the present study, we found that the combination of hypoxia and glucose deprivation decreased total cellular ATP levels to the same extent in both WT and HIF-1α-null cells. This finding supports our previous conclusion that increased intracellular glucose, rather than decreased ATP levels, is responsible for the stimulation of c-Jun N-terminal kinase activity in WT cells exposed to hypoxia. AMPK activity, conventionally defined by phosphorylation of AMPK target sites on the metabolic enzymes ACC1/2 (19), was strongly activated in both WT and HIF-1α-null cells under the same conditions of hypoxia and glucose deprivation, which is consistent with its function as a sensor of ATP depletion. However, AMPK activity was also rapidly induced in both cell types following exposure to hypoxia in the presence of glucose, even though total cellular ATP was not significantly depleted. By using genetically manipulated MEFs nullizygous for AMPK expression, we directly demonstrated that AMPK activity is sensitive to a wide range of low-oxygen conditions, at least in mesenchymal cells. To determine whether these hypoxia-inducible responses of AMPK also occur in vivo, we prepared tumor xenografts from transformed derivatives of the same WT and HIF-1α-null cells, and exposed tumor-bearing mice to the hypoxia probe pimonidazole (3, 10, 44, 45). Immunohistochemical analysis of these tumors indicated that AMPK activity was prevalent in hypoxic regions of both tumor types, especially in viable areas near necrosis. By using tumor xenografts prepared from identically transformed WT and AMPKα-null cells, we determined that the absence of AMPK activity greatly inhibited the growth of this experimental tumor type. We propose that activation of AMPK in hypoxic or ischemic microenvironments may be critical for cell survival and thus would represent a novel protective mechanism for metabolically depressed or ATP-deficient cells.

Anonymous Hierarchical Identity-Based Encryption (Without Random Oracles).

Abstract: We present an identity-based cryptosystem that features fully anonymous ciphertexts and hierarchical key delegation. We give a proof of security in the standard model, based on the mild Decision Linear complexity assumption in bilinear groups. The system is efficient and practical, with small ciphertexts of size linear in the depth of the hierarchy. Applications include search on encrypted data, fully private communication, etc. Our results resolve two open problems pertaining to anonymous identity-based encryption, our scheme being the first to offer provable anonymity in the standard model, in addition to being the first to realize fully anonymous HIBE at all levels in the hierarchy.

Fully collusion resistant traitor tracing with short ciphertexts and private keys

Abstract: We construct a fully collusion resistant tracing traitors system with sublinear size ciphertexts and constant size private keys. More precisely, let N be the total number of users. Our system generates ciphertexts of size $O(\sqrt{N})$ and private keys of size O(1). We first introduce a simpler primitive we call private linear broadcast encryption (PLBE) and show that any PLBE gives a tracing traitors system with the same parameters. We then show how to build a PLBE system with $O(\sqrt{N})$ size ciphertexts. Our system uses bilinear maps in groups of composite order.

Using Model-based Intrusion Detection for SCADA Networks

Abstract: In a model-based intrusion detection approach for protecting SCADA networks, we construct models that characterize the expected/acceptable behavior of the system, and detect attacks that cause violations of these models. Process control networks tend to have static topologies, regular trac patterns, and a limited number of applications and protocols running on them. Thus, we believe that model-based monitoring, which has the potential for detecting unknown attacks, is more feasible for control networks than for general enterprise networks. To this end, we describe three model-based techniques that we have developed and a prototype implementation of them for monitoring Modbus TCP networks.

Sequential aggregate signatures and multisignatures without random oracles

Abstract: We present the first aggregate signature, the first multisignature, and the first verifiably encrypted signature provably secure without random oracles. Our constructions derive from a novel application of a recent signature scheme due to Waters. Signatures in our aggregate signature scheme are sequentially constructed, but knowledge of the order in which messages were signed is not necessary for verification. The aggregate signatures obtained are shorter than Lysyanskaya et al. sequential aggregates and can be verified more efficiently than Boneh et al. aggregates. We also consider applications to secure routing and proxy signatures.

Does literacy mediate the relationship between education and health outcomes? A study of a low-income population with diabetes.

Abstract: dSYNOPSIS Objectives. We sought to determine whether literacy mediates the relationship between education and glycemic control among diabetes patients. Methods. We measured educational attainment, literacy using the Short Test of Functional Health Literacy in Adults (s-TOFHLA), and glycemic control (HbA1c) in 395 diabetes patients at a U.S. public hospital. We performed path analysis to compare two competing models to explain glycemic control. The direct effects model estimated how education was related to HbA1c; the mediational model estimated the strength of the direct relationship when the additional pathway from education to literacy to HbA1c was added. Results. Both the model with a direct effect of education on HbA1c and the model with literacy as a mediator were supported by good fit to observed data. The mediational model, however, was a significant improvement, with the additional path from literacy to HbA1c reducing the discrepancy from observed data (p0.01). After including this path, the direct relationship between education and HbA1c fell to a non-significant threshold. Conclusions. In a low-income population with diabetes, literacy mediated the relationship between education and glycemic control. This finding has important implications for both education and health policy.

Method and apparatus for wireless network security

Abstract: In one embodiment, the present invention is a method and apparatus for wireless network security. In one embodiment, a method for securing a wireless computing network includes receiving a communication from an unidentified transmitter, identifying the transmitter in accordance with a fingerprint generated from one or more radio frequency signal characteristics extracted from the communication, and taking action in response to an identity of the transmitter.

Sequential aggregate signatures and multisignatures without random oracles

Abstract: We present the first aggregate signature, the first multisignature, and the first verifiably encrypted signature provably secure without random oracles. Our constructions derive from a novel application of a recent signature scheme due to Waters. Signatures in our aggregate signature scheme are sequentially constructed, but knowledge of the order in which messages were signed is not necessary for verification. The aggregate signatures obtained are shorter than Lysyanskaya et al. sequential aggregates and can be verified more efficiently than Boneh et al. aggregates. We also consider applications to secure routing and proxy signatures.

Learning Theories and Education: Toward a Decade of Synergy

Abstract: Acknowledgments: This work was supported by a grant from the National Science Foundation (NSF#0354453). Any opinions, findings and conclusions expressed in the paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors wish to thank the following individuals for their contributions to the chapter: Leah Bricker, Hank Clark, Barbara Conboy, Joan Davis, Katie Hardin, Beth Koemans, Tiffany Lee, Laurie McCarthy, Maisy McGaughey, Raj Raizada, Suzanne Reeve, Maritza Rivera-Gaxiola, Tom Satwicz, Yang Zhang, and Heather Toomey Zimmmerman.

Compact group signatures without random oracles

Abstract: We present the first efficient group signature scheme that is provably secure without random oracles. We achieve this result by combining provably secure hierarchical signatures in bilinear groups with a novel adaptation of the recent Non-Interactive Zero Knowledge proofs of Groth, Ostrovsky, and Sahai. The size of signatures in our scheme is logarithmic in the number of signers; we prove it secure under the Computational Diffie-Hellman and the Subgroup Decision assumptions in the model of Bellare, Micciancio, and Warinshi, as relaxed by Boneh, Boyen, and Shacham.

Strongly unforgeable signatures based on computational diffie-hellman

Abstract: A signature system is said to be strongly unforgeable if the signature is existentially unforgeable and, given signatures on some message m, the adversary cannot produce a new signature on m. Strongly unforgeable signatures are used for constructing chosen-ciphertext secure systems and group signatures. Current efficient constructions in the standard model (i.e. without random oracles) depend on relatively strong assumptions such as Strong-RSA or Strong-Diffie-Hellman. We construct an efficient strongly unforgeable signature system based on the standard Computational Diffie-Hellman problem in bilinear groups.

Educating Students With Emotional Disturbances: A National Perspective on School Programs and Services

Abstract: This article provides a national perspective on the schools and school programs for students with emotional disturbances (ED) who are served in special education, using nationally representative da...

Pharmacogenomics: Challenges and Opportunities

Abstract: The outcome of drug therapy is often unpredictable, ranging from beneficial effects to lack of efficacy to serious adverse effects. Variations in single genes are 1 well-recognized cause of such unpredictability, defining the field of pharmacogenetics (see Glossary). Such variations may involve genes controlling drug metabolism, drug transport, disease susceptibility, or drug targets. The sequencing of the human genome and the cataloguing of variants across human genomes are the enabling resources for the nascent field of pharmacogenomics (see Glossary), which tests the idea that genomic variability underlies variability in drug responses. However, there are many challenges that must be overcome to apply rapidly accumulating genomic information to understand variable drug responses, including defining candidate genes and pathways; relating disease genes to drug response genes; precisely defining drug response phenotypes; and addressing analytic, ethical, and technological issues involved in generation and management of large drug response data sets. Overcoming these challenges holds the promise of improving new drug development and ultimately individualizing the selection of appropriate drugs and dosages for individual patients.

Measuring constraint-set utility for partitional clustering algorithms

Abstract: Clustering with constraints is an active area of machine learning and data mining research. Previous empirical work has convincingly shown that adding constraints to clustering improves performance, with respect to the true data labels. However, in most of these experiments, results are averaged over different randomly chosen constraint sets, thereby masking interesting properties of individual sets. We demonstrate that constraint sets vary significantly in how useful they are for constrained clustering; some constraint sets can actually decrease algorithm performance. We create two quantitative measures, informativeness and coherence, that can be used to identify useful constraint sets. We show that these measures can also help explain differences in performance for four particular constrained clustering algorithms.

Method and apparatus for identifying wireless transmitters

Abstract: In one embodiment, the present invention is a method and apparatus for identifying wireless transmitters. In one embodiment, a method for identifying a transmitter in a wireless computing network includes extracting one or more radio frequency signal characteristics from a communication from the transmitter and generating a fingerprint of the transmitter in accordance at least one of the extracted radio frequency signal characteristics.