Decades of research on distributed file systems and storage systems exists. New researchers and engineers have a lot of literature to study, but only a comparatively small number of high-level design choices are available when creating a distributed file system. And within each aspect of the system, typically several common approaches are used. So, rather than surveying distributed file systems, this article presents a survey of important design decisions and, within those decisions, the most commonly used options. It also presents a qualitative exploration of their tradeoffs. We include several relatively recent designs and their variations that illustrate other tradeoff choices in the design space, despite being underexplored. In doing so, we provide a primer on distributed file systems, and we also show areas that are overexplored and underexplored, in the hopes of inspiring new research.

We present a new side-channel attack that targets one of the most fundamental software caches in modern computer systems: the operating system page cache. The page cache is a pure software cache that contains all disk-backed pages, including program binaries, shared libraries, and other files. On Windows, dynamic pages are also part of this cache and can be attacked as well, e.g., data, heap, and stacks. Our side channel permits unprivileged monitoring of accesses to these pages of other processes, with a spatial resolution of 4kB and a temporal resolution of 2µs on Linux (≤6.7 measurements per second), and 466ns on Windows 10 (≤223 measurements per second). We systematically analyze the side channel by demonstrating different hardware-agnostic local attacks, including a sandbox-bypassing high-speed covert channel, an ASLR break on Windows 10, and various information leakages that can be used for targeted extortion, spam campaigns, and more directly for UI redressing attacks. We also show that, as with hardware cache attacks, we can attack the generation of temporary passwords on vulnerable cryptographic implementations. Our hardware-agnostic attacks can be mitigated with our proposed security patches, but the basic side channel remains exploitable via timing measurements. We demonstrate this with a remote covert channel exfiltrating information from a colluding process through innocuous server requests.

Existing bare-metal cloud services that provide users with physical servers have a number of serious disadvantages over their virtual alternatives, including slow provisioning times, difficulty for users to release servers (physical machines) and then reuse them to handle changes in demand, and poor tolerance to failures. We introduce M2, a bare-metal cloud service that uses network-mounted boot drives to overcome these disadvantages. We describe the architecture and implementation of M2 and compare its agility, scalability and performance to existing systems. We show that M2 can reduce provisioning time by over 50% while offering richer functionality, and comparable run time performance with respect to tools that provision images into local disks. M2 is open source and available at https://github.com/CCI-MOC/ims.

Abstract Monero is a privacy-centric cryptocurrency that allows users to obscure their transactions by including chaff coins, called “mixins,” along with the actual coins they spend. In this paper, we empirically evaluate two weaknesses in Monero’s mixin sampling strategy. First, about 62% of transaction inputs with one or more mixins are vulnerable to “chain-reaction” analysis - that is, the real input can be deduced by elimination. Second, Monero mixins are sampled in such a way that they can be easily distinguished from the real coins by their age distribution; in short, the real input is usually the “newest” input. We estimate that this heuristic can be used to guess the real input with 80% accuracy over all transactions with 1 or more mixins. Next, we turn to the Monero ecosystem and study the importance of mining pools and the former anonymous marketplace AlphaBay on the transaction volume. We find that after removing mining pool activity, there remains a large amount of potentially privacy-sensitive transactions that are affected by these weaknesses. We propose and evaluate two countermeasures that can improve the privacy of future transactions.

We propose a new Exokernel-like layer to allow mutually untrusting physically deployed services to efficiently share the resources of a data center. We believe that such a layer offers not only efficiency gains, but may also enable new economic models, new applications, and new security-sensitive uses. A prototype (currently in active use) demonstrates that the proposed layer is viable, and can support a variety of existing provisioning tools and use cases.

We are developing a new public cloud, the Massachusetts Open Cloud (MOC) based on the model of an Open Cloud exchange (OCX). We discuss in this paper the vision of an OCX and how we intend to realize it using the Open Stack open-source cloud platform in the MOC. A limited form of an OCX can be achieved today by layering new services on top of Open Stack. We have performed an analysis of Open Stack to determine the changes needed in order to fully realize the OCX model. We describe these proposed changes, which although significant and requiring broad community involvement will provide functionality of value to both existing single-provider clouds as well as future multi-provider ones.

BACKGROUND: As the amount of scientific data grows, peer-reviewed Scientific Data Analysis Resources (SDARs) such as published software programs, databases and web servers have had a strong impact on the productivity of scientific research. SDARs are typically linked to using an Internet URL, which have been shown to decay in a time-dependent fashion. What is less clear is whether or not SDAR-producing group size or prior experience in SDAR production correlates with SDAR persistence or whether certain institutions or regions account for a disproportionate number of peer-reviewed resources. METHODS: We first quantified the current availability of over 26,000 unique URLs published in MEDLINE abstracts/titles over the past 20 years, then extracted authorship, institutional and ZIP code data. We estimated which URLs were SDARs by using keyword proximity analysis. RESULTS: We identified 23,820 non-archival URLs produced between 1996 and 2013, out of which 11,977 were classified as SDARs. Production of SDARs as measured with the Gini coefficient is more widely distributed among institutions (.62) and ZIP codes (.65) than scientific research in general, which tends to be disproportionately clustered within elite institutions (.91) and ZIPs (.96). An estimated one percent of institutions produced 68% of published research whereas the top 1% only accounted for 16% of SDARs. Some labs produced many SDARs (maximum detected = 64), but 74% of SDAR-producing authors have only published one SDAR. Interestingly, decayed SDARs have significantly fewer average authors (4.33 +/- 3.06), than available SDARs (4.88 +/- 3.59) (p < 8.32 × 10-4). Approximately 3.4% of URLs, as published, contain errors in their entry/format, including DOIs and links to clinical trials registry numbers. CONCLUSION: SDAR production is less dependent upon institutional location and resources, and SDAR online persistence does not seem to be a function of infrastructure or expertise. Yet, SDAR team size correlates positively with SDAR accessibility, suggesting a possible sociological factor involved. While a detectable URL entry error rate of 3.4% is relatively low, it raises the question of whether or not this is a general error rate that extends to additional published entities.

BACKGROUND: The dynamic, decentralized world-wide-web has become an essential part of scientific research and communication. Researchers create thousands of web sites every year to share software, data and services. These valuable resources tend to disappear over time. The problem has been documented in many subject areas. Our goal is to conduct a cross-disciplinary investigation of the problem and test the effectiveness of existing remedies. RESULTS: We accessed 14,489 unique web pages found in the abstracts within Thomson Reuters' Web of Science citation index that were published between 1996 and 2010 and found that the median lifespan of these web pages was 9.3 years with 62% of them being archived. Survival analysis and logistic regression were used to find significant predictors of URL lifespan. The availability of a web page is most dependent on the time it is published and the top-level domain names. Similar statistical analysis revealed biases in current solutions: the Internet Archive favors web pages with fewer layers in the Universal Resource Locator (URL) while WebCite is significantly influenced by the source of publication. We also created a prototype for a process to submit web pages to the archives and increased coverage of our list of scientific webpages in the Internet Archive and WebCite by 22% and 255%, respectively. CONCLUSION: Our results show that link decay continues to be a problem across different disciplines and that current solutions for static web pages are helping and can be improved.

UNLABELLED: Studying plants using high-throughput genomics technologies is becoming routine, but interpretation of genome-wide expression data in terms of biological pathways remains a challenge, partly due to the lack of pathway databases. To create a knowledgebase for plant pathway analysis, we collected 1683 lists of differentially expressed genes from 397 gene-expression studies, which constitute a molecular signature database of various genetic and environmental perturbations of Arabidopsis. In addition, we extracted 1909 gene sets from various sources such as Gene Ontology, KEGG, AraCyc, Plant Ontology, predicted target genes of microRNAs and transcription factors, and computational gene clusters defined by meta-analysis. With this knowledgebase, we applied Gene Set Enrichment Analysis to an expression profile of cold acclimation and identified expected functional categories and pathways. Our results suggest that the AraPath database can be used to generate specific, testable hypotheses regarding plant molecular pathways from gene expression data. AVAILABILITY: http://bioinformatics.sdstate.edu/arapath/.