Algorithm Diversity for Resilient Systems

Diversity can significantly increase the resilience of systems, by reducing the prevalence of shared vulnerabilities and making vulnerabilities harder to exploit. Work on software diversity for security typically creates variants of a program using low-level code transformations. This paper is the first to study algorithm diversity for resilience. We first describe how a method based on high-level invariants and systematic incrementalization can be used to create algorithm variants. Executing multiple variants in parallel and comparing their outputs provides greater resilience than executing one variant. To prevent different parallel schedules from causing variants' behaviors to diverge, we present a synchronized execution algorithm for DistAlgo, an extension of Python for high-level, precise, executable specifications of distributed algorithms. We propose static and dynamic metrics for measuring diversity. An experimental evaluation of algorithm diversity combined with implementation-level diversity for several sequential algorithms and distributed algorithms shows the benefits of algorithm diversity

Climatic cyclicity at Site 806; the GRAPE record

We used the continuous saturated bulk density records collected by the gamma-ray attenuation porosity evaluator (GRAPE) at Ocean Drilling Program Site 806 on the top of the Ontong Java Plateau to evaluate the continuity of the recovered cores and to splice together a complete section from the multiple holes drilled at the site (for the upper 165 m, this is equivalent to approximately 0-5 Ma). The lack of offset in core breaks (between the 9.5-m-long, successive cores) from hole to hole made splicing difficult, and the results are not unambiguous. The composite section was converted to a time series by using biostratigraphy and supplementing this with oxygen-isotope datums for the interval between 2 and 5 Ma. Evolutionary spectra generated from the composite section clearly indicate the presence of Milankovitch frequencies throughout the record. We chose a final age model that was most consistent with a Milankovitch model but have not, as yet, spectrally tuned the data. The GRAPE (saturated bulk density) changes at Site 806 are the result of changes in grain size, with density decreasing as grain size increases. We attribute this to the removal of fine particles by winnowing, leaving a greater percentage of large hollow foraminifers behind— the winnowing effect. This is in contrast to the dissolution effect, which breaks up large hollow foraminifers into fragments but merely transfers intraparticle porosity to interparticle porosity and thus shows significant changes in grain size without significant changes in density. A 300-k.y. piston core record reveals that during this time interval increased winnowing has been associated with glacials and 100-k.y. cyclicity. For the time interval from 5 to 2 Ma, enhanced winnowing continues to be associated with isotopically heavy intervals dominated by 41-k.y. (obliquity) variance. In this band, the winnowing record is highly correlated with the ice-volume record, particularly since the onset of Northern Hemisphere glaciations. Before that time, the grain-size record continues to show variance in the obliquity band whereas the oxygen isotope record shows a shift to the dominance of precessional frequencies. We suggest that the winnowing signal is a response to increased thermohaline circulation and benthic storm activity associated with enhanced north-south thermal gradients during times of climatic degradation

Automated Crowdturfing Attacks and Defenses in Online Review Systems

Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers. In this paper, we identify a new class of attacks that leverage deep learning language models (Recurrent Neural Networks or RNNs) to automate the generation of fake online reviews for products and services. Not only are these attacks cheap and therefore more scalable, but they can control rate of content output to eliminate the signature burstiness that makes crowdsourced campaigns easy to detect. Using Yelp reviews as an example platform, we show how a two phased review generation and customization attack can produce reviews that are indistinguishable by state-of-the-art statistical detectors. We conduct a survey-based user study to show these reviews not only evade human detection, but also score high on "usefulness" metrics by users. Finally, we develop novel automated defenses against these attacks, by leveraging the lossy transformation introduced by the RNN training and generation cycle. We consider countermeasures against our mechanisms, show that they produce unattractive cost-benefit tradeoffs for attackers, and that they can be further curtailed by simple constraints imposed by online service providers

An Extended Stable Marriage Problem Algorithm for Clone Detection

Code cloning negatively affects industrial software and threatens intellectual property. This paper presents a novel approach to detecting cloned software by using a bijective matching technique. The proposed approach focuses on increasing the range of similarity measures and thus enhancing the precision of the detection. This is achieved by extending a well-known stable-marriage problem (SMP) and demonstrating how matches between code fragments of different files can be expressed. A prototype of the proposed approach is provided using a proper scenario, which shows a noticeable improvement in several features of clone detection such as scalability and accuracy.Comment: 20 pages, 10 figures, 6 table

Astronomically paced changes in overturning circulation in the Western North Atlantic during the middle Eocene

North Atlantic Deep Water (NADW) currently redistributes heat and salt between Earth’s ocean basins, and plays a vital role in the ocean-atmosphere CO2 exchange. Despite its crucial role in today’s climate system, vigorous debate remains as to when deep-water formation in the North Atlantic started. Here, we present datasets from carbonate-rich middle Eocene sediments from the Newfoundland Ridge, revealing a unique archive of paleoceanographic change from the progressively cooling climate of the middle Eocene. Well-defined lithologic alternations between calcareous ooze and clay-rich intervals occur at the ∼41-kyr beat of axial obliquity. Hence, we identify obliquity as the driver of middle Eocene (43.5–46 Ma) Northern Component Water (NCW, the predecessor of modern NADW) variability. High-resolution benthic foraminiferal δ18O and δ13C suggest that obliquity minima correspond to cold, nutrient-depleted, western North Atlantic deep waters. We thus link stronger NCW formation with obliquity minima. In contrast, during obliquity maxima, Deep Western Boundary Currents were weaker and warmer, while abyssal nutrients were more abundant. These aspects reflect a more sluggish NCW formation. This obliquity-paced paleoceanographic regime is in excellent agreement with results from an Earth system model, in which obliquity minima configurations enhance NCW formation