A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem

A quantum system will stay near its instantaneous ground state if the Hamiltonian that governs its evolution varies slowly enough. This quantum adiabatic behavior is the basis of a new class of algorithms for quantum computing. We test one such algorithm by applying it to randomly generated, hard, instances of an NP-complete problem. For the small examples that we can simulate, the quantum adiabatic algorithm works well, and provides evidence that quantum computers (if large ones can be built) may be able to outperform ordinary computers on hard sets of instances of NP-complete problems.Comment: 15 pages, 6 figures, email correspondence to [email protected] ; a shorter version of this article appeared in the April 20, 2001 issue of Science; see http://www.sciencemag.org/cgi/content/full/292/5516/47

A Semantics-Based Approach to Malware Detection

Malware detection is a crucial aspect of software security. Current malware detectors work by checking for signatures, which attempt to capture the syntactic characteristics of the machine-level byte sequence of the malware. This reliance on a syntactic approach makes current detectors vulnerable to code obfuscations, increasingly used by malware writers, that alter the syntactic properties of the malware byte sequence without significantly affecting their execution behavior. This paper takes the position that the key to malware identification lies in their semantics. It proposes a semantics-based framework for reasoning about malware detectors and proving properties such as soundness and completeness of these detectors. Our approach uses a trace semantics to characterize the behavior of malware as well as that of the program being checked for infection, and uses abstract interpretation to ``hide'' irrelevant aspects of these behaviors. As a concrete application of our approach, we show that (1) standard signature matching detection schemes are generally sound but not complete, (2) the semantics-aware malware detector proposed byChristodorescu et al. is complete with respect to a number of common obfuscations used by malware writers and (3) the malware detection scheme proposed by Kinder et al. and based on standard model-checking techniques is sound in general and complete on some, but not all, obfuscations handled by the semantics-aware malware detector

Distributed information consensus filters for simultaneous input and state estimation

This paper describes the distributed information filtering where a set of sensor networks are required to simultaneously estimate input and state of a linear discrete-time system from collaborative manner. Our research purpose is to develop a consensus strategy in which sensor nodes communicate within the network through a sequence of Kalman iterations and data diffusion. A novel recursive information filtering is proposed by integrating input estimation error into measurement data and weighted information matrices. On the fusing process, local system state filtering transmits estimation information using the consensus averaging algorithm, which penalizes the disagreement in a dynamic manner. A simulation example is provided to compare the performance of the distributed information filtering with optimal Gillijins–De Moor’s algorithm

The Paths to Choreography Extraction

Choreographies are global descriptions of interactions among concurrent components, most notably used in the settings of verification (e.g., Multiparty Session Types) and synthesis of correct-by-construction software (Choreographic Programming). They require a top-down approach: programmers first write choreographies, and then use them to verify or synthesize their programs. However, most existing software does not come with choreographies yet, which prevents their application. To attack this problem, we propose a novel methodology (called choreography extraction) that, given a set of programs or protocol specifications, automatically constructs a choreography that describes their behavior. The key to our extraction is identifying a set of paths in a graph that represents the symbolic execution of the programs of interest. Our method improves on previous work in several directions: we can now deal with programs that are equipped with a state and internal computation capabilities; time complexity is dramatically better; we capture programs that are correct but not necessarily synchronizable, i.e., they work because they exploit asynchronous communication

Formal framework for reasoning about the precision of dynamic analysis

Dynamic program analysis is extremely successful both in code debugging and in malicious code attacks. Fuzzing, concolic, and monkey testing are instances of the more general problem of analysing programs by dynamically executing their code with selected inputs. While static program analysis has a beautiful and well established theoretical foundation in abstract interpretation, dynamic analysis still lacks such a foundation. In this paper, we introduce a formal model for understanding the notion of precision in dynamic program analysis. It is known that in sound-by-construction static program analysis the precision amounts to completeness. In dynamic analysis, which is inherently unsound, precision boils down to a notion of coverage of execution traces with respect to what the observer (attacker or debugger) can effectively observe about the computation. We introduce a topological characterisation of the notion of coverage relatively to a given (fixed) observation for dynamic program analysis and we show how this coverage can be changed by semantic preserving code transformations. Once again, as well as in the case of static program analysis and abstract interpretation, also for dynamic analysis we can morph the precision of the analysis by transforming the code. In this context, we validate our model on well established code obfuscation and watermarking techniques. We confirm the efficiency of existing methods for preventing control-flow-graph extraction and data exploit by dynamic analysis, including a validation of the potency of fully homomorphic data encodings in code obfuscation

Recent environmental changes in the area of La Maddalena Harbour (Sardinia, Italy): data from mollusks and benthic foraminifera

Mollusks and benthic foraminifera are reliable tools to paleo-environmental reconstructions because they commonly occur in most marine habitats and are sensitive to major and short-lived changes of environmental drivers, induced by both natural and anthropogenic events. Their community structure provides useful information about the characteristics of their habitat and some species are sensitive to specific environmental controls. Features such as changes in species composition and community, or variation in test morphology provide evidence of fluctuation of several environmental factors. Therefore, both mollusks and benthic foraminifera can be used as an efficient method for identifying the history and ecological trajectory of marine ecosystems. This study focuses on the macro- (mollusks) and micropaleontological (benthic foraminifera) study of a 3 m long sediment core collected in the former military arsenal of the La Maddalena harbor (N Sardinia, Italy), at a depth of 15 m. The core site is located on the S-E coast of La Maddalena island, that underwent a complex history of human occupation along with natural environmental evolution and human-derived pressures. We aimed to reconstruct the main environmental changes recorded in the fossil benthic communities along the core, and to propose the most likely factors that caused these changes. Both mollusks and benthic foraminifera have been picked from the core, identified at genus/species level and counted. Ecological indications for each species have been extracted from literature. Univariate and multivariate statistics have been applied to highlight the community dynamics. More than 90 species of benthic foraminifera have been identified, and 101 mollusk species (846 specimens). The foraminifera diversity indices show a general reduction from the first 50 cm downcore. This slight decline is accompanied by changes in foraminiferal assemblages. The results concerning changes in foraminiferal species composition, their abundance and biodiversity, supported by statistical analyses (cluster analysis), allowed identification of three major foraminiferal associations corresponding to different marine coastal settings. The same results have been obtained by using mollusks and their ecological significance in the framework of benthic marine bionomics. Species are related to infralittoral vegetated bottom such as Posidonia meadows (HP) or photophilous algae through the core, but with variation in percentage of abundance, and HP species decreases from the bottom to the top, whereas species related to muddy bottom follow the opposite trend (coastal detritic mud, deep mud). This testifies that the area underwent a progressive reduction of Posidonia meadows and light-loving algae with a shift toward muddy bottoms, possibly related to the effect of the intensive renovation works of the harbor area. Moreover, radiocarbon dating obtained from Cerithium specimens indicated that the sedimentation rate increases in the upper portion of the core, according to the ecological signal reconstructed by the analysis of the mollusk assemblage

Typing and distribution of Plum pox virus isolates in Romania

Plum pox or Sharka, caused by Plum pox virus (PPV) is considered the most destructive disease of plum. Although PPV is widespread in all plum growing areas of Romania and causes serious yield losses, little is known about the variability of its isolates at a country level. For this reason, a large-scale study was performed with the aim of obtaining a picture of the prevalence and distribution of PPV strains in plum. During a three year survey, 200 PPV isolates collected from 23 different plum orchards from Transylvania, Moldavia and Muntenia areas were investigated. DASELISA and IC-RT-PCR were used for PPV detection. PPV strains were serologically determined by TAS-ELISA using PPV-D and PPV-M specific monoclonal antibodies. Molecular strain typing was done by IC/RT-PCR targeting three genomic regions corresponding to (Cter)CP, (Cter)NIb/(Nter)CP and CI. RFLP analysis was used to distinguish D and M strains, based on the RsaI polymorphism located in (Cter)CP. To confirm the presence of PPV-Rec strain, 13 PCR products spanning the (Cter)NIb/(Nter)CP were sequenced. Overall results showed that in Romania the predominant strain is PPV-D (73%), followed, with a much lower frequency, by PPV-Rec (14%). Mixed infections (PPV-D+PPVRec), which might generate additional variation by recombination, are also frequent (13%).Keywords: Romania, PPV strains, DAS/TAS-ELISA, IC/RT-PCR, RFLP, sequencin

Imaging of mandibular fractures: a pictorial review

Mandibular fractures are among the most common maxillofacial fractures observed in emergency rooms and are mainly caused by road accidents. The clinical features of mandibular fractures include malocclusion and loss of mandibular function. Panoramic radiography is usually limited to isolated lesions, whereas computed tomography is the tool of choice for all other facial traumatic events. No reference standard classification system for the different types of mandibular fractures is defined. Therapeutic options include a conservative approach or surgical treatment based on the anatomic area and the severity of fracture. The main purpose of this pictorial review is to illustrate a practical description of the pathophysiology of mandibular fractures and describe both the imaging techniques to recognise them and the therapeutic indications