Thwarting Attacks in Malcode-Bearing Documents by Altering Data Sector Values

Embedding malcode within documents provides a convenient means of attacking systems. Such attacks can be very targeted and difficult to detect to stop due to the multitude of document-exchange vectors and the vulnerabilities in modern document processing applications. Detecting malcode embedded in a document is difficult owing to the complexity of modern document formats that provide ample opportunity to embed code in a myriad of ways. We focus on Microsoft Word documents as malcode carriers as a case study in this paper. To detect stealthy embedded malcode in documents, we develop an arbitrary data transformation technique that changes the value of data segments in documents in such a way as to purposely damage any hidden malcode that may be embedded in those sections. Consequently, the embedded malcode will not only fail but also introduce a system exception that would be easily detected. The method is intended to be applied in a safe sandbox, the transformation is reversible after testing a document, and does not require any learning phase. The method depends upon knowledge of the structure of the document binary format to parse a document and identify the specific sectors to which the method can be safely applied for malcode detection. The method can be implemented in MS Word as a security feature to enhance the safety of Word documents

Email Archive Analysis Through Graphical Visualization

The analysis of the vast storehouse of email content accumulated or produced by individual users has received relatively little attention other than for specific tasks such as spam and virus filtering. Current email analysis in standard client applications consists of keyword based matching techniques for filtering and expert driven manual exploration of email files. We have implemented a tool, called the Email Mining Toolkit (EMT) for analyzing email archives which includes a graphical display to explore relationships between users and groups of email users. The chronological flow of an email message can be analyzed by EMT. Our design goal is to embed the technology into standard email clients, such as Outlook, revealing far more information about a user's own email history than is otherwise now possible. In this paper we detail the visualization techniques implemented in EMT. We show the utility of these tools and underlying models for detecting email misuse such as viral propagation, and spam spread as examples

Catalytic Mechanism of Amyloid-β Peptide Degradation by Insulin Degrading Enzyme: Insights from QM/MM MP2 Calculation

Insulin degrading enzyme (IDE), a metalloprotease that degrades amyloid-β (Aβ) peptides and insulin, is associated with Alzheimer’s disease and diabetes. The mechanism of IDE catalyzed degrading of Aβ peptides, which is of fundamental importance in the design of therapeutic methods for Alzheimer’s disease, has not been fully understood. In this work, combined quantum mechanics and molecular mechanics (QM/MM) style Møller-Plesset second order perturbation theory (MP2) geometry optimization calculations are performed to investigate the catalytic mechanism of the Aβ40 Phe19-Phe20 peptide bond cleavage by human IDE. The analyses using QM/MM MP2 optimization suggest that a neutral water molecule is at the active site of the enzyme-substrate (ES) complex. The water molecule is in hydrogen bonding with the nearby anionic Glu111 of IDE, but not directly bound to the catalytic Zn ion. This is confirmed by QM/MM DFTB3 molecular dynamics simulation. Our studies also reveal that the hydrolysis of the Aβ40 Phe19-Phe20 peptide bond by IDE consists of four key steps. The neutral water is first activated by moving toward and binding to the Zn ion. A gem-diol intermediate is then formed by the activated neutral water molecule attacking the C atom of the Phe19-Phe20 peptide bond. The next is the protonation of the N atom of Phe19-Phe20 peptide bond to form an intermediate with an elongated C-N bond. The final step is the breaking of the Phe19-Phe20 C-N bond. The final step is the rate-determining step with a calculated Gibbs free energy of activation of 17.34 kcal/mol, in good agreement with the experimental value 16.7 kcal/mol. This mechanism provides the basis for the design of biochemical methods to modulate the activity of IDE in humans

Non-uniform face mesh for 3D face recognition

Uniform face meshes are able to represent the face in 3D format and can also be used to perform 3D face recognition.However, to obtain a good recognition rate, a fine mesh which consists of many points would be needed to accurately represent the many contours of the face.Therefore, in this paper, it is proposed that a non-uniform face mesh is constructed for 3D face recognition. A non-uniform mesh consisting of fine meshes for the middle of the face and coarse meshes for the rest of the face was created. In comparison with a uniform mesh, the proposed non-uniform face mesh consists of much fewer points and therefore saves storage space and transmission time due to a smaller file size.Besides that, the proposed mesh was able to produce recognition rates that were only slightly lower than the uniform mesh, hence proving that important face features for recognition were retained

Behavior-Based Modeling and Its Application to Email Analysis

The Email Mining Toolkit (EMT) is a data mining system that computes behavior profiles or models of user email accounts. These models may be used for a multitude of tasks including forensic analyses and detection tasks of value to law enforcement and intelligence agencies, as well for as other typical tasks such as virus and spam detection. To demonstrate the power of the methods, we focus on the application of these models to detect the early onset of a viral propagation without "content-base" (or signature-based) analysis in common use in virus scanners. We present several experiments using real email from 15 users with injected simulated viral emails and describe how the combination of different behavior models improves overall detection rates. The performance results vary depending upon parameter settings, approaching 99% true positive (TP) (percentage of viral emails caught) in general cases and with 0.38% false positive (FP) (percentage of emails with attachments that are mislabeled as viral). The models used for this study are based upon volume and velocity statistics of a user's email rate and an analysis of the user's (social) cliques revealed in the person's email behavior. We show by way of simulation that virus propagations are detectable since viruses may emit emails at rates different than human behavior suggests is normal, and email is directed to groups of recipients in ways that violate the users' typical communications with their social groups

Control of the nanoscale crystallinity and phase separation in polymer solar cells

Grazing-incidence x-ray diffraction and atomic force microscopy were performed on bulk heterojunction regioregular poly(3-hexylthiophene) (RR-P3HT) [6,6]-phenyl-C71-butyric acid methyl esters spin-cast films with different film processing conditions to correlate the crystalline nanostructure of P3HT with the corresponding solar cell performance. The increase in long wavelength absorption for solvent annealed films is related to highly conjugated crystal structure of RR-P3HT phase-separated in the active layer. Upon thermal annealing, the solvent annealed 50-nm-thick device shows high solar cell performance with fill factor up to 73% and power conversion efficiency of 3.80%

Control of the nanoscale crystallinity and phase separation in polymer solar cells

Grazing-incidence x-ray diffraction and atomic force microscopy were performed on bulk heterojunction regioregular poly(3-hexylthiophene) (RR-P3HT) [6,6]-phenyl-C71-butyric acid methyl esters spin-cast films with different film processing conditions to correlate the crystalline nanostructure of P3HT with the corresponding solar cell performance. The increase in long wavelength absorption for solvent annealed films is related to highly conjugated crystal structure of RR-P3HT phase-separated in the active layer. Upon thermal annealing, the solvent annealed 50-nm-thick device shows high solar cell performance with fill factor up to 73% and power conversion efficiency of 3.80%

Impact of Aerosols on Convective Clouds and Precipitation

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested