Investigating Information Structure of Phishing Emails Based on Persuasive Communication Perspective

Current approaches of phishing filters depend on classifying messages based on textually discernable features such as IP-based URLs or domain names as those features that can be easily extracted from a given phishing message. However, in the same sense, those easily perceptible features can be easily manipulated by sophisticated phishers. Therefore, it is important that universal patterns of phishing messages should be identified for feature extraction to serve as a basis for text classification. In this paper, we demonstrate that user perception regarding phishing message can be identified in central and peripheral routes of information processing. We also present a method of formulating quantitative model that can represent persuasive information structure in phishing messages. This paper makes contribution to phishing classification research by presenting the idea of universal information structure in terms of persuasive communication theories

Exploring a method of extracting universal features of phishing emails

Current approaches of phishing filters depend on classifying emails based on obviously discernable features such as IP-based URLs or domain names. However, as those features can be easily extracted from a given phishing email, in the same sense, they can be easily manipulated by sophisticated phishers. Therefore, it is important that universal patterns of phishing messages should be identified to serve as a basis for novel phishing classification algorithm. In this paper, we argue that phishing is a kind of persuasion and explore feature extraction method based on persuasive communication perspective. Phishing message components, including message factors, source factors, and computer related factors, are investigated as message sender’s strategic message manipulation. On the other hand, message receiver’s cognitive components for information processing are discussed in terms of dual process of cognition. Our method consists of four major procedural steps. First, persuasive message components are identified through extensive literature review. Second, based on the identified persuasive message components, we conduct content analysis of email messages. Third, using factor analysis, persuasive components in phishing messages are classified for the validation of a dual process of cognition. From the pool of persuasive communication variables, we identify underlying dimensions to see whether central route information processing and peripheral route information processing are distinctly identified. Fourth, instances are classified by conducting logistic regression analysis based on the identified variables as a result of factor analysis in addition to known phishing factors identified by other studies. We, then, present a quantitative model that can represent persuasive information structure in phishing messages. This paper makes contribution to phishing classification research by presenting the idea of universal information structure in terms of persuasive communication theories

Efficient Conversion of Acetate to 3-Hydroxypropionic Acid by Engineered Escherichia coli

Acetate, which is an abundant carbon source, is a potential feedstock for microbial processes that produce diverse value-added chemicals. In this study, we produced 3-hydroxypropionic acid (3-HP) from acetate with engineered Escherichia coli. For the efficient conversion of acetate to 3-HP, we initially introduced heterologous mcr (encoding malonyl-CoA reductase) from Chloroflexus aurantiacus. Then, the acetate assimilating pathway and glyoxylate shunt pathway were activated by overexpressing acs (encoding acetyl-CoA synthetase) and deleting iclR (encoding the glyoxylate shunt pathway repressor). Because a key precursor malonyl-CoA is also consumed for fatty acid synthesis, we decreased carbon flux to fatty acid synthesis by adding cerulenin. Subsequently, we found that inhibiting fatty acid synthesis dramatically improved 3-HP production (3.00 g/L of 3-HP from 8.98 g/L of acetate). The results indicated that acetate can be used as a promising carbon source for microbial processes and that 3-HP can be produced from acetate with a high yield (44.6% of the theoretical maximum yield).11Ysciescopu

3D-Printed Microfluidic Device for the Detection of Pathogenic Bacteria Using Size-based Separation in Helical Channel with Trapezoid Cross-Section

A facile method has been developed to detect pathogenic bacteria using magnetic nanoparticle clusters (MNCs) and a 3D-printed helical microchannel. Antibody-functionalized MNCs were used to capture E. coli (EC) bacteria in milk, and the free MNCs and MNC-EC complexes were separated from the milk using a permanent magnet. The free MNCs and MNC-EC complexes were dispersed in a buffer solution, then the solution was injected into a helical microchannel device with or without a sheath flow. The MNC-EC complexes were separated from the free MNCs via the Dean drag force and lift force, and the separation was facilitated in the presence of a sheath flow. The concentration of the E. coli bacteria was determined using a light absorption spectrometer, and the limit of detection was found to be 10 cfu/mL in buffer solution and 100 cfu/mL in milk.open119188sciescopu

Novel Diagnostic Model for the Deficient and Excess Pulse Qualities

The deficient and excess pulse qualities (DEPs) are the two representatives of the deficiency and excess syndromes, respectively. Despite its importance in the objectification of pulse diagnosis, a reliable classification model for the DEPs has not been reported to date. In this work, we propose a classification method for the DEPs based on a clinical study. First, through factor analysis and Fisher's discriminant analysis, we show that all the pulse amplitudes obtained at various applied pressures at Chon, Gwan, and Cheok contribute on equal orders of magnitude in the determination of the DEPs. Then, we discuss that the pulse pressure or the average pulse amplitude is appropriate for describing the collective behaviors of the pulse amplitudes and a simple and reliable classification can be constructed from either quantity. Finally, we propose an enhanced classification model that combines the two complementary variables sequentially

Multiplex quantitative analysis of microRNA expression via exponential isothermal amplification and conformation-sensitive DNA separation

Expression profiling of multiple microRNAs (miRNAs) generally provides valuable information for understanding various biological processes. Thus, it is necessary to develop a sensitive and accurate miRNA assay suitable for multiplexing. Isothermal exponential amplification reaction (EXPAR) has received significant interest as an miRNA analysis method because of high amplification efficiency. However, EXPAR cannot be used for a broader range of applications owing to limitations such as complexity of probe design and lack of proper detection method for multiplex analysis. Here, we developed a sensitive and accurate multiplex miRNA profiling method using modified isothermal EXPAR combined with high-resolution capillary electrophoresis-based single-strand conformation polymorphism (CE-SSCP). To increase target miRNA specificity, a stem-loop probe was introduced instead of a linear probe in isothermal EXPAR to allow specific amplification of multiple miRNAs with minimal background signals. CE-SSCP, a conformation-dependent separation method, was used for detection. Since CE-SSCP eliminates the need for probes to have different lengths, easier designing of probes with uniform amplification efficiency was possible. Eight small RNAs comprising six miRNAs involved in Caenorhabditis elegans development and two controls were analyzed. The expression patterns obtained using our method were concordant with those reported in previous studies, thereby supporting the proposed method's robustness and utility.113sciescopu

Designing a Data Warehouse for Cyber Crimes

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on the data warehouse. We discuss several ways of utilizing the data warehouse using OLAP and data mining technologies. We finally discuss legal issues and data population issues for the data warehouse

Designing a Data Warehouse for Cyber Crimes

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on the data warehouse. We discuss several ways of utilizing the data warehouse using OLAP and data mining technologies. We finally discuss legal issues and data population issues for the data warehouse