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

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

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

Rapid and accurate clinical testing for COVID-19 by nicking and extension chain reaction system-based amplification (NESBA)

We herein describe rapid and accurate clinical testing for COVID-19 by nicking and extension chain reaction system-based amplification (NESBA), an ultrasensitive version of NASBA. The primers to identify SARS-CoV-2 viral RNA were designed to additionally contain the nicking recognition sequence at the 5'-end of conventional NASBA primers, which would enable nicking enzyme-aided exponential amplification of T7 RNA promoter-containing double-stranded DNA (T7DNA). As a consequence of this substantially enhanced amplification power, the NESBA technique was able to ultrasensitively detect SARS-CoV-2 genomic RNA (gRNA) down to 0.5 copies/μL (= 10 copies/reaction) for both envelope (E) and nucleocapsid (N) genes within 30 min under isothermal temperature (41 °C). When the NESBA was applied to test a large cohort of clinical samples (n = 98), the results fully agreed with those from qRT-PCR and showed the excellent accuracy by yielding 100% clinical sensitivity and specificity. By employing multiple molecular beacons with different fluorophore labels, the NESBA was further modulated to achieve multiplex molecular diagnostics, so that the E and N genes of SARS-CoV-2 gRNA were simultaneously assayed in one-pot. By offering the superior analytical performances over the current qRT-PCR, the isothermal NESBA technique could serve as very powerful platform technology to realize the point-of-care (POC) diagnosis for COVID-19

Characterization of germanium/silicon p-n junction fabricated by low temperature direct wafer bonding and layer exfoliation

The current transport across a p-Ge/n-Si diode structure obtained by direct wafer bonding and layer exfoliation is analysed. A low temperature anneal at 400 degrees C for 30 min was used to improve the forward characteristics of the diode with the on/off ratio at -1 V being > 8000. Post anneal, the transport mechanism has a strong tunnelling component. This fabrication technique using a low thermal budget (T <= 400 degrees C) is an attractive option for heterogeneous integration. (C) 2012 American Institute of Physics. (doi:10.1063/1.3688174