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

Implicit Kernel Attention

\textit{Attention} computes the dependency between representations, and it encourages the model to focus on the important selective features. Attention-based models, such as Transformers and graph attention networks (GAT) are widely utilized for sequential data and graph-structured data. This paper suggests a new interpretation and generalized structure of the attention in Transformer and GAT. For the attention in Transformer and GAT, we derive that the attention is a product of two parts: 1) the RBF kernel to measure the similarity of two instances and 2) the exponential of $L^{2}$ norm to compute the importance of individual instances. From this decomposition, we generalize the attention in three ways. First, we propose implicit kernel attention with an implicit kernel function, instead of manual kernel selection. Second, we generalize $L^{2}$ norm as the $L^{p}$ norm. Third, we extend our attention to structured multi-head attention. Our generalized attention shows better performance on classification, translation, and regression tasks

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

Fabrication and Evaluation of Mechanical Properties of CF/GNP Composites

AbstractCNT/CFRP (Carbon Nanotube/ Carbon Fiber Reinforced Plastic) composites and GNP/CFRP (Graphene Nano platelet/ Carbon Fiber Reinforced Plastic) have several excellent mechanical properties including, high strength, young's modulus, thermal conductivity, corrosion resistance, electronic shielding and so on. In this study, CNT/CFRP composites were manufactured by varying the CNT weight ratio as 2wt% and 3wt%, While GNP/CFRP composites were manufactured by varying the GNP weight ratio as 0.5wt% and 1wt%. The composites ware manufactured by mechanical method (3-roll-mill). Tensile, impact and wear tests were performed according to ASTM standards D638, D256 and D3181 respectively. It was observed that, increasing the CNT weight ratio improves the mechanical properties, e.g., tensile strength, impact and wear resistance

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

Research on a Denial of Service (DoS) Detection System Based on Global Interdependent Behaviors in a Sensor Network Environment

This research suggests a Denial of Service (DoS) detection method based on the collection of interdependent behavior data in a sensor network environment. In order to collect the interdependent behavior data, we use a base station to analyze traffic and behaviors among nodes and introduce methods of detecting changes in the environment with precursor symptoms. The study presents a DoS Detection System based on Global Interdependent Behaviors and shows the result of detecting a sensor carrying out DoS attacks through the test-bed

Gypsum-Dependent Effect of NaCl on Strength Enhancement of CaO-Activated Slag Binders

This study explores the combined effect of NaCl and gypsum on the strength of the CaO-activated ground-granulated blast furnace slag (GGBFS) binder system. In the CaO-activated GGBFS system, the incorporation of NaCl without gypsum did not improve the strength of the system. However, with the presence of gypsum, the use of NaCl yielded significantly greater strength than the use of either gypsum or NaCl alone. The presence of NaCl largely increases the solubility of gypsum in a solution, leading to a higher concentration of sulfate ions, which is essential for generating more and faster formations of ettringite in a fresh mixture of paste. The significant strength enhancement of gypsum was likely due to the accelerated and increased formation of ettringite, accompanied by more efficient filling of pores in the system