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

Impact Compression Test on Concrete after High-Temperature Treatment and Numerical Simulation of All Feasible Loading Rates

Concrete materials are important in infrastructure and national defence construction. These materials inevitably bear complicated loads, which include static load, high temperature, and high strain rate. Therefore, the dynamic responses and fragmentation of concrete under high temperatures and loading rates should be investigated. However, the compressive properties of rock materials under ultrahigh loading rates (>20 m/s) are difficult to investigate using the split Hopkinson pressure bar. Impact compression tests were conducted on concrete specimens processed at different temperatures (20-800 °C) under three loading rates in this study to discuss the variation law of the impact compression strength of concrete materials after high-temperature treatment. On this basis, numerical simulation was conducted on impact compression test under all feasible loading rates (10-110 m/s). The results demonstrate that the peak stress of all concrete specimens increases linearly with loading rate before 21 m/s and gradually decreases after 21 m/s. Peak stress shows an inverted V-shaped variation law. Moreover, the temperature-induced weakening effect exceeds the strengthening effect caused by loading rate with the increase in temperature. The growth of peak stress decreases considerably, especially under an ultrahigh loading rate (>50 m/s). These conclusions can provide theoretical references for the design of the ultimate strength of concrete materials for practical applications, such as fire and explosion prevention

Intelligent prediction model based on genetic algorithm and support vector machine for evaluation of mining-induced building damage

Značajke čimbenika koji utječu na štetu nastalu na zgradama zbog iskapanja zemlje su različite, nelinearne i multi linearne. Za bolji opis tih čimbenika razvijen je inteligentni model zasnovan na potpornom vektorskom stroju (SVM) kojim se može predvidjeti šteta na zgradama nastala podzemnim iskapanjem. Na temelju opsežnog razmatranja geoloških, rudarskih i građevnih faktora, 10 ih je pažljivo odabrano. Posebice je, kao glavna ulazna varijabla u predloženom modelu, upotrebljen stupanj oštećenja građevine od opeke i betona, nastao podzemnim iskapanjem. Stupanj oštećenja i najšira pukotina građevinske konstrukcije od opeke i betona izabrani su kao izlazne varijable u predloženom modelu. Ukupno su odabrana 32 tipična slučaja oštećenja zgrada u Kini zbog iskapanja zemlje te upotrebljena kao podaci za uvježbavanje (training data). Funkcija radijalne baze (radial basis function – RBF) upotrebljena je za SVM klasifikaciju i primjenu modela regresije s najvećom širinom pukotine. Kako bi primjena modela bila što šira i njegova sposobnost predviđanja što veća, za izbor učinkovitih parametara za SVM model upotrebljen je genetski algoritam (GA), i tada je izvršena odgovarajuća identifikacija šest grupa uzoraka. Rezultati klasifikacije i regresije pokazuju da se predloženim modelom, koji koristi GA-SVM, može predvidjeti šteta na konstrukciji od opeke i betona, nastala iskapanjem zemlje, a rezultati procjene u skladu su s praćenim podacima. To navodi na praktičnost primjene predloženog modela u rješavanju različitih inženjerskih problema.Characteristics of factors influencing mining-induced building damage are diverse, nonlinear, and multi-linear. For a better description of these factors, an intelligent prediction model for building damage induced by underground mining is developed based on the support vector machine (SVM). Based on a comprehensive consideration of geological, mining, and building factors, 10 factors are carefully selected. In particular, the mining-induced damage grade of the brick-concrete building structure is used as the main input variable in the proposed model. The damage grade and largest crack width of the brick-concrete building structure are selected as output variables in the proposed model. A total of 32 typical cases of mining-induced building damage in China are collected and used as training data. The radial basis function (RBF) is used for SVM classification and the application of the largest-crack-width regression model. To improve the model’s generalizability and predictive capacity, the genetic algorithm (GA) is adopted to select effective parameters for the SVM model, and then the corresponding identification of six group samples is performed. The classification and regression results show that the proposed prediction model using GA-SVM can predict the mining-induced damage of a brick-concrete building structure, and the evaluation results show good agreement with monitored data. This suggests the practicality of the proposed model in a wide range of engineering problems

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

EVALUATION OF ELDERLY MOBILITY BASED ON TRANSIT CARD DATA IN SEOUL

We analyzed the travel patterns of senior citizens in Seoul using Automatic Fare Collection (AFC) data. We focused specifically on mode choices and transfer patterns. Results showed that 99% of trips made by senior citizens (individuals over 65 years old), who were given free subway transit passes, consisted of single-mode trips. Average travel time was 31 minutes, and subway travel times were longer than bus travel times. Individuals made fewer transfers, took longer metro trips, and paid smaller fares when using their free subway transit cards. They were more negatively sensitive to bus travel time than metro travel time. Encouraging older adult travelers to use transfers that increase costs to a modest extent might help improve travel quality among a group of individuals who find it difficult to enter the metro system or who are uncomfortable making inter-metro transfers. Additionally, as older adults have more time, yet are economically disadvantaged and take more leisure trips, travel improvements could include adopting a time-flexible fare discount. We discuss these improvements in terms of the individual and social benefits afforded to transit passengers in South Korea.</p

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

Design, Analysis and Empirical Researches for Solar Heat Collecting System based on Flat Mirrors Combination

There has been a dramatic increase of research on energy production using solar energy. This research aims to examine development of concentrating solar collector that is related to mid-high solar energy field. Although the use of dish type solar thermal system has been common in the existing high-efficiency collector technology, several problems have been raised. In order to solve these issues, the frame has been designed as flat plate type with Fresnel lens and the structural stability has been proved by analysis. Furthermore, the experiment that checks collectorrsquos temperature has been performed for the correct works of the stirling engine

Utilization of Geotextile Tube for Sandy and Muddy Coastal Management: A Review

Threats to beaches have accelerated the coastal destruction. In recent decades, geotextile tubes were used around the world to prevent coastal erosion, to encourage beach nourishment, and to assist mangrove rehabilitation. However, the applications of geotextile tube in sandy and muddy coasts have different concerns as the geological settings are different. Applications of geotextile tubes in sandy beaches were mainly to prevent coastline from further erosion and to nourish the beach. However, for the muddy coasts, mangrove rehabilitation and conservation were additional concerns in coastal management schemes. The mangrove forests are natural barriers which can be found on the muddy coasts of many tropical countries. In this paper, the viability of geotextile tubes in sandy and muddy beaches was analysed. The advantages and disadvantages of the utilization of geotextile tubes in coastal management were discussed based on the experiences from the tropical countries such as Mexico, Malaysia, and Thailand. From the case studies, impressive improvements in coastal restoration after installation of geotextile tubes were shown. Based on the discussion, several recommendations to improve the application of geotextile tubes were suggested in this paper