Relevant bibliographies by topics / Phishing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Phishing'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Phishing"

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Jansson, K., and R. von Solms. "Phishing for phishing awareness." Behaviour & Information Technology 32, no. 6 (June 2013): 584–93. http://dx.doi.org/10.1080/0144929x.2011.632650.

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Brenner, Philip S. "Can Phishing Tank Survey Response Rates? Evidence from a Natural Experiment." Field Methods 31, no. 4 (September 11, 2019): 295–308. http://dx.doi.org/10.1177/1525822x19872443.

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In today’s survey climate, many individuals doubt the legitimacy of survey invitations. Phishing, an Internet-based fraud that tricks users into disclosing private information, has the potential to further erode the perceived legitimacy of e-mailed survey invitations and harm cooperation. However, no study has tested the effect of phishing on response rates. This article reports on a natural experiment examining phishing’s effect on survey response. University faculty and staff received an invitation to participate in an annual web survey on satisfaction with information technology (IT) services followed by a request to participate in a second “survey” ostensibly sent by another university department. However, the second survey invitation was a simulated phishing attack sent by the IT department. Analysis of response rates and the timing of responses from each of the last five years of the legitimate survey suggests that the phishing simulation dramatically reduced response compared to predictions based on previous years.
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Idna Idris, Mohd Yamani, Madihah Mohd Saudi, Shaharudin Ismail, and Emran Mohd Tamil. "Phishing." International Journal of Learning: Annual Review 12, no. 8 (2007): 79–88. http://dx.doi.org/10.18848/1447-9494/cgp/v14i08/45418.

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Fox, Dirk. "Phishing." Datenschutz und Datensicherheit - DuD 45, no. 11 (November 2021): 717. http://dx.doi.org/10.1007/s11623-021-1521-3.

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Gandhi, V. Karamchand, and Prof R. Senthil Kumar. "A Study on Phishing: Preventions and Anti-Phishing Solutions." International Journal of Scientific Research 1, no. 2 (June 1, 2012): 68–69. http://dx.doi.org/10.15373/22778179/jul2012/21.

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Fatima, Rubia, Affan Yasin, Lin Liu, and Jianmin Wang. "How persuasive is a phishing email? A phishing game for phishing awareness." Journal of Computer Security 27, no. 6 (October 11, 2019): 581–612. http://dx.doi.org/10.3233/jcs-181253.

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Zieni, Rasha, Luisa Massari, and Maria Carla Calzarossa. "Phishing or Not Phishing? A Survey on the Detection of Phishing Websites." IEEE Access 11 (2023): 18499–519. http://dx.doi.org/10.1109/access.2023.3247135.

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Mohamed, Gori, J. Visumathi, Miroslav Mahdal, Jose Anand, and Muniyandy Elangovan. "An Effective and Secure Mechanism for Phishing Attacks Using a Machine Learning Approach." Processes 10, no. 7 (July 12, 2022): 1356. http://dx.doi.org/10.3390/pr10071356.

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Phishing is one of the biggest crimes in the world and involves the theft of the user’s sensitive data. Usually, phishing websites target individuals’ websites, organizations, sites for cloud storage, and government websites. Most users, while surfing the internet, are unaware of phishing attacks. Many existing phishing approaches have failed in providing a useful way to the issues facing e-mails attacks. Currently, hardware-based phishing approaches are used to face software attacks. Due to the rise in these kinds of problems, the proposed work focused on a three-stage phishing series attack for precisely detecting the problems in a content-based manner as a phishing attack mechanism. There were three input values—uniform resource locators and traffic and web content based on features of a phishing attack and non-attack of phishing website technique features. To implement the proposed phishing attack mechanism, a dataset is collected from recent phishing cases. It was found that real phishing cases give a higher accuracy on both zero-day phishing attacks and in phishing attack detection. Three different classifiers were used to determine classification accuracy in detecting phishing, resulting in a classification accuracy of 95.18%, 85.45%, and 78.89%, for NN, SVM, and RF, respectively. The results suggest that a machine learning approach is best for detecting phishing.
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Singh, Kuldeep, Palvi Aggarwal, Prashanth Rajivan, and Cleotilde Gonzalez. "Training to Detect Phishing Emails: Effects of the Frequency of Experienced Phishing Emails." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 453–57. http://dx.doi.org/10.1177/1071181319631355.

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We studied people’s success on the detection of phishing emails after they were trained under one of three phishing frequency conditions, where the proportion of the phishing emails during training varied as: low frequency (25% phishing emails), medium frequency (50% phishing emails) and high frequency (75% phishing emails). Individual base susceptibility to phishing emails was measured in a pre-training phase in which 20% of the emails were phishing; this performance was then compared to a post-training phase in which participants aimed at detecting new rare phishing emails (20% were phishing emails). The Hit rates, False Alarm rates, sensitivities and response criterion were analyzed. Results revealed that participants receiving higher frequency of phishing emails had a higher hit rate but also higher false alarm rate at detecting phishing emails at post-training compared to participants encountering lower frequency levels during training. These results have implications for designing new training protocols for improving detection of phishing emails.
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Kumari, Khushboo, and Feon Jaison. "Detection of URL Based Phishing Websites Using Machine Learning in Django Framework." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 1151–53. http://dx.doi.org/10.22214/ijraset.2022.40828.

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Abstract: In this modern world, Phishing website detection is one of the most critical tasks in the world. In the recent times, a lot of people have suffered phishing attack due to phishing website. Machine Learning plays an important role in prediction of phishing website in the network. The proposed method predicts the URL based phishing websites based on features and also gives maximum accuracy to predict the result. This method uses uniform resource locator (URL) features to detect. It identified features that phishing site URLs contain. The proposed method takes those features for phishing detection. Security of the phishing detection website is also a major concern which is solved by providing administration who can manage the phishing detection website. Keywords: Phishing site, Machine learning, Legitimate, Prediction
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Dissertations / Theses on the topic "Phishing"

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Mei, Yuanxun. "Anti-phishing system : Detecting phishing e-mail." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2089.

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Because of the development of the Internet and the rapid increase of the electronic commercial, the incidents on stealing the consumers' personal identify data and financial account credentials are becoming more and more common. This phenomenon is called phishing. Now phishing is so popular that web sites such as papal , eBay, MSN, Best Buy, and America Online are frequently spoofed by phishers. What’s more, the amount of the phishing sites is increasing at a high rate.

The aim of the report is to analyze different phishing phenomenon and help the readers to identify phishing attempts. Another goal is to design an anti-phishing system which can detect the phishing e-mails and then perform some operations to protect the users. Since this is a big project, I will focus on the mail detecting part that is to analyze the detected phishing emails and extract details from these mails.

A list of the most important information of this phishing mail is extracted, which contains “mail subject”, “ mail received date”, “targeted user”, “the links”, and “expiration and creation date of the domain”. The system can presently extract this information from 40% of analyzed e-mails.

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Ghani, Hajra. "Phishing : En innehållsanalys av phishing på webben." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-29012.

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The goal with this research has been to answer questions related to social engineeringbased phishing attacks: email phishing and website phishing. This study answers questions like why these attacks occur, which type of internet users easily get tricked by phishers, Moreover this study consist of different defense mechanisms that exist against the attacks, weaknesses in them, examples to improve them and other technical solutions against them. Often the attacks consist of a combination of both email phishing and website phishing. A link can be sent to a user via email that leads to a phishing site where the user get tricked into submitting personal information.These attacks aims to steal personal information and money from users. There are anti-phishing tools in web browsers and mailsystems to protect the user. There are special phishingfilters and features that can protect users from phishing mails and detect them. Users who get attacked by phishers are those who lack knowledge about them. But since high educated people and security experts also fall for phishing beacuse phishers develop new techniques and strategies to attack users, more advanced techniques in web browsers and mail systems are needed. This study was done through a systematic litterture review where 10 articles where chosen. These articles where studied and summarised through a content analysis.
Målet med denna undersökning har varit att besvara frågor relaterat till social engineeringbaserade phishngattacker: email phishing och website phishing. Den här studien tar upp varför dessa attacker utförs, vilka användare som mest blir drabbade av de. Vidare handlar studien om olika skyddsmekanismer som existerar mot attackerna, vilka bristerna det finns i de, eventuella förbättringsförslag och förslag på andra tekniska lösningar. Oftast sker attackerna genom en kombination av email phishing och website phishing. En skadlig länk kan skickas till en användare via mail som leder till en phishingsida där användaren blir lurad till att fylla i privata uppgifter om sig själv. Dessa attacker sker främst för att stjäla personuppgifter och leder oftast till att en användare blir drabbad finansiellt. Det finns olika anti-phishing verktyg i webbläsare och mailsystem för att skydda användare. Mot email phishing finns speciella phishingfilter och olika kännetecken som hjälper till att skydda mot skadliga mail och upptäcka de. De flesta som blir drabbade av phishing är just användare som ej är medvetna om vad phishing är. Men eftersom det visat sig att även högutbildade människor och säkerhetsexperter faller för phishing då phisher utvecklar nya tekniker och strategier att utföra attacker, krävs det mer avancerade tekniska lösningar i webbläsare och mailsystem. Studien har genomförts med hjälp av en systematisk litteraturstudie, där 10 artiklar valdes ut. Dessa artiklar bearbetades och sammanfattades genom en innehållsanalys.
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Alnajim, Abdullah M. "Fighting Internet fraud : anti-phishing effectiveness for phishing websites detection." Thesis, Durham University, 2009. http://etheses.dur.ac.uk/2149/.

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Recently, the Internet has become a very important medium of communication. Many people go online and conduct a wide range of business. They can sell and buy goods, perform different banking activities and even participate in political and social elections by casting a vote online. The parties involved in any transaction never need to meet and a buyer can sometimes be dealing with a fraudulent business that does not actually exist. So, security for conducting businesses online is vital and critical. All security-critical applications (e.g. online banking login pages) that are accessed using the Internet are at the risk of fraud. A common risk comes from so-called Phishing websites, which have become a problem for online banking and e-commerce users. Phishing websites attempt to trick people into revealing their sensitive personal and security information in order for the fraudster to access their accounts. They use websites that look similar to those of legitimate organizations and exploit the end-user's lack of knowledge of web browser clues and security indicators. This thesis addresses the effectiveness of Phishing website detection. It reviews existing anti-Phishing approaches and then makes the following contributions. First of all, the research in this thesis evaluates the effectiveness of the current most common users' tips for detecting Phishing websites. A novel effectiveness criteria is proposed and used to examine every tip and rank it based on its effectiveness score, thus revealing the most effective tips to enable users to detect Phishing attacks. The most effective tips can then be used by anti-Phishing training approaches. Secondly, this thesis proposes a novel Anti-Phishing Approach that uses Training Intervention for Phishing Websites' Detection (APTIPWD) and shows that it can be easily implemented. Thirdly, the effectiveness of the New Approach (APTIPWD) is evaluated using a set of user experiments showing that it is more effective in helping users distinguish between legitimate and Phishing websites than the Old Approach of sending anti-Phishing tips by email. The experiments also address the issues of the effects of technical ability and Phishing knowledge on Phishing websites' detection. The results of the investigation show that technical ability has no effect whereas Phishing knowledge has a positive effect on Phishing website detection. Thus, there is need to ensure that, regardless their technical ability level (expert or non-expert), the participants do not know about Phishing before they evaluate the effectiveness of a new anti-Phishing approach. This thesis then evaluates the anti-Phishing knowledge retention of the New Approach users and compares it with the knowledge retention of users who are sent anti-Phishing tips by email.
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Nordgren, Daniella. "Phishing attacks targeting hospitals : A study over phishing knowledge at Blekingesjukhuset." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16681.

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Context. Phishing emails is a type of computer attack targeting users and tries to trick them into giving out personal information, follow shady links or download malicious attachments. Phishing is often closely linked to ransomware, which is a type of attack that locks a users computer and asks for a ransom in order to give access back. Ransomware viruses often contaminate a computer through a phishing email. Hospitals are a growing target for these types of attacks because of their need of being able to access their system at all times. Objectives. This study intends to research the phishing knowledge among employees at Blekingesjukhuset and whether Blekingesjukhuset is at a risk of falling victim to a ransomware attack through a phishing email opened by an employee. Methods. This is researched by reading relevant literature and a survey sent out to employees at Blekingesjukhuset regarding their phishing knowledge. Results. The results show that the participants of the survey where overall unsure on how to detect phishing emails and thought that knowledge about the subject is necessary. Conclusions. The conclusion was made that the employees did not know what to look for in order to determine whether an email is a phishing email or not. Based on this information the conclusion can be made that it does exist a risk of Blekingesjukhuset falling victim to a ransomware attack through a phishing email unintentionally opened by an employee.
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Henshaw, James Presley. "Phishing Warden : enhancing content-triggered trust negotiation to prevent phishing attacks /." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd840.pdf.

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Magnusson, Patrik. "Företagens skydd mot phishing." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13731.

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Denna studie kommer undersöka hur företag hanterar phishinghotet. Phishingmail är ettangreppssätt som faller in i begreppet social engineering och kan användas för att luramänniskor att uppge information som de inte ska dela med sig av. Ett phishingmail har sommål att efterlikna ett vanligt mail som tillexempel en fakturapåminnelse. Men istället för attpengarna går till den angivna avsändaren kan attackeraren istället kapa bankuppgifterna. Målet med attacken kan vara olika, det kan vara att ta del av information så sombankuppgifter och eller lösenord. Det kan också sprida skadlig kod som infekterarmottagarens dator med virus. Phishingmail kan se ut på olika sätt och det gör det svårt att geett exakt exempel på hur ett phishingmail ser ut. Målet med denna studie är att ge en uppfattning av hur företag som intervjuas hanterarphishingattacker. Studien har som syfte att identifiera problem, för att ge en bild avhanteringen av phishingattacker. Bilden kommer besvara frågor som, vilka policys finns föratt motverka hotet, hur och när utbildas de anställda samt hur ser de själva på phishing somhot? Sammanställningen bestå av intervjuer från anställda på olika företag som ansvarar förinformationssäkerheten. Efter att intervjuerna genomförts sammanfattas svaren för att kunna utförasammanställningen. Målet med sammanställningen är att redovisa ett resultat som besvararfrågan, vilka åtgärder som finns hos organisationerna för att motverka phishinghotet.Sammanställningen har delats upp i tre huvudgrupper: handlingsplan, utbildning och kultur.Genom att placera in svaren i rätt huvudgrupp blir det en helhetsbild och ett resultat kanpresenteras.Företagen visar förståelse för i vilka problem phishingmail kan ge ett företag. Det finns i regelåtgärder på varje företag för att motverka och förminska hotet. Viss utbildning ges tillanställda. Men phishing anses inte vara ett så stort hot. Den generella uppfattningen frånföretagen är att phishing inte anses vara ett stort hot. Samtidigt berättar dom om händelser däranställda öppnar skadliga mail trotts att det inte finns något hot enligt dom själva. Efter genomförda intervjuer och insamling av information kunde en eventuell annan bristpresenteras. Flera utav de företag som kontaktades ville inte ställa upp på studien på grund avolika anledningar. Så som att det inte fanns någon IT-avdelning eller ren okunskap inomämnet. Detta kan visa på att det finns brister hos flera företag där det inte finns enhelhetslösning på hur informations ska säkras upp och hur informationssäkerheten ska utvecklas.
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Maurer, Max-Emanuel. "Counteracting phishing through HCI." Diss., Ludwig-Maximilians-Universität München, 2014. http://nbn-resolving.de/urn:nbn:de:bvb:19-169668.

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Computer security is a very technical topic that is in many cases hard to grasp for the average user. Especially when using the Internet, the biggest network connecting computers globally together, security and safety are important. In many cases they can be achieved without the user's active participation: securely storing user and customer data on Internet servers is the task of the respective company or service provider, but there are also a lot of cases where the user is involved in the security process, especially when he or she is intentionally attacked. Socially engineered phishing attacks are such a security issue were users are directly attacked to reveal private data and credentials to an unauthorized attacker. These types of attacks are the main focus of the research presented within my thesis. I have a look at how these attacks can be counteracted by detecting them in the first place but also by mediating these detection results to the user. In prior research and development these two areas have most often been regarded separately, and new security measures were developed without taking the final step of interacting with the user into account. This interaction mainly means presenting the detection results and receiving final decisions from the user. As an overarching goal within this thesis I look at these two aspects united, stating the overall protection as the sum of detection and "user intervention". Within nine different research projects about phishing protection this thesis gives answers to ten different research questions in the areas of creating new phishing detectors (phishing detection) and providing usable user feedback for such systems (user intervention): The ten research questions cover five different topics in both areas from the definition of the respective topic over ways how to measure and enhance the areas to finally reasoning about what is making sense. The research questions have been chosen to cover the range of both areas and the interplay between them. They are mostly answered by developing and evaluating different prototypes built within the projects that cover a range of human-centered detection properties and evaluate how well these are suited for phishing detection. I also take a look at different possibilities for user intervention (e.g. how should a warning look like? should it be blocking or non-blocking or perhaps even something else?). As a major contribution I finally present a model that combines phishing detection and user intervention and propose development and evaluation recommendations for similar systems. The research results show that when developing security detectors that yield results being relevant for end users such a detector can only be successful in case the final user feedback already has been taken into account during the development process.
Sicherheit rund um den Computer ist ein, für den durchschnittlichen Benutzer schwer zu verstehendes Thema. Besonders, wenn sich die Benutzer im Internet - dem größten Netzwerk unserer Zeit - bewegen, ist die technische und persönliche Sicherheit der Benutzer extrem wichtig. In vielen Fällen kann diese ohne das Zutun des Benutzers erreicht werden. Datensicherheit auf Servern zu garantieren obliegt den Dienstanbietern, ohne dass eine aktive Mithilfe des Benutzers notwendig ist. Es gibt allerdings auch viele Fälle, bei denen der Benutzer Teil des Sicherheitsprozesses ist, besonders dann, wenn er selbst ein Opfer von Attacken wird. Phishing Attacken sind dabei ein besonders wichtiges Beispiel, bei dem Angreifer versuchen durch soziale Manipulation an private Daten des Nutzers zu gelangen. Diese Art der Angriffe stehen im Fokus meiner vorliegenden Arbeit. Dabei werfe ich einen Blick darauf, wie solchen Attacken entgegen gewirkt werden kann, indem man sie nicht nur aufspürt, sondern auch das Ergebnis des Erkennungsprozesses dem Benutzer vermittelt. Die bisherige Forschung und Entwicklung betrachtete diese beiden Bereiche meistens getrennt. Dabei wurden Sicherheitsmechanismen entwickelt, ohne den finalen Schritt der Präsentation zum Benutzer hin einzubeziehen. Dies bezieht sich hauptsächlich auf die Präsentation der Ergebnisse um dann den Benutzer eine ordnungsgemäße Entscheidung treffen zu lassen. Als übergreifendes Ziel dieser Arbeit betrachte ich diese beiden Aspekte zusammen und postuliere, dass Benutzerschutz die Summe aus Problemdetektion und Benutzerintervention' ("user intervention") ist. Mit Hilfe von neun verschiedenen Forschungsprojekten über Phishingschutz beantworte ich in dieser Arbeit zehn Forschungsfragen über die Erstellung von Detektoren ("phishing detection") und das Bereitstellen benutzbaren Feedbacks für solche Systeme ("user intervention"). Die zehn verschiedenen Forschungsfragen decken dabei jeweils fünf verschiedene Bereiche ab. Diese Bereiche erstrecken sich von der Definition des entsprechenden Themas über Messmethoden und Verbesserungsmöglichkeiten bis hin zu Überlegungen über das Kosten-Nutzen-Verhältnis. Dabei wurden die Forschungsfragen so gewählt, dass sie die beiden Bereiche breit abdecken und auf die Abhängigkeiten zwischen beiden Bereichen eingegangen werden kann. Die Forschungsfragen werden hauptsächlich durch das Schaffen verschiedener Prototypen innerhalb der verschiedenen Projekte beantwortet um so einen großen Bereich benutzerzentrierter Erkennungsparameter abzudecken und auszuwerten wie gut diese für die Phishingerkennung geeignet sind. Außerdem habe ich mich mit den verschiedenen Möglichkeiten der Benutzerintervention befasst (z.B. Wie sollte eine Warnung aussehen? Sollte sie Benutzerinteraktion blockieren oder nicht?). Ein weiterer Hauptbeitrag ist schlussendlich die Präsentation eines Modells, dass die Entwicklung von Phishingerkennung und Benutzerinteraktionsmaßnahmen zusammenführt und anhand dessen dann Entwicklungs- und Analyseempfehlungen für ähnliche Systeme gegeben werden. Die Forschungsergebnisse zeigen, dass Detektoren im Rahmen von Computersicherheitsproblemen die eine Rolle für den Endnutzer spielen nur dann erfolgreich entwickelt werden können, wenn das endgültige Benutzerfeedback bereits in den Entwicklungsprozesses des Detektors einfließt.
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Kalinová, Diana. "Phishing a ľudský faktor." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-192464.

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The main aim of the diploma thesis is to underline the importance of human factor for the success of phishing attacks and to identify the reasons, why the Czech and Slovak users are vulnerable to phishing. The thesis focuses on the user as the weakest part in the system which phishers exploit. Social and technical tricks that are cheating users are in the second chapter. The third chapter focuses on social engineering and sociological methods of attack. The fourth chapter is devoted to the delivery of phishing and fifth chapter explores the various types of phishing attacks. The sixth chapter presents the reasons for the operation of phishing, the aspects of credibility and authenticity of e-mails and web sites, that users follow and the implications of using the context in phishing. The victims of phishing have specific reactions which are mentioned in the seventh chapter. The eighth chapter explores the various measures against phishing, not just technology. Mentioned eight chapters present a theoretical basis for the following chapters of the diploma thesis. In the ninth chapter is performed analysis of the global situation of phishing. Through analysis are identified current and historical trends in phishing. Finally, the chapter shows the implications for the user. The tenth chapter is devoted to the phishing attacks in the Czech and Slovak Republic which are interesting in terms of the importance of human factor. We determine whether users are able to defend attacks only with their carefulness, mindfulness and awareness of phishing. Within the last chapter is taken empirical research through the questionnaire survey. The research verifies the awareness of the Czech and Slovak users about phishing, their personal experiences with phishing, their security habits and the aspects of credibility and authenticity that they consider in emails and websites. Based on all findings are drawn conclusions and recommendations.
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Dong, Xun. "Defending against phishing attacks." Thesis, University of York, 2009. http://etheses.whiterose.ac.uk/2215/.

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Valuable information, such as user authentication credentials and personal sensitive information, can be obtained by exploiting vulnerabilities within the user’s understanding of a system, and particularly a lack of understanding of the user interface. As the barrier to exploiting system vulnerabilities has increased significantly with time, attacking users has rapidly become a more efficient and effective alternative. To protect users from phishing attacks system designers and security professionals need to understand how users interact with those attacks. In this thesis I present an improved understanding of the interaction and three novel mechanisms to defend against phishing attacks.
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Le, Page Sophie. "Understanding the Phishing Ecosystem." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39385.

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In “phishing attacks”, phishing websites mimic trustworthy websites in order to steal sensitive information from end-users. Despite research by both academia and the industry focusing on development of anti-phishing detection techniques, phishing has increasingly become an online threat. Our inability to slow down phishing attacks shows that we need to go beyond detection and focus more on understanding the phishing ecosystem. In this thesis, we contribute in three ways to understand the phishing ecosystem and to offer insight for future anti-phishing efforts. First, we provide a new and comparative study on the life cycle of phishing and malware attacks. Specifically, we use public click-through statistics of the Bitly URL shortening service to analyze the click-through rate and timespan of phishing and malware attacks before (and after) they were reported. We find that the efforts against phishing attacks are stronger than those against malware attacks.We also find phishing activity indicating that mitigation strategies are not taking down phishing websites fast enough. Second, we develop a method that finds similarities between the DOMs of phishing attacks, since it is known that phishing attacks are variations of previous attacks. We find that existing methods do not capture the structure of the DOM, and question whether they are failing to catch some of the similar attacks. We accordingly evaluate the feasibility of applying Pawlik and Augsten’s recent implementation of Tree Edit Distance (AP-TED)calculations as a way to compare DOMs and identify similar phishing attack instances.Our method agrees with existing ones that 94% of our phishing database are replicas. It also better discriminates the similarities, but at a higher computational cost. The high agreement between methods strengthens the understanding that most phishing attacks are variations, which affects future anti-phishing strategies.Third, we develop a domain classifier exploiting the history and internet presence of a domain with machine learning techniques. It uses only publicly available information to determine whether a known phishing website is hosted on a legitimate but compromised domain, in which case the domain owner is also a victim, or whether the domain itself is maliciously registered. This is especially relevant due to the recent adoption of the General Data Protection Regulation (GDPR), which prevents certain registration information to be made publicly available. Our classifier achieves 94% accuracy on future malicious domains,while maintaining 88% and 92% accuracy on malicious and compromised datasets respectively from two other sources. Accurate domain classification offers insight with regard to different take-down strategies, and with regard to registrars’ prevention of fraudulent registrations.
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Books on the topic "Phishing"

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Lininger, Rachel. Phishing. New York: John Wiley & Sons, Ltd., 2005.

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Jakobsson, Markus, and Steven Myers, eds. Phishing and Countermeasures. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470086106.

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Hadnagy, Christopher, and Michele Fincher. Phishing Dark Waters. Indianapolis, Indiana, USA: John Wiley & Sons, Inc, 2015. http://dx.doi.org/10.1002/9781119183624.

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Sonowal, Gunikhan. Phishing and Communication Channels. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7744-7.

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Gundar, Ud. Dag ba-reshet: Phishing. Ḳiryat Gat: Ḳorʼim, 2018.

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1952-, Vines Russell Dean, ed. Phishing: Cutting the identity theft line. Indianapolis, IN: Wiley Pub., 2005.

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United States. Federal Trade Commission. Office of Consumer and Business Education., ed. Cómo evitar que lo 'pesquen' con una red de estafa electrónica. [Washington, D.C.]: Federal Trade Commission, Bureau of Consumer Protection, Office of Consumer and Business Education, 2005.

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Budnick, Dean. The Phishing manual: A compendium to the music of Phish. New York: Hyperion, 1996.

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Budnick, Dean. The Phishing manual: A compendium to the music of Phish. New York: Hyperion, 1996.

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Organisation for Economic Co-operation and Development., ed. Online identity theft. Paris: OECD, 2009.

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Book chapters on the topic "Phishing"

1

Prasad, Ramjee, and Vandana Rohokale. "Phishing." In Springer Series in Wireless Technology, 33–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31703-4_3.

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Ziegler, Manuel. "Phishing." In Web Hacking, 117–23. München: Carl Hanser Verlag GmbH & Co. KG, 2014. http://dx.doi.org/10.3139/9783446441125.008.

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Zhu, Yada, and Jingrui He. "Social Phishing." In Encyclopedia of Social Network Analysis and Mining, 1–7. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_290-1.

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Moallem, Abbas. "Phishing Detection." In Understanding Cybersecurity Technologies, 57–68. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003038429-7.

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Sonowal, Gunikhan. "Phishing Kits." In Phishing and Communication Channels, 115–35. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7744-7_6.

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Zhu, Yada, and Jingrui He. "Social Phishing." In Encyclopedia of Social Network Analysis and Mining, 2762–68. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_290.

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Langford, Tyson, and Bryson Payne. "Phishing Faster: Implementing ChatGPT into Phishing Campaigns." In Lecture Notes in Networks and Systems, 174–87. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47454-5_13.

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Topor, Lev. "White Supremacy." In Phishing for Nazis, 38–66. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003320265-3.

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Topor, Lev. "Antisemitism on the Dark Web." In Phishing for Nazis, 95–117. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003320265-5.

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Topor, Lev. "Introduction." In Phishing for Nazis, 1–19. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003320265-1.

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Conference papers on the topic "Phishing"

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Rangasamy, Gokul, Primya T, Gurupriya Kumar, Harinath Sivakumar, and Kanagaraj G. "Phishion: Phishing Detection Application." In 2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE). IEEE, 2024. http://dx.doi.org/10.1109/ic-etite58242.2024.10493749.

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Tout, Hicham, and William Hafner. "Phishpin: An Identity-Based Anti-phishing Approach." In 2009 International Conference on Computational Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/cse.2009.306.

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Merugula, Suneetha, K. Suresh Kumar, Satish Muppidi, and Ch Vidyadhari. "Stop Phishing : Master Anti-Phishing Techniques." In 2022 IEEE North Karnataka Subsection Flagship International Conference (NKCon). IEEE, 2022. http://dx.doi.org/10.1109/nkcon56289.2022.10126569.

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Blancaflor, Eric B., Adrian B. Alfonso, Kevin Nicholas U. Banganay, Gabriel Angelo B. Dela Cruz, Karen E. Fernandez, and Shawn Austin M. Santos. "Let's Go Phishing: A Phishing Awareness Campaign Using Smishing, Email Phishing, and Social Media Phishing Tools." In 11th Annual International Conference on Industrial Engineering and Operations Management. Michigan, USA: IEOM Society International, 2021. http://dx.doi.org/10.46254/an11.20211105.

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B. Blancaflor, Eric, Adrian B. Alfonso, Kevin Nicholas U. Banganay, Gabriel Angelo B. Dela Cruz, and Karen E. Fernandez. "Let's Go Phishing: A Phishing Awareness Campaign Using Smishing, Email Phishing, and Social Media Phishing Tools." In 1st Asia Pacific International Conference on Industrial Engineering and Operations Management. Michigan, USA: IEOM Society International, 2021. http://dx.doi.org/10.46254/ap01.20210108.

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"PHISHPIN: AN INTEGRATED, IDENTITY-BASED ANTI-PHISHING APPROACH." In International Conference on Security and Cryptography. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0002222503690374.

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Lim, Wei Heng, Weng Foong Liew, Chun Yew Lum, and Seah Fang Lee. "Phishing Security: Attack, Detection, and Prevention Mechanisms." In International Conference on Digital Transformation and Applications (ICDXA 2020). Tunku Abdul Rahman University College, 2020. http://dx.doi.org/10.56453/icdxa.2020.1017.

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Abstract:
While the Internet technologies have been developed over the decades, a significant issue has been coming along with it, the cybercrime. Cybercrime consists of various types of cyberattacks which could bring mild to serious adverse effects to individuals or organizations’ operations. Among those cybercrime attacks, phishing is one of the common mechanisms used. The phishing attack could target on any of the electronic communication users. The paper provides an overview insight on the phishing security concepts, ranging from various types of phishing attack techniques, phishing detection mechanism to prevention approaches. Comparison were included for each of the phishing aspects. Keywords: Phishing attack, phishing detection, phishing prevention, phishing security
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Dhamija, Rachna, Peter Cassidy, Phillip Hallam-Baker, and Markus Jacobsson. "Phoiling phishing." In the 15th international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1135777.1135888.

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PREDU, Adrian. "Phishing: A Present Threat." In International Conference on Cybersecurity and Cybercrime. Romanian Association for Information Security Assurance, 2014. http://dx.doi.org/10.19107/cybercon.2014.07.

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Phishing can be seen as a threat that keeps growing day by day, which has as a primary objective the obtaining of money from different kind of customers, through fraud. In less than two decades, this illegal practice managed to become an industry with an annual worldwide financial impact of billions of dollars. This paper tries to explain what phishing means and how it evolved into a global threat, presents the main types of phishing techniques that are currently used, as well as solutions against them.
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Liu, Gang, Bite Qiu, and Liu Wenyin. "Automatic Detection of Phishing Target from Phishing Webpage." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.1010.

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Reports on the topic "Phishing"

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Fette, Ian, Norman Sadeh, and Anthony Tomasic. Learning to Detect Phishing Emails. Fort Belvoir, VA: Defense Technical Information Center, June 2006. http://dx.doi.org/10.21236/ada456046.

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Kohli-Laven, Nina, and John F. Buford. Robust and Efficient Anti-Phishing Techniques. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada586670.

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Cain, P., and D. Jevans. Extensions to the IODEF-Document Class for Reporting Phishing. RFC Editor, July 2010. http://dx.doi.org/10.17487/rfc5901.

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Wendt, Jeremy Daniel. Omen: identifying potential spear-phishing targets before the email is sent. Office of Scientific and Technical Information (OSTI), July 2013. http://dx.doi.org/10.2172/1093687.

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Tamborello, Franklin P., and Kristen K. Greene. Exploratory lens model of decision-making in a potential phishing attack scenario. Gaithersburg, MD: National Institute of Standards and Technology, October 2017. http://dx.doi.org/10.6028/nist.ir.8194.

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Chowdhury, Jannatul Nayim, and Wahid bin Ahsan. Online Privacy Awareness in Bangladesh: Challenges and Solutions. Userhub, May 2024. http://dx.doi.org/10.58947/nydl-lbvp.

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In recent times, individuals in Bangladesh are facing serious challenges due to their growing dependency on the internet. This study employs a qualitative research design to identify a lack of understanding and awareness of internet usage among individuals, coupled with the negligence of authorities, as the primary causes of these issues. The findings reveal that while most people are aware of online scams, phishing, and suspicious links, they often share personal information without reading privacy policies due to their complexity. Additionally, there is a significant lack of knowledge about government laws and regulations regarding online privacy. The study suggests that comprehensive educational initiatives are essential to improve online privacy practices in Bangladesh.
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