In 2023, the most common type of cyber crime reported to the United States internet Crime Complaint Center was phishing and spoofing, affecting approximately 298 thousand individuals. In addition, over 55 thousand cases of personal data breaches cases were reported to the IC3 during that year. Dynamic of phishing attacks Over the past few years, phishing attacks have increased significantly. In 2023, almost 300 thousand individuals fell victim to such attacks. The highest number of phishing scam victims since 2018 was recorded in 2021, approximately 324 thousand.Phishing attacks can take many shapes. Bulk phishing, smishing, and business e-mail compromise (BEC) are the most common types. In 2023, 76 percent of the surveyed worldwide organizations reported encountering bulk phishing attacks, while roughly three in four were targeted by smishing scams. Impact of phishing attacks Among the most targeted industries by cybercriminals are healthcare, financial, manufacturing, and education institutions. An observation carried out in the first quarter of 2023 found that social media was most likely to encounter phishing attacks. According to the reports, almost a quarter of them stated being targeted by a phishing scam in the measured period. Very often, phishing e-mails contain a crucial risk for the organization. Almost three in ten worldwide organizations that have experienced phishing attacks suffered from a customer or a client data breach as a consequence. Phishing scams that delivered ransomware infections were also common for the surveyed organizations.

In 2023, 21,489 individuals in the United States reported encountering business e-mail compromise (BEC) scams. This figure has slightly increased in the last three years, with 19,954 reported victims in 2021 and, 21,832 in 2022.

1) Data Introduction • The Email Phishing Dataset is designed for phishing email detection using machine learning.

2) Data Utilization (1) Email Phishing Dataset has characteristics that: • All emails were refined and subjected to a custom NLP feature extraction pipeline focused on phishing metrics. • This dataset contains no raw text or headers, only features engineered for model training/testing. (2) Email Phishing Dataset can be used to: • Developing an email detection model: It can be used to train and evaluate AI models that classify normal mail and phishing mail using various characteristics such as email body, subject, and sender. • E-mail security policy and threat analysis research: Analyzing real phishing cases and normal email data to derive the characteristics of phishing attacks, and use them to establish effective email security policies and develop threat response strategies.

During the fourth quarter of 2024, nearly 23 percent of phishing attacks worldwide targeted social media. Web-based software services and webmail were targeted by over 23 percent of registered phishing attacks. Furthermore, financial institutions accounted for 12 percent of attacks.

data-phishing-detection

A dataset to test methods to detect phishing emails The file data.parquet contains the dataset, 400 emails. 200 are synthetic phishing attempts and 200 are synthetic regular emails.

  Schema

input - an email, synthesized by an LLM, that is either a phishing attempt or a regular email. output - 'Yes' if the email is a phishing attempt, 'No' otherwise.

  Prompt

The prompt.md file contains a prompt that can be used with an LLM as a starting… See the full description on the dataset page: https://huggingface.co/datasets/RevaHQ/data-phishing-detection.

In December 2023, around 9.45 million phishing e-mails were detected worldwide, up from 5.59 million in September 2023. This figure has seen a continuous increase since January 2022. It is partially associated with the launch of ChatGPT in November 2022.

Introduction

Phishing Statistics: Phishing is a kind of cyberattack in which criminals try to fool people into sharing personal information such as passwords or credit card numbers, often by pretending to be a trusted company or person through fake emails, websites, or messages. Phishing has become more common as many people use the Internet for banking, shopping, and communication.

In 2024, phishing attacks are a major threat to both individuals and businesses. Criminals are using more advanced techniques, and these attacks are costing billions of dollars globally. People need to stay aware and cautious online to avoid falling victim to these scams.

A partial dataset and document-term matrix of phishing emails targeting an institution of higher education and an associated script used for data analysis.

Introduction

Spam Statistics: In today’s digitally connected world, we all face the problem of online spam that is included within emails, text messages, social media chats, phone calls, and in many other segments. Globally, almost everyone gets some kind of spam every single day. In technology and cybersecurity, spam means unwanted messages sent to many people at once, usually with useless or harmful content.

This article will help you understand what spam is, where it comes from, and how it affects us so we can keep our emails safe and clean. Go through the overall article that includes several current statistical analyses from different insights that will allow you to understand the topic better.

A survey conducted in April 2020 revealed that the largest share of employees worldwide that had clicked on phishing email links were aged between 31 and 40 years old. Although those over ** were the least likely to have clicked on a phishing email, these older employees were also twice as likely to be unaware of what a phishing email was.

In 2000, Enron was one of the largest companies in the United States. By 2002, it had collapsed into bankruptcy due to widespread corporate fraud. The data has been made public and presents a diverse set of email information ranging from internal, marketing emails to spam and fraud attempts.

In the early 2000s, Leslie Kaelbling at MIT purchased the dataset and noted that, though the dataset contained scam emails, it also had several integrity problems. The dataset was updated later, but it becomes key to ensure privacy in the data while it is used to train a deep neural network model.

Though the Enron Email Dataset contains over 500K emails, one of the problems with the dataset is the availability of labeled frauds in the dataset. Label annotation is done to detect an umbrella of fraud emails accurately. Since, fraud emails fall into several types such as Phishing, Financial, Romance, Subscription, and Nigerian Prince scams, there have to be multiple heuristics used to label all types of fraudulent emails effectively.

To tackle this problem, heuristics have been used to label the Enron data corpus using email signals, and automated labeling has been performed using simple ML models on other smaller email datasets available online. These fraud annotation techniques are discussed in detail below.

To perform fraud annotation on the Enron dataset as well as provide more fraud examples for modeling, two more fraud data sources have been used, Phishing Email Dataset: https://www.kaggle.com/dsv/6090437 Social Engineering Dataset: http://aclweb.org/aclwiki

Label Annotation

To label the Enron email dataset two signals are used to filter suspicious emails and label them into fraud and non-fraud classes. Automated ML labeling Email Signals

Automated ML Labeling

The following heuristics are used to annotate labels for Enron email data using the other two data sources,

Phishing Model Annotation: A high-precision SVM model trained on the Phishing mails dataset, which is used to annotate the Phishing Label on the Enron Dataset.

Social Engineering Model Annotation: A high-precision SVM model trained on the Social Engineering mails dataset, which is used to annotate the Social Engineering Label on the Enron Dataset.

The two ML Annotator models use Term Frequency Inverse Document Frequency (TF-IDF) to embed the input text and make use of SVM models with Gaussian Kernel.

If either of the models predicted that an email was a fraud, the mail metadata was checked for several email signals. If these heuristics meet the requirements of a high-probability fraud email, we label it as a fraud email.

Email Signals

Email Signal-based heuristics are used to filter and target suspicious emails for fraud labeling specifically. The signals used were,

Person Of Interest: There is a publicly available list of email addresses of employees who were liable for the massive data leak at Enron. These user mailboxes have a higher chance of containing quality fraud emails.

Suspicious Folders: The Enron data is dumped into several folders for every employee. Folders consist of inbox, deleted_items, junk, calendar, etc. A set of folders with a higher chance of containing fraud emails, such as Deleted Items and Junk.

Sender Type: The sender type was categorized as ‘Internal’ and ‘External’ based on their email address.

Low Communication: A threshold of 4 emails based on the table below was used to define Low Communication. A user qualifies as a Low-Comm sender if their emails are below this threshold. Mails sent from low-comm senders have been assigned with a high probability of being a fraud.

Contains Replies and Forwards: If an email contains forwards or replies, a low probability was assigned for it to be a fraud email.

Manual Inspection

To ensure high-quality labels, the mismatch examples from ML Annotation have been manually inspected for Enron dataset relabeling.

Dataset Breakdown

Citations

Enron Dataset Title: Enron Email Dataset URL: https://www.cs.cmu.edu/~enron/ Publisher: MIT, CMU Author: Leslie Kaelbling, William W. Cohen Year: 2015

Phishing Email Detection Dataset Title: Phishing Email Detection URL: https://www.kaggle.com/dsv/6090437 DOI: 10.34740/KAGGLE/DSV/6090437 Publisher: Kaggle Author: Subhadeep Chakraborty Year: 2023

CLAIR Fraud Email Collection Title: CLAIR collection of fraud email URL: http://aclweb.org/aclwiki Author: Radev, D. Year: 2008

Dataset Card for "phishing-emails"

More Information needed

We have curated 7 repositories.The Ling and Enron datasets possess just two features: ‘Subject’ and ‘Body’. The other datasets consists of six features, namely ‘Sender’, ‘Receiver’, ‘Date’, ‘Subject’, ‘Body’, and ‘Urls’.Please cite this dataset:A. I. Champa, M. F. Rabbi, and M. F. Zibran, “Curated datasets and feature analysis for phishing email detection with machine learning,” in 3rd IEEE International Conference on Computing and Machine Intelligence (ICMI), 2024, pp. 1–7 (to appear).or @inproceedings{champa2024curated, title={Curated Datasets and Feature Analysis for Phishing Email Detection with Machine Learning}, author={Champa, Arifa I and Rabbi, Md Fazle and Zibran, Minhaz F}, booktitle={3rd IEEE International Conference on Computing and Machine Intelligence (ICMI)}, pages = {1--7 (to appear)}, year={2024}}

Spear Phishing Email Solution Market Outlook

The global spear phishing email solution market size was valued at USD 1.2 billion in 2023 and is expected to reach USD 4.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 15.5% during the forecast period. This impressive growth can be attributed to the rising number of phishing attacks targeting enterprises and the increasing need for robust email security solutions. With the proliferation of digital communication in business operations, the risk of falling prey to sophisticated spear phishing attacks has significantly heightened, driving the demand for specialized email security solutions.

One of the primary growth factors in the spear phishing email solution market is the increasing sophistication of phishing attacks. Cybercriminals are employing more advanced tactics and technologies to execute highly targeted attacks that are difficult to detect with traditional security measures. This has led to a growing awareness among organizations about the necessity of implementing advanced spear phishing solutions to safeguard sensitive information and maintain business continuity. Additionally, regulatory requirements and compliance mandates across various industries are compelling organizations to adopt comprehensive email security measures, further propelling market growth.

Another significant driver for the market is the rising adoption of cloud-based email solutions. As businesses continue to migrate their operations to the cloud, the need for cloud-native security solutions that can effectively protect against phishing threats has surged. Cloud-based spear phishing email solutions offer several benefits, including scalability, flexibility, and reduced costs, making them an attractive option for organizations of all sizes. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) technologies into these solutions enhances their ability to detect and mitigate phishing attempts in real-time, thereby boosting their adoption across various sectors.

The increasing frequency of high-profile data breaches and cyber-attacks has also underscored the importance of robust email security. Organizations are becoming more proactive in their approach to cybersecurity, investing in advanced solutions to prevent potential financial losses and reputational damage. The financial services, healthcare, and government sectors, in particular, have emerged as significant contributors to the market's growth due to the critical nature of the data they handle. These sectors are increasingly deploying spear phishing email solutions to protect their sensitive information from malicious actors.

Regionally, North America is expected to dominate the spear phishing email solution market during the forecast period, owing to the early adoption of advanced cybersecurity solutions and the presence of key market players in the region. Europe and the Asia Pacific are also anticipated to witness substantial growth, driven by increasing digitalization, the rising number of cyber threats, and stringent regulatory requirements. The increasing awareness and adoption of spear phishing solutions in Latin America and the Middle East & Africa are also expected to contribute to the overall market growth.

Component Analysis

The spear phishing email solution market can be segmented by component into software and services. The software segment includes solutions designed to detect, prevent, and respond to spear phishing attacks. These software solutions leverage advanced technologies such as artificial intelligence (AI), machine learning (ML), and behavioral analysis to identify and mitigate phishing threats. The growing sophistication of phishing attacks has necessitated the adoption of advanced email security software, making this segment a significant contributor to the market's growth.

The services segment, on the other hand, encompasses various professional and managed services aimed at enhancing an organization's email security posture. Professional services include consulting, training, and implementation services provided by cybersecurity experts to help organizations effectively deploy and manage spear phishing email solutions. Managed services involve outsourcing the management and monitoring of email security to third-party service providers, allowing organizations to focus on their core business operations while ensuring robust protection against phishing threats.

Within the software segment, the integration of AI and ML technologies has significantly

This API is providing the information of press releases issued by the authorized institutions and other similar press releases issued by the HKMA in the past regarding fraudulent bank websites, phishing E-mails and similar scams information.

The phishing protection market is experiencing robust growth, driven by the escalating sophistication and frequency of phishing attacks targeting individuals and organizations across diverse sectors. The increasing reliance on digital platforms for banking, e-commerce, and communication has created a fertile ground for cybercriminals, necessitating robust security measures. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based security solutions, the proliferation of mobile devices, and the increasing awareness of phishing threats among both individuals and businesses. Furthermore, stringent government regulations concerning data privacy and security are compelling organizations to invest heavily in advanced phishing protection technologies. While the BFSI (Banking, Financial Services, and Insurance) sector remains a significant adopter, growth is also observed across other sectors like healthcare, government, and telecommunications, due to their sensitive data assets and heightened regulatory scrutiny. The market is segmented by application (BFSI, Government, Healthcare, Telecommunications and IT, Transportation, Education, Retail) and type of phishing (email-based, non-email-based), each presenting unique opportunities for specialized solutions. Companies like Cyren, BAE Systems, Microsoft, FireEye, Symantec, Proofpoint, GreatHorn, Cisco, Phishlabs, Intel, and Mimecast are key players, constantly innovating to counter evolving phishing tactics. The market's growth trajectory is projected to remain positive over the forecast period (2025-2033), although challenges remain. These include the ever-evolving nature of phishing techniques, the difficulty in detecting sophisticated attacks, and the ongoing skills gap in cybersecurity expertise. Despite these obstacles, the market’s future looks promising, spurred by continuous advancements in artificial intelligence (AI) and machine learning (ML) technologies which enhance threat detection and response capabilities. The increasing adoption of multi-layered security solutions, incorporating phishing protection alongside other security measures, further contributes to the overall market growth. The geographical distribution of the market indicates strong growth in North America and Europe, while the Asia-Pacific region is poised for significant expansion in the coming years, driven by increasing internet penetration and digitalization.

The phishing protection market is experiencing robust growth, driven by the escalating sophistication of phishing attacks and the increasing reliance on digital platforms across various sectors. While precise market size figures for 2025 are unavailable, a logical estimation based on industry reports and observed CAGR trends in cybersecurity suggests a market value exceeding $10 billion in 2025. Considering a conservative Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, the market is projected to reach approximately $35 billion by 2033. This significant expansion is fueled by several key factors, including the rising adoption of cloud-based services, the proliferation of mobile devices, and the increasing frequency of advanced persistent threats (APTs). Organizations across diverse industries are prioritizing robust phishing protection solutions to safeguard their sensitive data and maintain operational continuity. The market's expansion is also being shaped by evolving trends such as artificial intelligence (AI)-powered threat detection, integration with security information and event management (SIEM) systems, and the growing demand for user-focused security awareness training programs. However, certain restraints limit the market's growth potential. These include the high cost of advanced phishing protection solutions, the need for skilled professionals to manage and maintain these systems, and the ongoing challenge of keeping pace with the constantly evolving tactics of cybercriminals. Despite these hurdles, the persistent threat landscape ensures a continued, albeit potentially moderated, growth trajectory for the phishing protection market throughout the forecast period. Major players like Cyren, BAE Systems, Microsoft, FireEye, Symantec, Proofpoint, GreatHorn, Cisco, PhishLabs, Intel, and Mimecast are actively competing to innovate and capture significant market share. The geographic distribution of the market reveals strong growth across North America and Europe, with emerging markets showing significant potential for future expansion.

The email-based phishing protection market is experiencing robust growth, projected to reach a substantial size. The market's Compound Annual Growth Rate (CAGR) of 20.3% from 2019-2033 indicates a significant upward trajectory driven by the increasing sophistication of phishing attacks and the rising adoption of cloud-based email services. Businesses of all sizes are facing escalating cybersecurity threats, making robust email security a critical investment. The market is further fueled by the growing awareness of data privacy regulations and the resulting need for compliance, pushing organizations to proactively implement advanced phishing protection measures. Key players like Cyren, BAE Systems, Microsoft, and others are investing heavily in research and development to enhance their offerings, creating a competitive landscape that fosters innovation and drives market expansion. The segment breakdown (while not provided) likely includes solutions categorized by deployment (cloud, on-premise), size of organization (SMB, enterprise), and specific features (anti-spoofing, machine learning-based detection). The forecast period (2025-2033) will see continued expansion, primarily driven by the increasing adoption of advanced threat detection techniques, including AI and machine learning. However, market restraints might include the rising costs associated with implementing and maintaining these solutions, especially for smaller organizations. Despite this, the overall market outlook remains positive due to the ever-increasing threat landscape and the escalating consequences of successful phishing attacks, leading to substantial financial and reputational damage. The geographical distribution is expected to show strong growth in regions with rapidly developing digital economies and increasing internet penetration. Understanding these dynamics is crucial for businesses seeking to capitalize on the opportunities presented within this growing market.

Market Overview and Growth Dynamics: The global email-based phishing protection market is experiencing robust growth, with a projected market size of $1844.9 million by 2033. Driven by increasing cyber threats and the prevalence of targeted phishing attacks, the market is poised to maintain a high CAGR of 20.3% during the forecast period (2025-2033). This growth is fueled by the adoption of advanced security technologies, such as AI-powered threat detection and response systems, as organizations seek to protect their sensitive data and assets from phishing attacks. Market Segmentation, Trends, and Key Players: The market is segmented based on application (SMEs, large enterprises) and deployment type (cloud, on-premises). Cloud-based solutions are gaining popularity due to their scalability, cost-effectiveness, and ease of deployment. Key market trends include the rise of phishing-as-a-service (PhaaS), increased integration with other cybersecurity solutions, and the adoption of encryption and multi-factor authentication techniques. Prominent players in the market include Cyren, BAE Systems, Microsoft Corporation, FireEye Inc., and Symantec Corporation. These companies offer a range of email phishing protection solutions tailored to meet the specific needs of businesses of all sizes.

The Spear Phishing Email Solution market has emerged as a critical segment in cybersecurity, addressing the increasing sophistication and prevalence of spear phishing attacks targeting individuals and organizations alike. Spear phishing, unlike traditional phishing, involves highly personalized emails that are tailo