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【2020 Application Example】 Through smart sensing technology, effectively reducing the misjudgment rate of business email fraud by over 50%, safeguarding corporate finances!

Business email fraud causes over ten billion USD in losses annually!

Business Email Compromise (BEC) has become a global threat, causing losses of over ten billion dollars every year. Criminal organizations target victim companies in various ways, infiltrating and lurking over long periods to steal information, eventually orchestrating scams to induce victims to make payments or transact with the wrong parties.

In such crimes, key fraudulent emails often appear indistinguishable from ordinary business or personal correspondence because they match business contexts and daily transaction behaviors. BEC messages may not even contain URLs or attachments that could be detected by technical security measures, rendering antivirus and click-prevention strategies ineffective.

With email fraud being rampant, effective prevention of such threats has become a top priority!

A domestic biomedical manufacturer, one of the government's five major innovation industries and a recipient of the 13th Startup Business Award from the Ministry of Economic Affairs, features high innovation and high risk in the biotechnology sector. Handling sensitive information related to new drugs, experimental materials, or market development, and even confidential personal data tied to medical and clinical trials, the company faces substantial threats from BEC scams. They hope to leverage AI's interpretation capabilities for more accurate and comprehensive alerts against malicious emails, ultimately enhancing productivity and avoiding scams.

Utilizing AI recognition to preemptively deter threatening emails, effectively boosting corporate productivity!

'Artificial Intelligence-assisted BEC transaction intent perception' is a feature developed by NetzEngine Information Software Co., Ltd. and Dupont Digital Security Ltd., capable of identifying emails with transactional intents and incorporating them into NetzEngine's MailGates email behavior analysis module to detect threatening messages and improve the detection accuracy of suspicious threat emails.

This case uses two functionalities from the aforementioned AI technologies, 'Email Fraud Protection by Mail Header Security Policy' and 'Email Fraud Protection by Email Behavior Analysis Policy'.

Openfind MailGates' 'Mail Header Security Policy' feature

▲Openfind MailGates' 'Mail Header Security Policy' feature

In MailGates' 'Email Fraud Protection' features, the 'Mail Header Security Policy' can be adjusted. For example, all emails from hotmail.com must have a correct From header, but the Reply-to header will be blank, this is the correct format for Hotmail emails, the same applies to Gmail.

If the email comes from another source, however, it should adhere to the filtering rules recommended by MailGates: Both From and Reply-to should come from the correct and same domain, otherwise, it is likely to be a fraudulent message. The third rule in the image represents all emails from openfind.com.tw should use the aforementioned default rules for inspection. If an email does not comply with the Mail Header Security Policy as per this setup, users will receive a 'Email Fraud Warning' notification on the subject line, helping to prevent BEC email fraud.

▲Openfind MailGates' 'Email Behavior Analysis Policy' feature, can set 'Protection Level'

Openfind MailGates' 'Email Behavior Analysis Policy' feature, can set 'Operational Actions'

▲Openfind MailGates' 'Email Behavior Analysis Policy' feature, can set 'Operational Actions'

In MailGates' 'Email Fraud Protection' feature, the 'Email Behavior Analysis Policy' can be applied as needed. This feature's design and settings might seem complex for average users, who could opt for the 'Intelligent Detection' method instead, simply choosing among 'Loose, Standard, Strict' levels. The system will determine the actual settings for these levels based on recently collected feedback data. More skilled managers can use the 'Custom' mode, to set all behavior analysis functionalities in detail.

For example, by listing commonly impersonated domain names under 'Similar External Domains', the system will automatically consider similar but unequal domains, intended to impersonate and deceive users, as higher threat sources. This feature allows users to set alerts for such emails, including using title and content warnings, and through behavior analysis, if the system deems the email likely to be a BEC fraud, it will clearly prompt users to be vigilant.

'Email Fraud Protection by Mail Header Security Policy' and 'Email Fraud Protection by Email Behavior Analysis Policy' are actually planned and designed functionalities incorporated into the MailGates email protection system, combined with the aforementioned AI research outcomes, all MailGates users will be able to utilize these two functions against BEC scam emails.

For corporate clients, 'missed threat emails' represent the most significant information security threat and the aspect most needing improvement. With the adoption of NetzEngine's BEC smart sensing mechanisms, they can immediately and effectively reduce the threats of BEC scams within the unit, avoiding scams and boosting corporate productivity!

Comprehensively guarding客户 client email security, expanding the value of the domestic information security industry

NetzEngine Information Software Co., Ltd., in collaboration with AI startup Dupont Digital Security Ltd., adopts NLP and more specialized threat analysis technologies, capable of intelligently perceiving emails with transaction intentions and increasing the interception rate of BEC emails. This not only enhances client value and maintains their cybersecurity capabilities, but as a leader in domestic email security, Openfind NetzEngine Information will continue to develop solutions for email and messaging communication security.

In the future, NetzEngine plans to integrate BEC protection and APT sandbox defense technologies, continuously expanding into a derivative product line: Advanced Threat Protections. By addressing customer needs against the continually increasing cybersecurity threats with a robust and comprehensive protection solution, it aims to deliver greater value to customers, while also expanding the domestic information security industry's problem-solving options and enhancing its value.

In the current high-end cybersecurity protection market, many clients can only use products from foreign manufacturers. These products' designs, usage processes, and, most crucially, the sources and processes of samples or policy settings often do not suit the specific requirements of domestic government agencies or enterprises. Therefore, through products and services offered by NetzEngine, enterprises will be helped to safeguard email security.

「Translated content is generated by ChatGPT and is for reference only. Translation date:2024-05-19」

Recommend Cases

這是一張圖片。 This is a picture.
Realizing the dream of unmanned stores, Magpie Life is building the future of the smartphone industry

"The DNA of Magpie Life is not limited to vending machines We believe that vending machines combine technology, access, and humanities to bring us exciting results" This is a sentence on the official website of Magpie Life Let the vending machines bring To live a pleasant life and build a considerate, technological and sustainable future for the smartphone industry is also the original intention of Magpie Life Founded in 2018, Magpie Life launched Taiwan’s first private-brand mobile payment scan code sensor 4 months after its establishment, completing the consumption experience through screen touch The Magpie U1 smart vending machine manages the POS system and gathers data in the background, allowing consumers to synchronize with the world's new retail pace and experience a new retail consumption experience of purchasing convenience, checkout security, visual entertainment, and improved logistics replenishment efficiency Traditional vending machines lack information visibility and AI 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vending machines are less flexible and cannot adapt to changes in consumer preferences Traditional vending machines have shortcomings such as limited change shopping, single payment tools, limited number of products, and few choices Affected by the COVID-19 epidemic, consumption habits have shifted to contactless methods, causing the unmanned store market to heat up Generally, vending machines can only place relatively simple products such as drinks, food, etc The properties available for sale are limited The patented vending machine developed by Magpie can adjust the shelf space and is equipped with a lifting cargo elevator, which is suitable for various types of goods In addition, the machine is equipped with an industrial computer and a large-size touch display screen, which can meet the needs of advertising support at the same time It is expected to move towards a storeless store According to Magpie Life Observation, the consumer market trend in the past two years is that consumers demand convenient life, food consumption patterns value dining experiencesimple and fast, and are equipped with mobile phone-connected ordering models, and hot drinks and Fresh food delivery is the focus of two major trends The location, items sold, consumption methods and multiple payment methods are the focus of market growth for smart vending machines In terms of convenience, Taiwanese consumers still prefer to purchase vending machine food near stations, airports, schools, and businesses in business districts Various payment methods are also gaining more support from consumers, indicating that in the future, automatic Vending machines can be developed in two directions diversified items and diversified payment methods AI sales forecast technology integrates back-end management to achieve precise marketing purposesDue to the wide variety of products, it is difficult to know the performance of products under different factors such as season, market conditions , promotional activities, etc, it is easy to cause out-of-stock or over-inventory situations Magpie Life has specially developed "AI sales forecasting technology" and integrated it into the back-end management system, hoping to lock in customer purchasing preferences and intentions through data analysis In order to achieve the purpose of precise marketing, make accurate business decisions and effectively allocate limited resources The introduction of AI systems can achieve the three major goals of precise marketing, inventory management and supply chain management This system is a replenishment decision-making aid designed specifically for supply chain managers It uses AI to predict future sales demand, helping companies effectively optimize production capacity, inventory and distribution strategies Its overall system architecture includes1 Data exploratory analysis function Provides automatic value filling, automatic coding and automatic feature screening functions for missing values in the data 2 Modeling function 1 Provides model training functions for two types of prediction problems regression Regression and time series Time Series Forecast nbsp2 Supports Auto ML automatic modeling, and the best model is recommended by the system Integrated models can also be established to improve model accuracy nbsp3 Supports multiple algorithm types Random Forest, XGBoost, GBM and other algorithms nbsp4 Supports a variety of time series models exponential smoothing, ARIMA, ARIMAX, intermittent demand, dynamic multiple regression and other models nbsp5 Supports a variety of model evaluation indicators R, MAE, MSE, RMSE, Deviance, AUC, Lift top 1, Misclassification and other indicators nbsp6 Supports automatic cutting of training data sets and Holdout verification data sets, and can manually adjust the ratio nbsp7 Supports automatic model ensemble learning Stacked Ensemble, balancing function learning Balancing Classes, and Early Stopping nbsp8 Supports the creation of multiple models at the same time The system will allocate resources according to modeling needs, so that modeling, prediction and other tasks have independent computing resources and do not affect each other In the overall server space With an upper limit, computing resources can be used efficiently nbsp9 It has in-memory computing function, which can use large-capacity and high-speed memory to perform calculations to avoid reading and writing a large number of files from the hard disk and improve computing performance 3 Data concatenation function Using API grafting and complete data concatenation automation, there is no need to manually import data, improving user experience 4 Chart analysis function Provides visual charts and basic statistical values for product sales AI data analysis solutions have two major advantages 1 Entrepreneurship machines can be rented and sold at low cost to open unmanned physical stores and cooperate with the chain retail industry Through smart machines, entrepreneurs can rent and sell them at a lower cost than the store rent Cost of running a retail business Two cooperation models, machine sales and leasing, are provided, and the choice is based on the evaluation of the industry 2 Various types of products are put on the shelves Products are sold anytime and anywhere 24 hours a day Up to 60 kinds of diversified products can be put on the shelves Large transparent windows enhance the visibility of products Regular replenishment and tracking of product sales status are available, and product types can be adjusted according to needs Recently, the line between the Internet and the physical world has blurred, the way customers interact has changed significantly, and consumer demand is changing and personalized The retail industry is facing unprecedented challenges and uncertainties, and mastering data has become key AI data analysis solutions can help the retail industry quickly activate large amounts of data, create seamless personalized experiences, optimize the operational value chain and improve efficiency, and strengthen the core competitiveness of enterprises 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】哈瑪星科技建構AI模型管理平台 加速AI落地應用
Hamastar Technology Builds an AI Model Management Platform to Accelerate the Application of AI

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Institutional customers still require high level of customization for AI Using the requirements of government Agency A implemented by Hamastar Technology as an example, users must control false information from specific channels The platform needs to provide data ingestion functions for training models and predictions, and can complete natural language processing NLP text classification model training and use When the model discovers false information, it needs to immediately notify responsible personnel through messaging software The need of Agency B is to use an AI model to automatically classify petitions and immediately provide information on past cases as reference for the petitioner or officer Although the project models are similar data ingestion, model prediction, warning notification, the required functions still need to be separately developed for individual projects, and existing programs and models cannot be reused to speed up the implementation of subsequent projects After in-depth discussion, Hamastar Technology found that pain points of enterprises implementing AI projects include high implementation costs and lengthy project schedules It is difficult for a single enterprise to simultaneously have data scientists, analysts, engineers, and designers Current projects are all focused on solving the needs of specific fields, and it is difficult to reuse the AI models in other fields of application At the same time, the tools are concentrated in AI projects and cannot provide customers with total solutions In other words, due to the "limited manpower," "restricted fields," and "insufficient tools" of AI service providers, the implementation of AI technology projects requires high costs or lengthy timelines These are common problems that companies urgently need to solve Therefore, if there is an AI model application service management platform, it will be able to solve the above difficulties and not only reduce costs, but also accelerate project implementation and provide customers with one-stop solutions AI model application service management platform assists in quickly completing projects Therefore, with the support of the AI project of the Industrial Development Bureau, Ministry of Economic Affairs, Hamastar Technology carried out the "AI Model Application Service Management Platform AISP RampD Project" and engaged in the RampD of AISP products The purpose is for AI service providers to complete the AI projects with twice the result using only half the effort The AISP provides one-stop AI solutions AI service providers can quickly assemble required functions, such as data API, model management, and model prediction result monitoring subscription through existing module functions of the AISP It also provides commonly used graphical tools to help companies quickly design interactive charts or dashboards required by users, effectively reducing the labor costs required to execute projects, shortening the solution POC or implementation time, and accelerating the implementation and diffusion of industry AI In terms of product business model, in the short term, the company will extensively invite IT service providers with expertise in the field of AI to work together, and use platform services to solve the AI implementation problems faced by requesting units in various field, gradually building trust in the platform brand In the mid-term, the company hopes to gradually expand the market based on its past success, and form strategic alliances with multiple IT service providers to solve more and wider problems in specialized fields and provide more solutions for units to choose from The platform combines field experts to jointly expand overseas markets In the long term, after establishing AI strategic alliances in various specialized fields, the platform will have a large number of AI solution experts for specialized fields After accumulating a large amount of successful project experience, Hamastar Technology hopes that the AISP will be able to work with experts companies to expand into the international market Harmastar Technology Co, Ltd was formed in 2000 by recruiting numerous senior professional managers and technical experts in related fields It is committed to software technology RampD and services, and aims to develop into an international software company, actively creating opportunities for international cooperation in the industry Under the excellent leadership of its first president, the company has rapidly grown into a major software company in Taiwan

【導入案例】AI嘛會煮咖啡 無人烘豆機靠AI 精準設點與培養忠實客群
AI Can Make Coffee! Autonomous Coffee Roasters Relying on AI for Precise Location Setting and Cultivating Loyal Customers

Have you had your morning coffee yet Over the past decade, Taiwan has gradually formed a coffee drinking culture With the advancement of AI technology, autonomous coffee roasters can now rely on AI for precise location setting while also cultivating a loyal customer base Let's see how this is done According to the International Coffee Organization ICO, Taiwanese consume approximately 285 billion cups of coffee annually, with the coffee market in Taiwan estimated at 80 billion TWD, growing about 20 each year In recent years, the 'drinking coffee' culture in Taiwan has become synonymous with popularity, with coffee being the most frequently chosen daily beverage by 65 of the population Coffee enthusiasts, particularly the more avid ones, are willing to pay more for coffee beans that suit their tastes An increasing number of unmanned drink kiosks have also begun to appear in the Taiwanese beverage market Unmanned coffee beverage shops face difficulties in expanding quickly, primarily due to two major issues one is the appropriateness of customer flow and machine placement locations which still rely on manual analysis the second is penetrating the market of mid to high-end coffee lovers accurately AI resolves two major challenges for autonomous coffee roasters suitable placement and cultivating a loyal customer base To tackle these issues and help autonomous coffee roasters quickly break into the market, Raysharp Electronics intends to implement AI for people flow counting analysis and unfamiliar face recognition These technologies aim to calculate the crowd size at potential roaster locations and classify consumers by gender and age for more precise market analysis They also provide multiple choices for the roasting of raw coffee beans, offering a more customized service tailored to the needs and tastes of professional coffee aficionados with a pack of 'high-quality roasted beans' Since 2018, the rise of unmanned stores has been mainly due to owners wanting to reduce persistently rising rent and personnel costs However, the initial assessment of store locations still requires hourly labor expenses for manual estimation of customer flow, leading to possible miscalculations of both on-site consumers and passerby traffic These inaccuracies may prevent precise real-time analysis of customer flow, or even misguided estimations of operational efficacy after a trial run, thus missing the optimal timing for loss-preventing location retraction Raysharp Electronics introduces autonomous coffee roasters equipped with AI-based people counting analysis and facial recognition Raysharp Electronics combines AI people counting analysis and facial recognition with the coffee trend known as 'black gold', addressing the preferences of numerous coffee connoisseurs in Taiwan who enjoy personally selecting coffee beans at bulk stores and frequenting high-quality grinding cafes or chain coffee shops A new concept for the first autonomous coffee roaster offering choices based on the origin, variety, and roasting methods of coffee beans has emerged AI coffee roasters enhance customer loyalty and materials management efficiency by 20 For the advanced development of autonomous coffee roasters, Raysharp Electronics engineers have equipped the AI NVIDIA development platform on the basis of TCNNFacenet Through AI, tens of thousands of images related to gender and age are used for sample training, allowing even first-time coffee roasting customers to be easily classified using unfamiliar face recognition This gains consumer trust, enhances willingness to use, and allows for recording purchase information and future product recommendations, leading to consumer purchase behavior analysis This information helps owners tailor future material preparation based on consumer preferences for different coffee beans, reducing raw material transportation and storage issues, and improving material management efficiency by 20 Moreover, by placing these autonomous coffee roasters in high-traffic areas, owners can use cameras to capture the crowd and assess whether the machine location has an adequate customer base, quickly analyzing whether to reposition the machines, and more easily targeting the best locations for middle and high-end coffee lovers The unmanned coffee roaster features a professional roasting mode interface, providing options based on the origin and variety of coffee beans, their roasting methods light, medium, deep, and related temperature, wind speed, and timing settings If improvement needs arise during the process, engineers can adjust firmware parameters and also assist in integration with the owner's ordering system Staff members briefly describe the operation of the autonomous coffee roaster 'Black Gold' penetrates deeper into coffee shops, science parks, and commercial buildings through AI This autonomous coffee roaster targets coffee connoisseurs and can be placed in middle to high-end coffee shops to roast more customized coffee beans than those available in bulk stores Upon completing a batch of coffee beans, it immediately provides them to professional technicians within the coffee shops for grinding and manual brewing The remaining roasted beans can also be taken home for brewing and enjoyment It also adds value to coffee shops by better understanding consumer preferences for coffee beans and launching more customer-attracting drink promotions and appropriate inventory management In addition to coffee shops, the autonomous coffee roaster can also utilize AI-based people counting analysis to precisely set up near scientific parks and commercial buildings, offering high-quality coffee beans for office brewing to internal employees with high coffee consumption needs Furthermore, implementing a physical membership system can initiate coffee bean purchase promotions or periodic payment incentives, thus attracting new clients and cultivating existing customer loyalty and retention The operation interface of the smart autonomous coffee roaster「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」