TWI776796B - Financial terminal security system and financial terminal security method - Google Patents
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Abstract
Description
本發明涉及金融技術領域，尤其涉及一種金融終端安全防護方法及系統。The invention relates to the field of financial technology, and in particular, to a method and system for security protection of financial terminals.
目前，透過金融終端進行的犯罪活動越來越猖獗，犯罪分子在金融終端張貼誤導性轉帳資訊、安裝盜卡裝置及攝影機、進行洗錢等一系列金融犯罪活動，現有的ATM機等金融終端，大多配備攝影機進行
現有的金融終端，主要透過以下方式進行安全防護：Existing financial terminals are mainly protected by the following methods:
1、透過攝影機進行
2、透過不間斷的語音提示以及張貼警示說明，提醒使用者注意用卡安全。但是語音提示對使用者的提醒效果有限，也無法解決犯罪分子安裝盜卡裝置及攝影機等惡意犯罪行為。2. Through continuous voice prompts and posting warning instructions, users are reminded to pay attention to card safety. However, the voice prompt has a limited effect on reminding users, and it cannot solve malicious crimes such as the installation of card theft devices and cameras by criminals.
3、透過限制單次交易額度以及每日最高交易額度，以降低風險。但是限制交易額度交易次數，對於正常用卡的持卡人帶來不便。3. Reduce risks by limiting the single transaction amount and the daily maximum transaction amount. However, the number of transactions within the transaction limit is limited, which brings inconvenience to the cardholders who use the card normally.
本發明實施例的主要目的在於提出一種金融終端安全防護方法及系統，透過對使用者行為的自動監控分析，區分正常金融交易使用者與可疑犯罪分子，並提供報警以及即時風險處理功能，以保障金融終端交易安全。The main purpose of the embodiments of the present invention is to provide a financial terminal security protection method and system, through automatic monitoring and analysis of user behavior, distinguish normal financial transaction users and suspicious criminals, and provide alarm and real-time risk processing functions to protect Financial terminal transaction security.
為實現上述目的，本發明提供了一種金融終端安全防護系統，包含：金融終端、使用者行為追蹤單元、使用者行為分析單元、使用者行為模式資料庫以及事件處理單元；其中該使用者行為模式資料庫係用於從大量的終端交易操作行為中編制使用者交易行為模式案例，並將使用者交易行為模式案例進行儲存，該使用者行為模式案例包含正常交易行為以及異常交易行為。該使用者行為追蹤單元係用於獲取使用者在該金融終端上的交易操作行為資訊來產生交易事件消息，並傳輸至該使用者行為分析單元。該使用者行為分析單元係用於對該交易事件消息與該使用者行為模式資料庫儲存的使用者行為模式案例進行匹配，以判斷交易事件消息是正常交易行為模式還是異常交易行為模式，並將判斷結果發送至該事件處理單元。該事件處理單元係用於根據該判斷結果進行相應的交易行為處理。In order to achieve the above purpose, the present invention provides a financial terminal security protection system, comprising: a financial terminal, a user behavior tracking unit, a user behavior analysis unit, a user behavior pattern database and an event processing unit; wherein the user behavior pattern The database is used to compile user transaction behavior pattern cases from a large number of terminal transaction operation behaviors, and store the user transaction behavior pattern cases. The user behavior pattern cases include normal transaction behaviors and abnormal transaction behaviors. The user behavior tracking unit is used to obtain the user's transaction operation behavior information on the financial terminal to generate transaction event messages, and transmit the information to the user behavior analysis unit. The user behavior analysis unit is used to match the transaction event message with the user behavior pattern cases stored in the user behavior pattern database, so as to determine whether the transaction event message is a normal transaction behavior pattern or an abnormal transaction behavior pattern, and analyze The judgment result is sent to the event processing unit. The event processing unit is used to perform corresponding transaction behavior processing according to the judgment result.
根據本發明的一實施例，該使用者行為追蹤單元包含虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組、機台操作追蹤模組以及交易處理追蹤模組，其中：該虹膜焦點識別追蹤模組係用於透過視頻攝影機來採集使用者的虹膜焦點，以實現對視覺焦點的追蹤；該視頻圖像識別追蹤模組係用於透過視頻攝影機來採集使用者操作的視頻圖像資料；該機台操作追蹤模組係用於追蹤金融終端的使用者操作；以及該交易處理追蹤模組係用於追蹤交易處理系統的交易處理環節。According to an embodiment of the present invention, the user behavior tracking unit includes an iris focus recognition tracking module, a video image recognition tracking module, a machine operation tracking module and a transaction processing tracking module, wherein: the iris focus recognition tracking module The module is used to collect the user's iris focus through a video camera, so as to realize the tracking of the visual focus; the video image recognition tracking module is used to collect the video image data of the user's operation through the video camera; the The machine operation tracking module is used for tracking user operations of the financial terminal; and the transaction processing tracking module is used for tracking the transaction processing links of the transaction processing system.
根據本發明的另一實施例，該使用者行為分析單元對該交易事件消息、發送時間序列以及交易金額進行分析，在該使用者行為模式資料庫中進行匹配，以及區分正常交易行為以及異常交易行為。According to another embodiment of the present invention, the user behavior analysis unit analyzes the transaction event message, the sending time series and the transaction amount, performs matching in the user behavior pattern database, and distinguishes between normal transaction behavior and abnormal transaction Behavior.
根據本發明的另一實施例，該事件處理單元包含正常交易行為處理模組以及異常交易行為處理模組，其中：該正常交易行為處理模組係用於支援金融交易終端發起的金融交易的幕後處理；以及該異常交易行為處理模組係用於對異常交易行為進行終止處理，並進行系統報警，並且提供異常交易行為的查詢以及處理記錄。According to another embodiment of the present invention, the event processing unit includes a normal transaction behavior processing module and an abnormal transaction behavior processing module, wherein: the normal transaction behavior processing module is used to support the background of the financial transaction initiated by the financial transaction terminal processing; and the abnormal transaction behavior processing module is used for terminating abnormal transaction behavior, making a system alarm, and providing query and processing records of abnormal transaction behavior.
為實現上述目的，本發明還對應地提供了一種金融終端安全防護方法，包含：從大量的終端交易操作行為中編制使用者交易行為模式案例，並將使用者交易行為模式案例進行儲存，該使用者行為模式案例包含正常交易行為以及異常交易行為；獲取使用者在該金融終端上的交易操作行為資訊，以產生交易事件消息；對該交易事件消息與該使用者行為模式案例進行匹配，以判斷交易事件消息是正常交易行為模式還是異常交易行為模式，並將判斷結果發送至該事件處理單元；根據該判斷結果進行相應的交易行為處理。In order to achieve the above object, the present invention also provides a financial terminal security protection method correspondingly, comprising: compiling user transaction behavior pattern cases from a large number of terminal transaction operation behaviors, and storing the user transaction behavior pattern cases, and using Cases of user behavior patterns include normal transaction behaviors and abnormal transaction behaviors; obtain information on the user's transaction operation behavior on the financial terminal to generate transaction event messages; match the transaction event messages with the user behavior pattern cases to determine Whether the transaction event message is a normal transaction behavior mode or an abnormal transaction behavior mode, the judgment result is sent to the event processing unit; the corresponding transaction behavior processing is performed according to the judgment result.
根據本發明的一實施例，獲取使用者在該金融終端上的交易操作行為資訊的步驟包含：透過視頻攝影機來採集使用者的虹膜焦點，以實現對視覺焦點的追蹤；透過視頻攝影機來採集使用者操作的視頻圖像資料；追蹤金融終端的使用者操作；以及追蹤交易處理系統的交易處理環節。According to an embodiment of the present invention, the step of acquiring the user's transaction operation behavior information on the financial terminal includes: collecting the user's iris focus through a video camera to track the visual focus; video image data of the operator's operation; tracking the user operation of the financial terminal; and tracking the transaction processing link of the transaction processing system.
根據本發明的另一實施例，判斷交易事件消息是正常交易行為模式還是異常交易行為模式的步驟包含：對該交易事件消息、發送時間序列以及交易金額進行分析，利用分析結果與儲存的該使用者行為模式案例進行匹配，以及區分正常交易行為以及異常交易行為。According to another embodiment of the present invention, the step of judging whether the transaction event message is a normal transaction behavior mode or an abnormal transaction behavior mode includes: analyzing the transaction event message, the sending time series and the transaction amount, and using the analysis result and the stored usage Matching cases of user behavior patterns, as well as distinguishing between normal transaction behavior and abnormal transaction behavior.
根據本發明的另一實施例，根據該判斷結果進行相應的交易行為處理的步驟包含：當交易事件消息是正常交易行為模式時，支援金融交易終端發起的金融交易的幕後處理；否則，對異常交易行為進行終止處理，並進行系統報警；同時，提供異常交易行為的查詢以及處理記錄。According to another embodiment of the present invention, the step of performing corresponding transaction behavior processing according to the judgment result includes: when the transaction event message is a normal transaction behavior mode, supporting the behind-the-scenes processing of the financial transaction initiated by the financial transaction terminal; The transaction behavior is terminated, and the system alarms; at the same time, the query and processing records of abnormal transaction behavior are provided.
上述技術方案實現了以及有益效果：The above technical solutions have achieved and beneficial effects:
本技術方案透過虹膜識別技術、視頻圖像識別技術，匹配金融終端操作的正常行為模式以及異常行為模式，並對異常交易行為進行追蹤處理，能夠確保金融終端安全，以及避免/減輕犯罪份子的違法行為而造成使用者在金錢上的損失。This technical solution uses iris recognition technology and video image recognition technology to match the normal behavior patterns and abnormal behavior patterns of financial terminal operations, and to track abnormal transaction behaviors, so as to ensure the safety of financial terminals and avoid/reduce criminals from breaking the law. behavior and cause the user to lose money.
以下將結合本發明實施例中的附圖，對本發明實施例中的技術方案進行清楚、完整地描述，值得注意的是，所舉出的實施例僅為本發明一部分實施方式，而不是所有的實施方式。基於本發明中的實施例，本領域通常知識者所做出的修改/修飾皆屬於本發明的範疇。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is worth noting that the cited embodiments are only a part of implementations of the present invention, not all of them. implementation. Based on the embodiments of the present invention, modifications/modifications made by those skilled in the art all belong to the scope of the present invention.
第1圖係為本發明實施例提出的一種金融終端安全防護系統功能框圖，包含有：金融終端101、使用者行為追蹤單元102、使用者行為分析單元103、使用者行為模式資料庫104以及事件處理單元105。FIG. 1 is a functional block diagram of a financial terminal security protection system proposed by an embodiment of the present invention, including: a
使用者行為模式資料庫104係用於從大量的終端交易操作行為中編制使用者交易行為模式案例，並將使用者交易行為模式案例進行儲存，其中該使用者行為模式案例包含正常交易行為以及異常交易行為。The user
使用者行為追蹤單元102係用於獲取使用者在該金融終端101上的交易操作行為資訊，以產生交易事件消息，並將交易事件消息傳輸至使用者行為分析單元103。The user
使用者行為分析單元103係用於對該交易事件消息與該使用者行為模式資料庫儲存的使用者行為模式案例進行匹配，以判斷交易事件消息是正常交易行為模式或是異常交易行為模式，並且將判斷結果發送至事件處理單元105，其中事件處理單元105係用於根據該判斷結果進行相應的交易行為處理。The user
本系統透過對使用者行為的自動監控分析、區分正常金融交易使用者與可疑犯罪分子，並提供報警以及即時風險處理功能，以保障金融終端交易安全。Through automatic monitoring and analysis of user behavior, the system distinguishes normal financial transaction users from suspicious criminals, and provides alarm and real-time risk processing functions to ensure the safety of financial terminal transactions.
第2圖係為本實施例的系統示意圖，包含有：金融終端（諸如ATM機台）、使用者行為追蹤單元（包含虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組、機台操作追蹤模組以及交易處理追蹤模組）、使用者行為分析單元、使用者行為模式資料庫、事件處理單元以及交易處理系統。FIG. 2 is a schematic diagram of the system of this embodiment, including: a financial terminal (such as an ATM machine), a user behavior tracking unit (including an iris focus recognition tracking module, a video image recognition tracking module, and a machine operation tracking module) module and transaction processing tracking module), user behavior analysis unit, user behavior pattern database, event processing unit and transaction processing system.
金融終端（諸如ATM機）：需要對傳統的金融機台進行必要的改造，以支援將圖像資料、機台運算資料發送到幕後處理系統。Financial terminals (such as ATM machines): It is necessary to make necessary modifications to traditional financial machines to support the sending of image data and machine computing data to the behind-the-scenes processing system.
使用者行為追蹤單元用於負責對使用者的交易操作行為進行識別以及追蹤，並且包含有虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組、機台操作追蹤模組以及交易處理追蹤模組，其中：The user behavior tracking unit is used to identify and track the user's transaction operation behavior, and includes an iris focus recognition tracking module, a video image recognition tracking module, a machine operation tracking module, and a transaction processing tracking module. ,in:
虹膜焦點識別追蹤模組，用以透過視頻攝影機來採集使用者的虹膜焦點，以實現對視覺焦點的追蹤，其中，在正常的金融終端交易下，使用者的視覺焦點會有相對固定的模式；The iris focus recognition and tracking module is used to collect the user's iris focus through a video camera to realize the tracking of the visual focus. In the normal financial terminal transaction, the user's visual focus will have a relatively fixed pattern;
視頻圖像識別追蹤模組，用以透過視頻攝影機來採集使用者操作的視頻圖像資料（例如使用者手部操作、使用者的攜帶工具等）；Video image recognition and tracking module, which is used to collect video image data (such as user's hand operation, user's carrying tool, etc.) through video cameras;
對於虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組來說，虹膜焦點識別追蹤模組以及視頻圖像識別追蹤模組均透過攝影機進行即時圖像以及視頻採集，並對圖像以及視頻進行即時分析以及處理，延時僅為秒級，可以保證即時性。For the iris focus recognition tracking module and the video image recognition tracking module, the iris focus recognition tracking module and the video image recognition tracking module both collect real-time images and videos through cameras, and perform Real-time analysis and processing, with a delay of only seconds, can ensure immediacy.
虹膜焦點識別追蹤以一定週期（例如0.5秒）進行圖像採樣，並對採樣圖像進行眼球追蹤分析。為了提高識別精度，可以採用紅外線投射方式，主動投射紅外線等光束到虹膜來提取特徵。具體步驟依序包含：The iris focus recognition tracking performs image sampling at a certain period (for example, 0.5 seconds), and performs eye tracking analysis on the sampled images. In order to improve the recognition accuracy, infrared projection method can be used to actively project infrared light beams to the iris to extract features. The specific steps include:
採集眼部圖像、圖像預處理、虹膜及瞳孔檢測、虹膜及瞳孔定位、虹膜角度變化及視線方向計算，以及觸發事件消息。Collect eye images, image preprocessing, iris and pupil detection, iris and pupil positioning, iris angle change and gaze direction calculation, and trigger event messages.
機台操作追蹤模組：追蹤金融機台的使用者操作，如：插卡、鍵盤輸入、吐鈔等。正常的金融終端操作，有其相對固定的機台操作次序模式；Machine operation tracking module: Track user operations of financial machines, such as: card insertion, keyboard input, cash out, etc. The normal financial terminal operation has its relatively fixed machine operation sequence mode;
交易處理追蹤模組：追蹤交易處理系統的交易處理環節，如：取款操作的金額、卡號等資訊；Transaction processing tracking module: Track the transaction processing links of the transaction processing system, such as: the amount of the withdrawal operation, card number and other information;
對於使用者行為分析單元來說，根據使用者行為追蹤單元提供的資料，進行使用者行為的綜合分析，匹配正常交易行為模式以及異常交易行為模式，並提交事件處理模組進行後續處理。實作方式可例如是：使用者行為（例如取款）的每一操作步驟，都相應會觸發虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組、機台操作追蹤模組以及交易處理追蹤模組，產生交易事件消息，並提交給使用者行為分析模組。使用者行為分析模組針對交易事件消息的類型、發生時間序列以及交易金額等進行分析，在使用者行為模式資料庫中進行匹配，區分正常交易行為以及異常交易行為，並相應進行後續處理（例如報警、終止交易）。For the user behavior analysis unit, according to the data provided by the user behavior tracking unit, a comprehensive analysis of user behavior is performed, matching normal transaction behavior patterns and abnormal transaction behavior patterns, and then submitted to the event processing module for subsequent processing. The implementation method can be, for example, that each operation step of user behavior (such as withdrawing money) will trigger the iris focus recognition tracking module, video image recognition tracking module, machine operation tracking module and transaction processing tracking module accordingly. group, generate transaction event messages, and submit them to the user behavior analysis module. The user behavior analysis module analyzes the type of transaction event message, the time series of occurrence and the transaction amount, etc., matches in the user behavior pattern database, distinguishes between normal transaction behavior and abnormal transaction behavior, and conducts follow-up processing accordingly (for example, alarm, terminate the transaction).
對於本實施例來說，使用者行為模式資料庫分為正常交易行為模式資料庫以及異常行為模式資料庫。使用者行為模式資料庫的建立過程包含：For this embodiment, the user behavior pattern database is divided into a normal transaction behavior pattern database and an abnormal behavior pattern database. The creation process of the user behavior pattern database includes:
首先，初始使用者行為模式資料庫建立。實作方式可例如是：First, an initial user behavior pattern database is created. This can be implemented, for example:
根據對常見的正常交易行為（例如取款）、常見的異常交易行為（例如非法安裝盜卡裝置）進行交易流程分析，編制使用者行為模式案例，形成初始使用者行為模式資料庫；According to the transaction process analysis of common normal transaction behaviors (such as withdrawals) and common abnormal transaction behaviors (such as illegal installation of stolen card devices), compile user behavior pattern cases, and form an initial user behavior pattern database;
接著，使用者行為模式驗證。實作方式可例如是：Next, user behavior pattern verification. This can be implemented, for example:
透過實際的使用者操作，對初始使用者行為模式資料庫進行驗證，並根據驗證結果調整模式資料庫；Through the actual user operation, verify the initial user behavior pattern database, and adjust the pattern database according to the verification result;
最後，使用者行為模式擴充。實作方式可例如是：Finally, the user behavior pattern is expanded. This can be implemented, for example:
根據實際發生的新型正常或異常交易，對應分析以及設計新的使用者行為模式，補充到使用者行為模式資料庫。According to the actual occurrence of new normal or abnormal transactions, corresponding analysis and design of new user behavior patterns, supplemented to the user behavior pattern database.
對於事件處理單元來說，用於負責交易行為的處理，可包含：For the event processing unit, which is responsible for the processing of transaction behavior, it can include:
當交易事件消息是正常交易行為模式時，支援金融交易終端發起的金融交易的幕後處理；When the transaction event message is a normal transaction behavior pattern, support the behind-the-scenes processing of financial transactions initiated by the financial transaction terminal;
否則，對於高風險異常行為，進行即時的交易處理，如：終止當前交易、停止金融機台服務等；對異常交易行為透過警報、短信等途徑進行報警；同時，為系統監控人員提供異常交易行為的查詢以及處理記錄功能。Otherwise, for high-risk abnormal behaviors, conduct real-time transaction processing, such as: terminating current transactions, stopping financial machine services, etc.; alarming abnormal transaction behaviors through alarms, text messages, etc.; at the same time, providing system monitoring personnel with abnormal transaction behaviors query and processing records.
如第3圖所示，為本發明實施例提出的一種金融終端安全防護方法流程圖，包含以下步驟：As shown in FIG. 3, it is a flowchart of a financial terminal security protection method proposed by an embodiment of the present invention, including the following steps:
步驟301：從大量的終端交易操作行為中編制使用者交易行為模式案例，並將使用者交易行為模式案例進行儲存，其中該使用者行為模式案例包含正常交易行為以及異常交易行為；Step 301 : compile a user transaction behavior pattern case from a large number of terminal transaction operation behaviors, and store the user transaction behavior pattern case, wherein the user behavior pattern case includes normal transaction behavior and abnormal transaction behavior;
步驟302：獲取使用者在該金融終端上的交易操作行為資訊，以產生交易事件消息；Step 302: Acquire the user's transaction operation behavior information on the financial terminal to generate a transaction event message;
步驟303：對該交易事件消息與該使用者行為模式案例進行匹配，以判斷交易事件消息是正常交易行為模式還是異常交易行為模式，並將判斷結果發送至該事件處理單元；Step 303: Match the transaction event message with the user behavior pattern case to determine whether the transaction event message is a normal transaction behavior pattern or an abnormal transaction behavior pattern, and send the judgment result to the event processing unit;
步驟304：根據該判斷結果進行相應的交易行為處理。Step 304: Perform corresponding transaction behavior processing according to the judgment result.
根據上述金融終端安全防護方法流程，以下係基於第2圖的系統來描述正常的銀行卡取款交易流程如下：According to the process of the above-mentioned financial terminal security protection method, the following is based on the system in Figure 2 to describe the normal bank card withdrawal transaction process as follows:
1、使用者到達取款機：虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組追蹤到使用者進入。1. The user arrives at the ATM: the iris focus recognition tracking module and the video image recognition tracking module track the user's entry.
2、插卡：虹膜焦點識別追蹤模組追蹤到使用者的虹膜焦點集中到ATM機插卡槽，視頻圖像識別追蹤模組追蹤到使用者插卡操作，機台操作追蹤模組監控到插卡操作；2. Card insertion: The iris focus recognition tracking module tracks the user's iris focus to the ATM card slot, the video image recognition tracking module tracks the user's card insertion operation, and the machine operation tracking module monitors the insertion operation. card operation;
3、螢幕輸入：虹膜焦點識別追蹤模組追蹤到使用者的虹膜焦點集中到ATM機螢幕，視頻圖像識別追蹤模組追蹤到使用者螢幕輸入操作，機台操作追蹤模組監控到螢幕輸入操作；3. Screen input: The iris focus recognition tracking module tracks the user's iris focus to the ATM screen, the video image recognition tracking module tracks the user's screen input operation, and the machine operation tracking module monitors the screen input operation ;
4、密碼鍵盤輸入：虹膜焦點識別追蹤模組追蹤到使用者的虹膜焦點集中到密碼鍵盤，視頻圖像識別追蹤模組追蹤到使用者密碼鍵盤操作，機台操作追蹤模組監控到密碼鍵盤操作；4. Password keyboard input: The iris focus recognition tracking module tracks the user's iris focus to the password keyboard, the video image recognition tracking module tracks the user's password keyboard operation, and the machine operation tracking module monitors the password keyboard operation. ;
5、交易發送幕後處理：交易處理追蹤模組監控到取款交易提交以及系統返回。5. Behind-the-scenes processing of transaction sending: The transaction processing tracking module monitors the withdrawal transaction submission and system return.
6、吐鈔：機台操作追蹤模組監控到機台吐鈔操作，虹膜焦點識別追蹤模組追蹤到使用者的虹膜焦點集中到吐鈔口，視頻圖像識別追蹤模組追蹤到使用者取鈔動作；6. Cash-out: The machine operation tracking module monitors the machine's cash-out operation, the iris focus recognition and tracking module tracks the user's iris focus to the cash-out port, and the video image recognition and tracking module tracks the user's withdrawal. banknote action;
7、取卡：機台操作追蹤模組監控到機台吐卡操作，虹膜焦點識別追蹤模組追蹤到使用者的虹膜焦點集中到ATM機插卡槽，視頻圖像識別追蹤模組追蹤到使用者取卡操作；7. Card removal: The machine operation tracking module monitors the machine spit card operation, the iris focus recognition tracking module tracks the user's iris focus to the ATM card slot, and the video image recognition tracking module tracks the use of card-taking operation;
8、離開取款機：虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組追蹤到使用者離開。8. Leaving the ATM: The iris focus recognition tracking module and the video image recognition tracking module track the user's departure.
9、行為分析：使用者行為分析單元進行使用者行為的綜合分析，匹配使用者行為模式資料庫，識別出正常交易行為模式，無需任何後續處理。9. Behavior analysis: The user behavior analysis unit conducts a comprehensive analysis of user behavior, matches the user behavior pattern database, and identifies normal transaction behavior patterns without any follow-up processing.
以下將基於第2圖所示的系統框圖來描述異常操作行為，該操作行為是犯罪分子在ATM機插卡槽安裝盜卡裝置。具體流程為：The following will describe the abnormal operation behavior based on the system block diagram shown in FIG. 2 , and the operation behavior is that the criminal installs the card stealing device in the card slot of the ATM machine. The specific process is:
1、犯罪分子到達取款機：虹膜焦點識別追蹤模組、視頻圖像識別追蹤模組可能會追蹤到犯罪分子左右查看是否有人員。1. Criminals arrive at the ATM: The iris focus recognition tracking module and the video image recognition tracking module may track the criminals to see if there are people around.
2、犯罪分子安裝盜卡裝置：虹膜焦點識別追蹤模組追蹤到犯罪分子的虹膜焦點長時間集中到ATM機插卡槽，視頻圖像識別追蹤模組追蹤到犯罪分子取出盜卡裝置、手部長時間停留在ATM機插卡槽，同時機台操作追蹤模組未監控到任何插卡操作、交易處理追蹤模組未監控到任何交易操作；2. Criminals install card theft devices: The iris focus recognition tracking module tracks the criminals' iris focus to the ATM card slot for a long time, and the video image recognition tracking module tracks the criminals to take out the stolen card device and the length of their hands. The time stays in the card slot of the ATM machine, and at the same time, the machine operation tracking module does not monitor any card insertion operations, and the transaction processing tracking module does not monitor any transaction operations;
3、犯罪分子檢查盜卡裝置工作情況：犯罪分子***測試用卡，檢查盜卡裝置是否正常。虹膜焦點識別追蹤模組追蹤到犯罪分子的虹膜焦點長時間集中到ATM機插卡槽，視頻圖像識別追蹤模組追蹤到犯罪分子插卡操作，機台操作追蹤模組監控到插卡口異常、交易處理追蹤模組未監控到任何交易操作；3. Criminals check the working condition of the card theft device: The criminals insert the test card to check whether the card theft device is normal. The iris focus recognition and tracking module tracked the iris focus of criminals to the ATM card slot for a long time, the video image recognition tracking module tracked the criminal's card insertion operation, and the machine operation tracking module monitored the abnormal card slot. , The transaction processing tracking module does not monitor any transaction operations;
4、行為分析：使用者行為分析單元進行使用者行為的綜合分析，匹配使用者行為模式資料庫，識別出異常行為模式；4. Behavior analysis: The user behavior analysis unit conducts a comprehensive analysis of user behavior, matches the user behavior pattern database, and identifies abnormal behavior patterns;
5、事件處理：時間處理單元暫停發生可疑事件的ATM機任何操作，透過警報、短信等途徑進行報警，系統監控以及維護人員對問題機台進行檢查以及跟進處理。5. Event processing: The time processing unit suspends any operation of the ATM machine with suspicious events, and sends an alarm through alarms, text messages, etc., and the system monitoring and maintenance personnel check and follow up on the problem machine.
進一步地，當嫌疑人帶上鴨舌帽等，資訊採集終端無法採集到虹膜焦點以及圖像，虹膜焦點識別追蹤模組無法正常採集到虹膜及眼球資料，這本身就是一個異常事件。視頻圖像識別追蹤模組如果可以分析到嫌疑人蒙面等異常行為，也可以提供異常事件。Furthermore, when the suspect wears a cap, etc., the information collection terminal cannot collect the iris focus and images, and the iris focus recognition and tracking module cannot normally collect the iris and eyeball data, which is an abnormal event in itself. If the video image recognition tracking module can analyze abnormal behaviors such as masking of suspects, it can also provide abnormal events.
本發明的技術方案匹配正常的金融終端操作行為模式以及異常行為模式，並對異常交易行為進行追蹤處理，能夠確保金融終端安全，以及避免/減輕犯罪分子的違法行為而造成使用者在金錢上的損失。 以上所述僅為本發明之較佳實施例，凡依本發明申請專利範圍所做之均等變化與修飾，皆應屬本發明之涵蓋範圍。The technical solution of the present invention matches normal financial terminal operation behavior patterns and abnormal behavior patterns, and tracks abnormal transaction behaviors, which can ensure the safety of financial terminals, and avoid/mitigate the illegal behavior of criminals and cause users to lose money in money. loss. The above descriptions are only preferred embodiments of the present invention, and all equivalent changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope of the present invention.
101‧‧‧金融終端102‧‧‧使用者行為追蹤單元103‧‧‧使用者行為分析單元104‧‧‧使用者行為模式資料庫105‧‧‧事件處理單元301～304‧‧‧步驟101‧‧‧
第1圖係為本發明實施例提出的一種金融終端安全防護系統功能框圖。 第2圖係為本實施例的系統示意圖。 第3圖係為本發明實施例提出的一種金融終端安全防護方法流程圖。FIG. 1 is a functional block diagram of a financial terminal security protection system proposed by an embodiment of the present invention. FIG. 2 is a schematic diagram of the system of this embodiment. FIG. 3 is a flowchart of a financial terminal security protection method proposed by an embodiment of the present invention.
301~304‧‧‧步驟 301~304‧‧‧Steps
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Also Published As
| Publication number | Publication date |
|---|---|
| CN105957271A (en) | 2016-09-21 |
| TW201723967A (en) | 2017-07-01 |
| WO2017107734A1 (en) | 2017-06-29 |
| CN105957271B (en) | 2018-12-28 |
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