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As passenger demand and routes grow, challenges like seat hoarding and malicious web scraping have emerged. Such activities disrupt normal flight operations, cause economic losses, and negatively impact user experiences. To address these issues, Sichuan Airlines implemented Dingxiang's aviation anti-crawling solution. The solution offers robust protection for ticketing information on B2C websites and official apps by detecting and preventing unauthorized data extraction. Its key features include: atbCAPTCHA: Real-time detection and interception of malicious accounts and bot activities during user registration, login, and searches. Device Fingerprinting: Continuous monitoring to identify and mitigate risks like code injection, emulators, and jailbroken devices, ensuring system stability. Dinsight Real-Time Decision Engine: Behavior-based analysis to identify potential threats, securing all transactions. #aviation #Antifraud  #Dingxiang  #atbCAPTCHA #Anticrawle https://lnkd.in/gNfwjEbw

Happy New Year 2025! https://lnkd.in/g5WgwS3v #2025 #NewYear #DEEPFAKE #AI  #Antifraud  #Dingxiang 

To further safeguard the App's security, Soul has chosen to use Dingxiang App Hardening to enhance platform security, protect user privacy, and ensure compliance with regulatory requirements. First, App hardening enhances the app's ability to resist attacks, preventing hackers from intruding, tampering, or reverse engineering, thereby ensuring the security of user data. Second, Soul uses hardening technology to protect its anti-fraud features, preventing fraudsters from bypassing protective mechanisms and ensuring the effectiveness of fake identity and online scam prevention. Furthermore, App hardening strengthens data encryption and access control, ensuring that user privacy remains protected and improving platform security and user trust. Additionally, Soul App needs to comply with China’s Cybersecurity Law and Data Security Law, and App hardening helps meet these compliance requirements. #voicecloning #DEEPFAKE #AI  #Antifraud  #Dingxiang https://lnkd.in/gPd_w-Z8

Recently, a video posted by an account named “Ban Hua XXX” showed a well-known doctor, Zhang Wenhong, promoting a protein bar. However, media investigations revealed that while the lip movements and voice in the video resembled Zhang Wenhong’s, the promotion was not done by him. The video was confirmed to be a deepfake, created using AI technology. Screenshots from users indicated that 1,266 units of the protein bar had been sold. Zhang Wenhong later told the media that there were multiple such fraudulent accounts, which frequently changed, making it challenging to report them. Zhang Wenhong said, “I’ve considered reporting this to the police, but it’s hard to describe an invisible and intangible perpetrator who changes accounts daily and uses only virtual tools. Who can I report? I think this is a violation of consumer rights and should be handled by the relevant authorities.” #voicecloning #DEEPFAKE #AI  #Antifraud  #Dingxiang https://lnkd.in/g_U_kvFG

Merry Christmas！ https://lnkd.in/g5WgwS3v

Mr. Li received a text message claiming to be from his workplace leader, asking him to add a social media account for further communication. After becoming "friends," the fraudster requested an urgent transfer of funds, claiming it was needed for financial turnover, with a promise of repayment later. Initially doubtful, Mr. Li was convinced when the scammer initiated a video call. The person in the video appeared to be his “leader,” which made Mr. Li lower his guard. He then made three separate transfers totaling 950,000 yuan. Later that day, during a conversation with friends, Mr. Li found the situation suspicious and decided to report it to the police. After receiving his report, the police quickly coordinated with the bank to freeze the involved funds through emergency measures, successfully recovering 830,000 yuan and preventing greater losses. Thanks to the swift action of the authorities, most of Mr. Li’s money was retrieved. In Another Case, an Elderly Woman Is Scammed by AI Voice Cloning。Ms. Li received a call from someone claiming to be her "younger brother." The caller stated that he had changed his phone number and asked her to add him on WeChat, promising to visit her soon. A few days later, the "brother" called again, claiming he was detained after a fight and needed money for compensation. He asked Ms. Li for financial assistance. Believing the story, she prepared 70,000 yuan in cash. The scammer then requested an additional 50,000 yuan. Though Ms. Li began to feel suspicious, she still decided to report the incident to the police. #voicecloning #DEEPFAKE #AI  #Antifraud  #Dingxiang https://lnkd.in/g9RQV2aY

The core objective of AIGC audio detection technology is to improve accuracy and reliability in the face of continuously advancing audio forgery techniques, focusing on audio quality, voiceprint features, and spectrum analysis.  **Audio Quality:** Forged audio often exhibits quality anomalies, such as noise, distortion, or other imperfections that affect clarity. Since the process of generating synthetic audio typically introduces these unnatural elements, they serve as important clues for detecting fake audio.  **Voiceprint Features:** Each person’s unique vocal characteristics, shaped by their physiological traits like vocal cord structure and speaking habits, create distinct voiceprints. AIGC-generated audio often lacks the personalized nuances of human speech, tending to be overly regular and mechanical in aspects like tone and pitch, which forms the basis for voiceprint detection.  **Spectrum Analysis:** Spectrum analysis converts audio signals from the time domain to the frequency domain to examine frequency components. In audio forgery detection, AIGC-generated audio often exhibits unnatural features in high or low-frequency ranges, such as irregular frequency distribution. These anomalies can be revealed through spectrogram analysis.  AIGC audio detection technology combines multi-level feature fusion, adversarial training, and temporal modeling to maintain high-precision detection performance even in the face of various generation techniques and complex noise interference. Looking ahead, the integration of multimodal information and more advanced deep learning technologies is expected to further improve the detection of forged audio. #voicecloning #DEEPFAKE #AI  #Antifraud  #Dingxiang The primary task of AIGC image forgery detection is to determine whether an image was generated or tampered with by artificial intelligence. Evidence of forgery is typically reflected in visual artifacts, digital signal anomalies, model fingerprints, facial priors, and violations of physical imaging principles.  https://lnkd.in/gbFbs9GN

The rapid development of AIGC technology has brought unprecedented security risks to identity verification systems in the financial industry. Especially in widely used remote facial recognition and voiceprint recognition systems, black and gray markets have leveraged AIGC tools to carry out "face-swapping" and "voice-cloning" attacks, which have become a serious threat. **AIGC "Face-Swapping" Attack:**   Remote facial recognition systems are widely used in various financial services, such as account opening, credit card applications, and claims processing, as an identity verification method to ensure user security. The system workflow includes multiple steps such as face data collection, liveness detection, quality testing, and face comparison. However, black and gray market actors can easily create fake videos using AIGC tools. By customizing client ROMs or hijacking cameras, they inject counterfeit victim videos into the client during the face collection process. Through forged actions such as "blinking" and "shaking head," they bypass liveness detection, thus overcoming identity verification measures and launching an attack. **AIGC "Voice-Cloning" Attack:**   Voiceprint recognition systems, as another identity verification method, also face challenges from AIGC. Voiceprint recognition works by collecting users' voice information and analyzing their voiceprint features to verify identity, commonly used in telephone banking and mobile financial services. Black and gray market actors can acquire victim voice samples, such as recordings from phone scams, and use AIGC tools to generate counterfeit audio. During the voice collection process, attackers can play back the fake audio to bypass the voiceprint comparison system, successfully launching an identity verification attack. Both of these AIGC attack methods share a common characteristic: attackers use AIGC technology to generate highly realistic fake audio-video content, enabling them to carry out fraud without traditional identity verification methods. As AIGC technology continues to evolve, financial institutions urgently need to strengthen anti-fraud technologies, enhance system security, and adopt more stringent detection and prevention measures to ensure accurate and secure customer identity verification, thus addressing increasingly complex cybersecurity challenges. #voicecloning #DEEPFAKE #AI  #Antifraud  #Dingxiang https://lnkd.in/g9ZNPjYQ

Recently, the **"Digital Intelligence Driven, Open Win-Win: Fintech Empowering High-Quality Financial Development"** forum was held in Shanghai, hosted by the Bank of Communications. Over 200 guests from government agencies, financial institutions, and technology enterprises attended the event, focusing on the deep integration of artificial intelligence and data elements. Discussions centered on AI large model applications in the financial sector, exploring fintech development trends and practical opportunities, providing clear directions and strategic recommendations for the industry's future. **Qian Bin**, a Party Committee member and Vice President of the Bank of Communications, delivered a keynote speech at the forum. At the event, the **"White Paper on Financial AIGC Audio-Video Anti-Fraud"** was unveiled. Jointly authored by the Bank of Communications, Dingxiang Technology, and RealAI, the white paper systematically discusses the risk challenges brought by AIGC technology applications, focusing on audio-video fraud issues in the financial industry. It provides references to help financial institutions enhance their capabilities in identifying and preventing AIGC-related fraud. **Li Zhaoning**, General Manager of the Bank of Communications’ Network Finance Department and Director of the Fintech Innovation Research Institute, gave an in-depth explanation of the white paper during the forum. #App #DEEPFAKE #voicecloning #AI  #Antifraud  #Dingxiang https://lnkd.in/gjgSKVjH

Mr. Zhang, a septuagenarian, has been living alone since his wife passed away years ago. His son works abroad and rarely visits. One day, Mr. Zhang received a call from an unfamiliar number. The voice on the other end was unmistakably that of his son. "Dad, I’m in trouble overseas and need money to resolve the issue," the voice said, filled with urgency and tension. Concerned for his son, Mr. Zhang quickly decided to send his hard-earned savings to “help.” A few days later, during a call with his real son, Mr. Zhang discovered he had been scammed. The entire incident was orchestrated by fraudsters using AI voice-cloning technology to replicate his son’s voice. Another heartbreaking incident involved Mrs. Wang, whose daughter is studying abroad. The two often communicate via video calls. One day, Mrs. Wang received a video call request that displayed her daughter’s familiar face. At first, Mrs. Wang suspected nothing, as she was accustomed to such calls. During the conversation, however, the “daughter” claimed to be in urgent need of tuition and living expenses. Driven by maternal concern, Mrs. Wang quickly transferred the money. Later, she discovered that her real daughter had not initiated the call. The “daughter” on the screen was actually a scammer using AI face-swapping technology to superimpose her daughter’s face onto their own. #voicecloning #Antifraud  #Dingxiang  #DEEPFAKE #AI https://lnkd.in/g4hb3dU3