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This article describes the definition, architecture, and practical applications of explainability in JD's retail recommendation system, covering ranking, model, and traffic explainability, system challenges, data infrastructure, and specific techniques such as SHAP and Integrated Gradients for interpreting model decisions.
Bilibili combats API abuse by deploying a two‑layer anti‑crawling system—gateway‑side signature verification and a GAIA risk‑control engine integrated into APIGW—that unifies device data, applies flexible rule packages, triggers diverse human challenges, and has already blocked billions of malicious requests with over 85% recall while preventing service outages.
The paper presents a scalable sFlow‑based traffic analysis system that combines high‑performance agents, collectors, and analyzers—extending Elastiflow with sFlowtool, Logstash, Kafka, and Elasticsearch/Kibana, while adding CMDB integration, Druid storage, and Celery stream processing to achieve sub‑30‑second latency for data‑center monitoring, anomaly detection, and IP‑level analytics, and discusses future needs for broader protocol support and adaptive collection.
In March 2023 Stack Overflow’s traffic fell nearly 14% while ChatGPT’s usage surged, prompting the company’s CEO to announce a 10% layoff and sparking a broader analysis of AI‑driven tools like GitHub Copilot reshaping how developers seek code solutions.
The article analyzes how Stack Overflow's monthly traffic has fallen sharply in 2023, contrasting this trend with the explosive growth of AI services like ChatGPT and GitHub, and discusses the platform's strategic responses including content bans, layoffs, and new AI‑focused product plans.
The talk, led by Bilibili’s risk‑control head, outlines Internet risk‑control fundamentals, precise traffic perception techniques, and a full‑scenario joint‑defense framework that combines hierarchical identification, cross‑scene signal sharing, statistical anomaly detection, and layered mitigation (soft and hard) to counter black‑market attacks on platforms.
This presentation explores internet risk control, detailing its classification, precise traffic perception methods, and full‑scenario joint defense and control strategies, using Bilibili as a case study to illustrate challenges, adversaries, detection techniques, and mitigation measures.
This article explains how mid‑size enterprises can inventory their network assets, understand complex zone structures, and apply full‑traffic network analysis and tracing techniques—such as SPAN, tunneling, and real‑time monitoring—to improve the effectiveness of security drills.
This article explains how Alibaba's traffic analysis platform evolved to require real‑time analytics, outlines the business background, data model and metric system, discusses the difficulties of big‑data processing, and describes why ClickHouse was chosen and how its features solve those challenges.
This article investigates how to dynamically identify road closures by classifying vehicle, bicycle, and pedestrian trajectories, addressing sample imbalance and noisy labels with a label‑probability mixture Bayesian model and a deep‑learning image‑encoding pipeline, and compares their experimental results.
The 2020 Q2 China Major Cities Traffic Analysis Report, produced by Gaode Maps together with the National Information Center’s Big Data Development Department, Tsinghua University’s Daimler Sustainable Transportation Joint Research Center and other authorities, presents image‑based traffic patterns, mobility trends and data‑driven insights for major Chinese cities in the second quarter of 2020, accessible via the “Read Original” link.
This article explains the concept of full‑path packet loss monitoring, its importance for banking networks, the causes of packet loss, and detailed technical implementations—including traffic splitting, collection, automatic analysis engines, TCP retransmission detection, and algorithms for pinpointing loss locations—to dramatically reduce troubleshooting time.
iQIYI built QNSM, a DPDK‑based full‑traffic analysis engine for complex multi‑zone network boundaries, delivering high‑performance (10+ Gbps per NIC) real‑time detection of DDoS, IDPS, and DLP, with modular pipelines, Kafka integration, and open‑source deployment across 22 clusters.
Gaode’s semi‑supervised deep‑learning framework combines LSTM and ResNet to analyze 28‑day sequences of 39‑dimensional traffic and planning features, automatically discovering and verifying road‑closure events through a three‑layer pipeline, boosting detection confidence and top‑N accuracy by about ten percent and improving user routing.
This article introduces the fundamentals of web crawlers, typical crawling methods, and a comprehensive set of anti‑crawling strategies—including IP control, browser and device simulation, CAPTCHA cracking, and traffic analysis—while detailing the architecture and capabilities of the 58 anti‑crawling platform.
This article provides a comprehensive overview of iQIYI's traffic anti‑cheat mechanisms, covering definitions of fraudulent traffic, industry challenges, data cleaning relationships, system design, rule‑based and machine‑learning solutions, feature engineering, model evaluation, monitoring, service applications, and future prospects.
This article introduces web crawlers, classifies them by technology and intent, presents statistics on crawler traffic across industries and regions, and analyzes the various harms they cause, laying the groundwork for future discussions on anti‑crawling strategies.
On April 8, a record‑breaking 1.23 Tbps DDoS attack—dominated by SSDP reflection and launched by roughly 166 000 mostly Chinese sources, including PCs, IDC servers and IoT devices—targeted a Tencent Cloud‑hosted game, prompting the article to urge operators to assess risk, adopt high‑protection services, conceal origin IPs, and tailor defense policies with expert assistance.
This article details how Qihoo 360 built large‑scale traffic analysis, VxLAN deployment, and SDN practices to automate network operations, improve visibility, and support security, while sharing real‑world challenges, solutions, and a Q&A on network automation strategies.