In today's accelerated digital transformation, how enterprises can effectively integrate AI technology and information security has become a key issue.This session will explore in-depth AI-driven information security innovation strategies, help enterprises utilize AI technology to realize proactive prediction and response mechanisms, and provide CIOs and CISOs with a new perspective on risk.

As enterprises increasingly adopt application-driven business models, security issues have become increasingly prominent. Many network security measures focus too much on human identity and ignore the management of machine identity. This provides opportunities for hackers and may lead to deep system attacks, ultimately leading to network attacks and data leaks. 

In the current digital economy, secure machine-to-machine communications have become even more important. However, with the widespread application of artificial intelligence (AI), new risks also arise. AI's automation and decision-making capabilities, if not properly managed, can lead to management vulnerabilities in TLS certificates and machine identities, increasing security threats.

Participants will gain an in-depth understanding of the challenges posed by rapidly growing machines and the complexities of cloud environments. We will explore the risks that AI can cause in TLS certificate lifecycle management (CLM), including potential errors in automated processes, insufficient anomaly detection, and errors in vulnerability prediction. This workshop will provide attendees with key insights and tools to strengthen their cybersecurity defenses and effectively manage machine identities in an AI-driven environment

Data protection is a key challenge for businesses. Through case sharing, the actual effects and practical strategies of innovative solutions are demonstrated, providing valuable reference and inspiration for enterprises in the field of information security.

As the 5G era dawns and the Internet of Things (IoT) rapidly proliferates, network traffic is undergoing explosive growth. The emergence of innovative applications (like OTT services) and diverse network architectures (such as CDNs) has made traffic content and behavior more varied and complex, presenting new challenges for carrier-grade traffic visibility and forensic analysis.

In this session, we will delve into use cases to explore how GenieAnalytics by Genie Networks leverages diverse traffic data collection, big data database construction, heterogeneous data correlation and enrichment, multidimensional traffic analytics, and network forensics to help network operators grasp traffic pattern, gain instant insights, and effectively address challenges.

We will demonstrate how to build a carrier-grade, network-wide traffic analysis solution, assisting network management teams in optimizing network resources, detecting traffic anomalies, and enhancing network security. This presentation, combining technological trends with practical applications, will lead you to explore new horizons in next-generation network security and management.

Elastic Security combines AI Assistant and Machine Learning to bring a new perspective to enterprise security operations. The AI Assistant focuses on quickly analyzing alerts, helping security teams clarify the threats to prioritize and provide the best response recommendations, significantly shortening incident response time. Machine learning technology is responsible for in-depth mining of massive log data within the enterprise, proactively identifying potential threats and abnormal behavior, avoiding the risks that traditional rule-based systems may miss. Compared to the high false positive rate and data processing bottlenecks of traditional SIEMs, Elastic Security breaks through limitations with its distributed architecture and intelligent analysis technology, achieving more comprehensive and accurate control of modern threats. This topic will delve into how Elastic Security can revolutionize security operation processes and improve threat detection efficiency through the perfect combination of AI Assistant and machine learning, and demonstrate its qualitative difference from traditional SIEMs, providing enterprises with an intelligent security solution for the future.

Over the past decade, HCLSoftware has played a pivotal role in advancing the digital economy with its robust cybersecurity capabilities. The company has been a driving force behind digital transformation, offering proven security solutions that empower businesses to evolve securely and efficiently.

HCLSoftware offers a comprehensive suite of products and services that tackle a wide range of areas including business applications, AI and intelligent operations, total experience, data and analytics, and cybersecurity. These solutions are designed to bridge the gap between where businesses currently stand and where they aspire to be, equipping them with the necessary toolkit to thrive in the digital+ economy.

With a strong focus on automation, cloud adoption, data analytics, and security, HCLSoftware is portrayed as a catalyst for decision-making, unlocking potential, and propelling transformative growth across various industries.

• Challenges, Trends, and Strategies for Modern Data Environments
• Balancing Security and Efficiency: Ensuring a Safe Environment While Maintaining Operations
• Application and Flexibility of Innovative Technologies in Data Security

With the rapid growth of Internet use, whether it is various information equipment, mobile devices or IoT devices, more and more services are provided using the Web. As Web application services are used in large numbers, what are the problems with Web applications? What risks will arise from these issues? How to face these risks is an important issue worthy of discussion.