Edge Cybersecurity in Retail
The retail industry is booming, making it a common target for bad actors. According to IBM’s ranking, retail and wholesale were the fifth-most targeted industries, accounting for 7.3% of all attacks in 2021. Cyber criminals are financially motivated to attack retail from different angles in the hope of getting a piece of the cake, which is projected to amount to around $27.3 trillion US dollars by the end of 2022.
Retailers favor the use of edge environments to access easy and simplified integrations of networking and security aspects in their infrastructure. In fact, according to Gartner research, 20% of tier 1 multichannel retailers will use edge computing to enable edge artificial intelligence use cases by 2025.
Cybersecurity in retail can be complex and is actually a factor of why many organizations fail to set the right protective barriers in place to safeguard sensitive data. For example, point-of-sale systems and devices carry the financial information of consumers, which is exactly what hackers are after.
Network attacks can bring significant service interruptions for critical systems in retail stores that are connected to Edge infrastructures. For example, POS terminals, security, and AI cameras, as well as other equipment can be critical for network security threats. Security incidents in these components can experience financial losses due to service interruptions.
Simultaneously, IoT-based connectivity is sometimes exposed to client and shop visitors and open to hacking and brute-forcing, DDoS and other kinds of threats. It’s critical for such systems to provide asset management and incident detection and response with solutions like AI EdgeLabs. Its Reinforcement Learning algorithms guarantee lower false positive rates for security operation teams and provide better hidden threat detection from adversaries and prevent them in real-time.
Edge Risk Use Cases in Retail
IoT is revolutionizing the retail industry by advancing customer experience, optimizing supply chains, and creating a new source of revenue. With IoT, it becomes easier and faster to collect data from customers, as well as analyze it and use it to offer more personalized services to each customer.
The security vulnerabilities of cameras, sensors, and other equipment can be broadly divided into two classes, Edge connected device challenges and software security issues.
Edge connected device threats arise due to the ubiquitous and heterogeneous nature of IoT devices, while the software security threats are related to the functionalities and the principles that should be enforced to attain a secure network.
Edge connected device vulnerabilities are typically related to wireless and Bluetooth technologies, while software security challenges require the ability to ensure security by integrity, authentication, end-to-end security, confidentiality, and more.
Cybersecurity attacks like BEC, server access, data theft, and credential harvesting were the most prominent ones for retail and wholesale last year. Phishing attacks took the first spot with 38% of all attacks, followed by stolen credentials at 32%, and vulnerability exploitation coming in third with 23%.
Internet of Things Devices
Brick-and-mortar retail stores rely more than ever on IoT devices such as cameras, sensors, and more to enhance the customer experience. As they gain popularity, these IoT devices need to be protected as bad actors love to tamper with them through sophisticated attacks that can result in multimillion dollar losses.
For robust protection and rich monitoring of these IoT devices, AI EdgeLabs provides advanced network and threat visibility, as well as early anomaly detection for threats that may come from IoT devices.
PCI DSS Compliance
Payment Card Industry Data Security Standard, or PCI DSS for short, handles consumer credit card information, making it a prime target for cyber criminals with high-profile attacks looking to steal money out of unsuspecting consumers.
Retailers need to implement firewalls, put strong security measures and systems in place, and provide maintenance to said systems to keep cyber criminals at bay. AI EdgeLabs is a threat intelligence cybersecurity platform that acts as a smart firewall solution when it comes to cyber AI and attack prevention.
Data Leaks and Data Hacks
Data leaks are probably some of the most prominent cases of cyber attacks as typically, criminals get away with accessing volumes of personal data, endangering their right to privacy protection.
Retailers heavily rely on artificial intelligence for personal image/video data of customers. As such, it becomes increasingly important for retailers to implement protection layers to prevent hacking or data leaks beyond the well-known and accepted security measures that many employ and which criminals now find easy to bypass.
How AI EdgeLabs Can Strengthen Cybersecurity in Retail
The AI EdgeLabs platform offers ongoing threat analytics to monitor threats based on the latest behavior-based analytics, as well as rich traffic inspection for anomalous patterns using Reinforcement Learning. The platform also provides automated incident response and remediation for immediate protection and maximum cybersecurity.
Even though the retail industry, more so than any other industry, is subject to the regulatory requirements, there’s still ample need for a centralized visibility and management solution.
It’s critical that retailers take a comprehensive approach to security infrastructure design at the Edge level, consolidating their applications under a common umbrella solution thatis modular, reliable, scalable, and easy to manage.
AI EdgeLabs threat intelligence ensures:
- Threat detection for IoT Equipment in the store
- Hidden and unknown threat and abnormal activity detection
- Smart firewalling with automated response
- Assets management inside the retail ecosystem
- Mitigation actions for incidents
AI EdgeLabs is a robust, enterprise-grade, and AI-based platform that brings advanced network visibility, early threat detection, and automated incident response and remediation vital for the retail industry. Enriched with Deep Reinforcement Learning, our platform is smart and impressively accurate in detecting threats before they even have a chance to cause harm.