However, this exponential growth is accompanied by various security threats. Sophisticated phishing attacks, cryptojacking, bot-based credential stuffing, and exploitation of IoT vulnerabilities among other threats continue to weaken business defenses.
What’s more, cybercriminals are increasingly using AI to launch these attacks. For instance, deepfake scams and convincing phishing emails using AI are amplifying the severity and sophistication of these attacks.
Moreover, e-commerce businesses deal with vast amounts of data. So, identifying anomalies and predicting potential vector attacks can be challenging. For instance, an article on the Wall Street Journal shares that Amazon faces nearly one billion threats a day.
Thus, it has become essential to counter these evolving threats by integrating AI in cybersecurity. From automated threat detection systems to predictive analytics, AI can help businesses enhance their resilience to cyber-attacks.
This post offers practical information on why AI matters and how it can be used to defend the business against such attacks.
7 Tactics to Use AI for Cyberthreat Prevention in E-Commerce
Implement AI-Enabled Fraud Detection
Businesses can safeguard their digital transactions and proactively identify and prevent fraudulent activities by leveraging machine learning and real-time analytics. Integrating AI-powered fraud detection into payment systems can help reduce fraud losses and enhance customer trust.
Here’s how businesses can leverage AI for fraud detection-
Analyze Transaction Patterns
AI tools can process volumes of transaction data to separate normal spending behaviors from anomalous transactions. For instance, if a shopper usually makes small domestic purchases but suddenly initiates a high-value international transaction, the machine learning algorithm can flag it for review.
Detect Anomalies
ML models can spot anomalies that traditional systems cannot detect. By training such models with historical data, AI can detect emerging fraud patterns and tactics. For instance, it can proactively detect card testing and account takeovers.
AI-Driven Risk Scoring
AI can assign risk scores to transactions based on several factors like user behavior, device type, or location to help with real-time fraud detection and prevention. For instance, high-risk transactions can trigger security measures like multi-factor authentication (MFA) and temporary transaction holds.
AI-Based Authentication to Strengthen Payment Security
AI-based authentication in digital transactions can help businesses combat fraud and bolster their security measures. AI can enhance biometric authentication systems to make them more secure and reliable by analyzing unique physiological and behavioral traits, making any unauthorized access tough.
This form of authentication is a robust alternative to traditional password-based logins as it uses machine learning algorithms, deep neural networks, and real-time analytics to enhance security.
AI-driven behavioral analytics is another area where AI can be deployed to detect anomalies that indicate unauthorized access.
For instance, the algorithms can analyze patterns in speed, transaction time, or navigation behavior and spot deviations from established patterns. Any anomaly can trigger security protocols like adding an authentication step for completing the transaction or putting the whole process on hold. This proactive approach can significantly improve the overall security of the payment process.
Finally, AI-based dynamic CVV codes change periodically, significantly reducing the risk of card-not-present fraud (CNP). The traditional static CVV is often at risk of theft or misuse. A Federal Trade Commission report shared that such credit card fraud topped the list of identity theft types in 2023.
In such a scenario, dynamic CVV (dCVV) is a compelling solution to neutralize threats and prevent fraudsters from executing unauthorized transactions. The dCVV card replaces the static three-digit code with an e-paper screen that updates automatically, preventing fraud transactions and allowing intervention when suspicious activity is detected.
AI for Threat Intelligence
AI can help digital commerce firms stay ahead of cybercriminals through threat intelligence. It analyzes huge volumes of data and predicts, detects, and mitigates threats in real-time.
AI-powered security tools identify patterns in dark web activity, malware signatures, and network traffic to spot potential cyberattacks. These tools can help online retail businesses receive real-time security insights and plan a proactive defense strategy.
Moreover, AI-powered security response allows quick action once a threat is detected. The system isolates infected systems, blocks malicious IPs, and enforces security policies without the need for human intervention.
For instance, AI can be deployed in endpoint detection and response (EDR) to reduce breach detection time and false alarms and enhance the speed of security system response, thus boosting overall security.
AI-enabled chatbots also offer instant alerts during a cybersecurity incident. The bots alert the user of unusual activity and suggest fitting actions to allow real-time mitigation of the threats.
Thus, AI can help e-commerce companies strengthen their security posture and minimize human error.
Boost IoT Security
The interconnected network of devices, sensors, and software allows e-commerce firms to transmit data to the database, track customer behavior, track the location of the products in transit, and offer the status of deliveries. This network offers huge opportunities for threat actors to remotely control IoT devices.
Hence, an e-commerce business cannot operate without IoT security. To understand how AI can help here, we must first understand what is IoT security.
IoT security in e-commerce encompasses all the measures taken to protect connected devices, secure online transactions, and prevent unauthorized access.
AI can power IoT security by monitoring connected devices and sensors at warehouses and payment gateways and studying the network traffic and behavior. ML algorithms identify patterns and spot anomalies to mitigate risks related to unauthorized access.
Further, deploying AI with encryption can enhance data security for IoT networks and protect data from being stolen, changed, or compromised. AI optimizes the encryption process, makes the threat detection process more efficient, and simplifies key management.
Proactive Malware and Phishing Attack Detection
One of the most prominent threats to an e-commerce business is malware infection which is used by cybercriminals to encrypt sensitive information like passwords or account details, rendering it inaccessible to the retailer. Phishing scams are yet another risk where fraudulent attempts are made to trick customers into sharing sensitive information.
Hence, e-commerce businesses must leverage advanced technologies like AI that can detect malicious software and prevent them from entering the system.
Training AI models to detect phishing emails and fraudulent websites presents a proactive approach to prevent such attacks. For instance, AI systems examine elements like unusual sender behavior or malicious attachments and block such threats.
Further, advanced AI-enabled malware analysis tools leverage machine learning to spot malware threats in real-time. These tools can automatically detect and get rid of malware threats before they cause harm to the system.
AI-powered browser security features also work to enhance user protection. For instance, the scareware blocker can detect and block malicious ads and scripts, preventing users from engaging with harmful content. The machine learning model compares web content with scam content samples to spot a threat. Once it detects a threat, the browser displays a warning or halts audio playback, discouraging the user from consuming the content.
Compliance Automation with AI
Compliance with regulations like GDPR, CCPA, PCI DSS, and others is central to protecting customer data and avoiding hefty fines and reputational damage. For instance, the legal consequences and penalties for GDPR non-compliance can amount to $21.76 million or 4% of the business’s global annual revenue.
Adopting AI for compliance can streamline the process and safeguard customer data, thus building trust. AI-enabled tools can help businesses avoid these fines by automating the compliance process and reducing human error. These platforms constantly monitor and compare compliance with the standard regulations on parameters like data handling practices and potential compliance gaps.
AI improves data security by automating the encryption process and monitoring unauthorized access through anomalies in patterns.
Besides, AI-enabled auditing systems can identify vulnerabilities in real-time from the network traffic and system logs. Security teams receive alerts and reports on network performance, enabling them to proactively mitigate the risks and improve their security posture.
AI-Powered Predictive Analytics
In cybersecurity, predictive analytics uses data and advanced analytical techniques to anticipate potential threats and forestall issues before they materialize. The neural networks can crunch vast volumes of data from a sea of IoT devices to spot anomalies.
For instance, these networks can detect and correct quantum computing errors like quantum decoherence in the system.
AI-powered predictive analytics can help businesses strengthen their defenses and stay one step ahead of cybercriminals. In fact, in an AI in Cybersecurity report, 69% of organizations shared that they would not be able to effectively respond to digital threats without AI.
Further, self-healing security solutions help in applying patches, reconfiguring security settings, and restoring compromised files without any human intervention. AI constantly learns from new attack patterns and feeds the ML algorithm to improve its accuracy and reduce false positives.
Tools like Security Information and Event Management (SIEM) can help e-commerce companies proactively mitigate risks. Businesses can also leverage Endpoint Detection and Response (EDR) solutions to strengthen their security framework.
Summing Up
AI is a strategic asset for digital commerce businesses aiming to improve their security posture. The e-commerce industry is rife with security threats; hence, proactive security intelligence is the need of the hour.
