Call-Aware Link Fraud Prevention Mechanism [Proposal]
1. Background
In many social engineering fraud cases, attackers initiate a phone call and guide the victim to open a malicious link sent through SMS, messaging apps, or other communication channels. The attacker remains on the call to create urgency and instruct the victim to perform actions such as entering credentials, sharing OTPs, or installing malicious applications.
Traditional caller identification tools mainly detect spam numbers but do not actively protect users during the real-time interaction phase of a scam.
This proposal introduces a Call-Aware Link Protection Framework designed to identify suspicious patterns involving calls, links, and user actions.
2. Key Risk Scenario
A typical fraud pattern occurs as follows:
The victim receives a call from an unknown or spoofed number.
During the call, the attacker sends a link via SMS, WhatsApp, or other messaging platforms.
The attacker instructs the victim to open the link immediately.
The victim enters sensitive information such as:
OTP
banking credentials
personal details
Since the victim is under real-time psychological pressure, they may follow instructions without verifying the link’s authenticity.
3. Proposed Solution Components
3.1 Call-Aware Link Opening Protection
A security layer within the mobile operating system or a dedicated security application can monitor whether a phone call is active when a link is opened.
Working Concept
User receives a link via SMS or messaging application.
User clicks the link while an active call is ongoing.
The system detects the active call session.
A security alert is triggered before opening the link.
This alert informs the user that fraudsters often send links during phone calls to steal sensitive information.
This mechanism introduces a moment of pause and helps the user reconsider the action before proceeding.
3.2 Real-Time Link Risk Analysis
When a link is received during a call, a security service can perform instant risk analysis on the link.
The analysis may include:
Domain registration age
Similarity to legitimate banking or service domains
Presence of URL shortening services
Matching against known phishing link or domain databases
If the link appears suspicious, the system can warn the user before opening it.
3.3 Call and Link Behavioral Pattern Detection
The system can monitor user behavior patterns during calls to identify suspicious activity sequences.
Example Pattern Detection
An unknown number calls the victim.
Within 1–2 minutes, the victim receives a link.
The victim attempts to open the link during the call.
When this pattern is detected, the system can trigger a possible scam alert.
Over time, additional fraud patterns can be added to a centralized database to improve detection accuracy.
3.4 Link Delay Mechanism
To disrupt real-time manipulation by attackers, links received during active calls can be temporarily restricted.
Possible actions include:
Temporarily hiding the link notification
Delaying link access until the call ends
Prompting the user to disconnect the call before proceeding
Since scammers rely heavily on urgency and continuous guidance, introducing delays significantly reduces the effectiveness of the attack.
3.5 Scam Number Behavior Analysis
Unlike traditional spam detection systems that rely primarily on user reports, an advanced system can perform behavioral analysis of call activity.
The system can maintain records of:
Call frequency
Number of unique recipients contacted
Duration of calls
Time patterns of calls
Examples of suspicious indicators include:
A number calling hundreds of users within a short time period
Repeated short-duration calls
Large volumes of calls within a single hour
When such patterns are detected, the system may generate alerts such as:
“This number has contacted multiple users within a short time frame. Possible scam activity detected.”
After the call ends, users may also be prompted to provide feedback or report the call, similar to existing caller identification platforms.
3.6 Elderly Protection Mode
Older individuals are among the most frequent victims of social engineering scams.
A dedicated Elderly Protection Mode can be introduced with enhanced safeguards, such as:
Stronger scam warnings
Automatic blocking of suspicious links during calls
Simplified alert messages
Optional notification to trusted family members if a potential scam is detected
This feature helps protect vulnerable users who may not be familiar with common cyber fraud tactics.
3.7 Real-Time Scam Interaction Interruption
When the system detects a high-risk combination of signals such as:
suspicious call
link received during call
OTP request or sensitive activity
the system can actively interrupt the interaction.
Possible responses include:
temporarily muting the call
displaying a full-screen security warning
requiring user confirmation before continuing the call
This intervention helps break the attacker’s control over the conversation and reduces the likelihood of successful fraud.
4. Key Differentiation
Most existing solutions focus on caller identification and spam reporting.
However, they do not adequately address the real-time interaction phase of scams, where the victim is actively manipulated during the call.
The proposed approach focuses on integrating:
call context
link behavior
OTP events
user interaction patterns
to create a multi-layer fraud prevention framework.
5. Conclusion
Fraudsters increasingly combine phone calls with malicious links to manipulate victims into revealing sensitive information. By implementing call-aware link protection, behavioral analysis, and real-time interaction controls, organizations can significantly reduce the success rate of such attacks.
The proposed system introduces proactive safeguards that interrupt scam workflows and provide users with timely warnings before sensitive actions are performed.
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