Defending Digital Storefronts: Deep Learning Strategies for E-Commerce Ransomware Prevention

As ransomware attacks targeting e-commerce companies that rely on digitally mediating commerce categories have increased in number during recent years along with much else connected with information security so too has crime become more sophisticated. “Ransomware” refers to a type of software that someone sends to Internet users hoping to gain access and control over their computers encrypts their sensitive file data. As a result, victims cannot use or read these files. They are, in effect, until the blackmail money has been paid normally using Bit coins or another kind of digital currency in e-commerce shops, ransomware encrypts product online, systems for accepting an order payment, customer databases and logistics. This together can lead to huge financial or reputation losses. Ransomware has become an enormous headache for e-commerce. Hackers take advantage of mistakes in programming, launch phishing ventures, or break into other people s systems-before infiltrating e-commerce platforms. There they hold vital data hostage and demand a ransom for its release. Ransomware attacks in e-commerce can lead to market loss, customer trust and damage claims as a result of data infringement. After all, the impact goes beyond financial loss at this moment. The Smart Chip Model Employing advanced algorithms like Artificial Neural Network (ANN), this smart chip monitors network flows and even finds unusual patterns, which in some cases could indicate ransomware attacks. By analyzing arriving and departing data packets, potential threats can be recognized in time to alert the system and prevent their having any effect. Its ability to identify new threats is increased by this AI-based model. In this way, the warning system worked has not only prevented ransomware from entering sensitive e-commerce data but also reduced financial loss and reputational damage Moreover, in the trials, this model achieved an 89% correctness rate, making it effective at reducing risks associated with ransomware. With the integration of this AI-enabled smart chip into e-commerce infrastructure, businesses are thus able to fortify their security posture. This means that they are less likely to be targeted by ransomware attacks. As a result, it had become an essential tool for reducing the threat ransomware posed to businesses and proactively tackling cyber security issues.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/ictacs62700.2024.10841295
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Defending Digital Storefronts: Deep Learning Strategies for E-Commerce Ransomware Prevention

Mudita Uppal, Ankita Kumari, Kamali Singla
Advanced Malware Detection Techniques
article

Defending Digital Storefronts: Deep Learning Strategies for E-Commerce Ransomware Prevention

Mudita Uppal, Ankita Kumari, Kamali Singla
article en

Abstract

As ransomware attacks targeting e-commerce companies that rely on digitally mediating commerce categories have increased in number during recent years along with much else connected with information security so too has crime become more sophisticated. “Ransomware” refers to a type of software that someone sends to Internet users hoping to gain access and control over their computers encrypts their sensitive file data. As a result, victims cannot use or read these files. They are, in effect, until the blackmail money has been paid normally using Bit coins or another kind of digital currency in e-commerce shops, ransomware encrypts product online, systems for accepting an order payment, customer databases and logistics. This together can lead to huge financial or reputation losses. Ransomware has become an enormous headache for e-commerce. Hackers take advantage of mistakes in programming, launch phishing ventures, or break into other people s systems-before infiltrating e-commerce platforms. There they hold vital data hostage and demand a ransom for its release. Ransomware attacks in e-commerce can lead to market loss, customer trust and damage claims as a result of data infringement. After all, the impact goes beyond financial loss at this moment. The Smart Chip Model Employing advanced algorithms like Artificial Neural Network (ANN), this smart chip monitors network flows and even finds unusual patterns, which in some cases could indicate ransomware attacks. By analyzing arriving and departing data packets, potential threats can be recognized in time to alert the system and prevent their having any effect. Its ability to identify new threats is increased by this AI-based model. In this way, the warning system worked has not only prevented ransomware from entering sensitive e-commerce data but also reduced financial loss and reputational damage Moreover, in the trials, this model achieved an 89% correctness rate, making it effective at reducing risks associated with ransomware. With the integration of this AI-enabled smart chip into e-commerce infrastructure, businesses are thus able to fortify their security posture. This means that they are less likely to be targeted by ransomware attacks. As a result, it had become an essential tool for reducing the threat ransomware posed to businesses and proactively tackling cyber security issues.

Chitkara University (IN)
Openalex Percentile: Top 71%
Advanced Malware Detection Techniques
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