Transparent Proxy Isolating Malware in Virtual Browsers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current malware attacks, particularly zero-day exploits and drive-by-download attacks, often go undetected by conventional anti-virus and anti-malware technologies, compromising user devices and personal information without users' knowledge or consent.
Innovation Solution
A system and method utilizing a transparent network proxy, virtual browser machines, and desktop virtualization technologies to securely browse unknown or suspicious URLs, ensuring that users' devices remain uncompromised by isolating potential malware within a browser virtual machine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a proxy blocks unknown URLs to prevent malware, then security is improved, but user ability to browse unknown URLs is dramatically reduced
Solution Approach 1:
A warning web page is introduced as an intermediary between the user and the unknown URL. When a user attempts to access an unknown URL, the proxy intercepts the request and presents a warning page that provides information about potential risks while allowing the user to make an informed decision. This mediator approach maintains security by alerting users without completely blocking access, thus preserving browsing versatility.
2Loss of information
If warning web pages are displayed for unknown URLs, then user awareness of potential malware is improved, but security decision is still placed on the user
Solution Approach 1:
The system performs preliminary analysis of the URL before allowing access. The proxy evaluates the URL against known malware databases, checks for suspicious patterns, and assesses risk levels in advance. This preliminary action provides users with concrete security information rather than generic warnings, enabling more informed decisions while maintaining stronger security protections.
3Reliability
If conventional anti-virus technologies are used, then detection of known malware is improved, but zero-day exploits and drive-by-download attacks go undetected
Solution Approach 1:
The system employs dynamic detection mechanisms that adapt to new threats in real-time. Instead of relying solely on static signature databases, the proxy uses behavioral analysis, sandboxing, and machine learning models that continuously update based on emerging threat patterns. This dynamic approach enables detection of zero-day exploits and drive-by-download attacks that conventional static anti-virus technologies miss.
Data Source
AI summary
A system for providing secure browsing via a transparent network proxy is disclosed. The system may receive, from a client, a request to access a resource. The request may include an identifier that may be utilized to locate the resource. Once the request is received, the system may determine if the resource is not trusted, such as if the identifier is determined to be unknown or suspicious. If the resource is determined to not be trusted by the system, the system may forward the request to a virtual machine manager that may select a browser virtual machine from a pool of browser virtual machines. After the browser virtual machine is selected, the browser virtual machine may stream a rendering of the resource to the client based on the request. The rendering of the resource may be provided in lieu of the actual resource.