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c/sideEffectively tracking third-party scripts removes ambiguity, guaranteeing that you remain informed about what is sent to your users' browsers, while also boosting script efficiency by as much as 30%. The uncontrolled existence of these scripts within users' browsers can lead to major complications when issues arise, resulting in negative publicity, possible legal repercussions, and claims for damages due to security violations. Organizations that manage cardholder information must adhere to PCI DSS 4.0 requirements, specifically sections 6.4.3 and 11.6.1, which mandate the implementation of tamper-detection mechanisms by March 31, 2025, to avert attacks by alerting relevant parties of unauthorized changes to HTTP headers and payment details. c/side is distinguished as the only fully autonomous detection system focused on assessing third-party scripts, moving past a mere reliance on threat intelligence feeds or easily circumvented detection methods. Utilizing historical data and advanced artificial intelligence, c/side thoroughly evaluates the payloads and behaviors of scripts, taking a proactive approach to counter new threats. Our ongoing surveillance of numerous websites enables us to remain ahead of emerging attack methods, as we analyze all scripts to improve and strengthen our detection systems continually. This all-encompassing strategy not only protects your digital landscape but also cultivates increased assurance in the security of third-party integrations, fostering a safer online experience for users. Ultimately, embracing such robust monitoring practices can significantly enhance both the performance and security of web applications.
What is SWEAR?
SWEAR operates as a platform dedicated to securing and authenticating audio and video content in real-time from the moment of capture. It creates a distinct "Digital DNA" for each frame, pixel, and audio segment during the recording, with the associated metadata safely recorded on a separate, unchangeable blockchain ledger, allowing any modifications to be easily detected later on. Users can verify the footage's authenticity by contrasting its current state with the original verified version, thus providing immediate evidence of its legitimacy when necessary. This platform is meticulously designed to safeguard sensitive uses, including legal documentation, surveillance operations, public safety initiatives, and corporate protection, which helps maintain a trustworthy chain of custody while retaining media integrity, whether being transmitted or stored. Furthermore, SWEAR’s security system integrates effortlessly with a variety of recording devices and cameras, and it includes a mobile application for greater convenience. The technology also delivers extensive metadata tracking, which covers aspects such as frame rate, resolution, and even detailed pixel information, assuring strong, immutable provenance and security protocols throughout the media's lifecycle. By adopting this comprehensive strategy, the platform not only bolsters confidence in the authenticity of media but also equips users with the tools necessary to leverage this technology in numerous critical situations. As a result, SWEAR stands out in the realm of media security and authenticity, paving the way for enhanced accountability in digital content management.
What is FakeCatcher?
Intel has introduced the innovative FakeCatcher technology for deepfake detection, which analyzes the "blood flow" within video pixels to swiftly determine the authenticity of videos in just milliseconds. This cutting-edge system is integrated into popular editing software that content creators and broadcasters regularly use, facilitating the identification of altered content during the editing phase. Additionally, it plays a vital role in vetting user-generated content, ensuring that authenticity verification is an integral part of the upload process. By making deepfake detection universally accessible, it empowers both individuals and organizations to effortlessly confirm the legitimacy of videos. Deepfakes, which constitute synthetic media that misrepresent reality by fabricating actors and actions, pose a significant challenge in today’s digital landscape. While numerous deep learning detection systems focus on analyzing raw data for inconsistencies, FakeCatcher adopts a unique method by identifying genuine markers of authenticity in real footage, emphasizing the subtle evidence of human characteristics, like the slight changes in pixel color due to blood flow. As the heart pumps, the color of our veins changes, generating the distinct data that FakeCatcher leverages to differentiate between authentic and doctored videos. This groundbreaking detection technology marks a substantial advancement in the ongoing battle against the misuse of deepfake technology, providing a beacon of hope in preserving the integrity of visual media. As the prevalence of deepfakes continues to rise, the implementation of such innovative solutions will be essential in safeguarding truth in digital content.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
SWEAR
Company Location
United States
Company Website
swear.com
Company Facts
Organization Name
Intel
Company Location
United States
Company Website
www.intel.com/content/www/us/en/newsroom/news/intel-introduces-real-time-deepfake-detector.html#gs.08lxwl