CACI International has patented a system to predict fingerprints in encrypted traffic using machine learning. By analyzing entropy levels, the system identifies paths taken by encrypted data in a network to enhance security measures. GlobalData’s report on CACI International gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on CACI International, was a key innovation area identified from patents. CACI International's grant share as of April 2024 was 69%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting existence of fingerprints among encrypted traffic
A recently granted patent (Publication Number: US11949711B2) discloses a computer-implemented method that involves generating a data set with a specific amount of entropy, combining this data set with user data before cryptographic encryption, and then analyzing the resulting ciphertexts using a machine learner to determine entropy levels. If the first ciphertext has higher entropy than the second ciphertexts obtained from the network, a portion of the network traversed by the first ciphertext is identified and outputted to a remote user.
The method utilizes a classifier, such as support vector machine (SVM) or artificial neural network, to make entropy level determinations. The user data, which can be part of a message being transmitted over the network, is combined with the data set through concatenation. Additionally, the method can identify portions of different networks traversed by the ciphertext and can include the entire path from the node where data set and user data are combined to the node where the user data is consumed. This innovative approach allows for dynamic combination of data sets and user data based on user demand, enhancing network security and efficiency in data transmission.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
