Abstract: A method may include a processing system having at least one processor obtaining a first plurality of domain name system traffic records, generating an input aggregate vector from the first plurality of domain name system traffic records, where the input aggregate vector comprises a plurality of features derived from the first plurality of domain name system traffic records, and applying an encoder-decoder neural network to the input aggregate vector to generate a reconstructed vector, where the encoder-decoder neural network is trained with a plurality of aggregate vectors generated from a second plurality of domain name system traffic records. In one example, the processing system may then calculate a distance between the input aggregate vector and the reconstructed vector, and apply at least one remedial action associated with the first plurality of domain name system traffic records when the distance is greater than a threshold distance.

Abstract: A method may include a processing system having at least one processor obtaining a first plurality of domain name system traffic records, generating an input aggregate vector from the first plurality of domain name system traffic records, where the input aggregate vector comprises a plurality of features derived from the first plurality of domain name system traffic records, and applying an encoder-decoder neural network to the input aggregate vector to generate a reconstructed vector, where the encoder-decoder neural network is trained with a plurality of aggregate vectors generated from a second plurality of domain name system traffic records. In one example, the processing system may then calculate a distance between the input aggregate vector and the reconstructed vector, and apply at least one remedial action associated with the first plurality of domain name system traffic records when the distance is greater than a threshold distance.

Abstract: A processing system having at least one processor may obtain domain name system (DNS) traffic records of a DNS platform, the DNS traffic records associated with a source device having a first status and that is submitting DNS queries, where a first-tier DNS authoritative server of the DNS platform is configured to forward the DNS queries from the source device to at least a first second-tier DNS authoritative server of the DNS platform designated for the first status. The processing system may further detect anomalous DNS traffic records from the DNS traffic records, identify a change of the source device from a first status to a second status, based upon the detecting the anomalous DNS traffic records, and reconfigure the first-tier DNS authoritative server to redirect the DNS queries from the source device to at least a second second-tier DNS authoritative server designated for the second status.

Abstract: A method may include a processing system assigning samples of network traffic data to positions in a list, where each of the samples is assigned a cluster identifier corresponding to the respective position, and traversing the list, where for each position, the processing system: increments an order indicator, and when the cluster identifier is not less than the order indicator, computes a distance between a sample assigned to the position and other samples, records a cluster identifier of another sample when a distance between the sample and the other sample is less than a threshold distance, and assigns a minimum cluster identifier that is recorded to all of the samples with cluster identifiers that are recorded. The processing system may determine clusters from cluster identifiers in the list after the traversing and identify at least one cluster as representing anomalous network traffic data.

Abstract: A processing system having at least one processor may obtain domain name system (DNS) traffic records of a DNS platform, the DNS traffic records associated with a source device having a first status and that is submitting DNS queries, where a first-tier DNS authoritative server of the DNS platform is configured to forward the DNS queries from the source device to at least a first second-tier DNS authoritative server of the DNS platform designated for the first status. The processing system may further detect anomalous DNS traffic records from the DNS traffic records, identify a change of the source device from a first status to a second status, based upon the detecting the anomalous DNS traffic records, and reconfigure the first-tier DNS authoritative server to redirect the DNS queries from the source device to at least a second second-tier DNS authoritative server designated for the second status.

Abstract: A method may include a processing system assigning samples of network traffic data to positions in a list, where each of the samples is assigned a cluster identifier corresponding to the respective position, and traversing the list, where for each position, the processing system: increments an order indicator, and when the cluster identifier is not less than the order indicator, computes a distance between a sample assigned to the position and other samples, records a cluster identifier of another sample when a distance between the sample and the other sample is less than a threshold distance, and assigns a minimum cluster identifier that is recorded to all of the samples with cluster identifiers that are recorded. The processing system may determine clusters from cluster identifiers in the list after the traversing and identify at least one cluster as representing anomalous network traffic data.

Abstract: A method may include a processing system having at least one processor obtaining a first plurality of domain name system traffic records, generating an input aggregate vector from the first plurality of domain name system traffic records, where the input aggregate vector comprises a plurality of features derived from the first plurality of domain name system traffic records, and applying an encoder-decoder neural network to the input aggregate vector to generate a reconstructed vector, where the encoder-decoder neural network is trained with a plurality of aggregate vectors generated from a second plurality of domain name system traffic records. In one example, the processing system may then calculate a distance between the input aggregate vector and the reconstructed vector, and apply at least one remedial action associated with the first plurality of domain name system traffic records when the distance is greater than a threshold distance.

Abstract: Concepts and technologies disclosed herein are directed to internet traffic classification via time-frequency analysis. According to one aspect of the concepts and technologies disclosed herein, a security classification scheme can be implemented to identify potentially malicious activities from normal internet traffic. The security classification scheme can exploit the distinctive characteristics of different types of traffic in both frequency domain and time domain to identify four different cases. Due to the separation of different types of traffic, the security classification scheme can lower the false alarm rate and improve network security. The security classification scheme can utilize a recursive discrete Fourier transform (“DFT”) implementation to enhance computational efficiency.

Abstract: Concepts and technologies disclosed herein are directed to internet traffic classification via time-frequency analysis. According to one aspect of the concepts and technologies disclosed herein, a security classification scheme can be implemented to identify potentially malicious activities from normal internet traffic. The security classification scheme can exploit the distinctive characteristics of different types of traffic in both frequency domain and time domain to identify four different cases. Due to the separation of different types of traffic, the security classification scheme can lower the false alarm rate and improve network security. The security classification scheme can utilize a recursive discrete Fourier transform (“DFT”) implementation to enhance computational efficiency.

Abstract: A system and method for bridging the POTS network and a packet network, such as the Internet, uses a set of access objects that provide the interfacing and functionality for exchanging address and payload information with the packet network, and for exchanging payload information with the payload subnetwork and signaling information with the signaling subnetwork of the POTS network.