Telefonaktiebolaget Lm Ericsson (publ)

Government of the United States of America, As Represented by the Secretary of Commerce

George Mason Intellectual Properties, Inc.

George Mason Research Foundation, Inc.

National Institute of Standards and Technology

Lingyu Wang

Makan Pourzandi

Yosr Jarraya

Mourad Debbabi

Mengyuan Zhang

Sushil Jajodia

Meisam Mohammady

Anoop Singhal

Steven E Noel

Momen Oqaily

Han Wang

Yuan Hong

Shangyu Xie

Sudershan Lakshmanan Thirunavukkarasu

Suryadipta Majumdar

Taous Madi

Amir Alimohammadifar

A method, system and apparatus are disclosed. According to one or more embodiments, a data node is provided. The data node includes processing circuitry configured to: receive an anomaly estimation for a first privatized dataset, the first private dataset being based on a dataset and a first noise profile, apply a second noise profile to the dataset to generate a second privatized dataset, the second noise profile being based at least on the anomaly estimation, and optionally cause transmission of the second privatized dataset for anomaly estimation.

DPOD: differentially private outsourcing of anomaly detection

A method, system and apparatus are disclosed. In one or more embodiments, a differential privacy, DP, node is provided. The DP node includes processing circuitry configured to: receive a query request; receive a first input corresponding to a utility parameter; receive a second input corresponding to a privacy parameter; select a baseline DP mechanism type based at least on a query request type of the query request, the first input and the second input, where the baseline DP mechanism type includes at least a noise parameter; generate a noise distribution based on the baseline DP mechanism type using a first value of the noise parameter; and determine a DP query result based on applying the noise distribution to the query request applied on a data set.

Utility optimized differential privacy system

A method, system and apparatus are disclosed. According to one or more embodiments, a detection node in communication with a network function virtualization, NFV, system operating a NFV stack that is logically separable into a plurality of levels including a first level and a second level is provided. The detection node includes processing circuitry configured to: translate an executed first level event sequence to at least one translated second level event sequence, and compare the at least one translated second level event sequence to an executed second level event sequence to at least in part detect inconsistencies between the at least one translated second level event sequence and the executed second level event sequence where the executed second level event sequence and the executed first level event sequence being part of a multi-level sequence flow.

System for translation-based real-time inconsistency detection in network functions virtualization (NFV)

Systems and methods for anonymizing data are provided herein. A network node can receive privacy constraints from a data owner and utility requirements from at least one data processor. An anonymization mechanism can be selected for each data attribute in a data set, based on its specified privacy constraint and/or utility requirement, from the available anonymization mechanism(s) appropriate for its associated attribute type.

Data anonymization views

A method, computing device and system are disclosed for evaluating security of virtual infrastructures of tenants in a cloud environment. At least one security metric may be calculated for virtual infrastructures of a tenant based on information associated with at least one virtual resource of the first tenant and at least one interaction of the at least one virtual resource of the first tenant with at least one virtual resource of at least one other tenant in a multi-tenant virtualized infrastructure. At least one security parameter may be evaluated for the first tenant based at least in part on at least one of the at least one calculated security metric for monitoring a security level of the first tenant relative to the at least one other tenant in the multi-tenant virtualized infrastructure.

Apparatus and method for evaluating multiple aspects of the security for virtualized infrastructure in a cloud environment

Systems and methods for verifying the validity of a network link are described herein. A verification packet and an associated packet handling flow can be generated and added to a network in order to investigate a link between network nodes (e.g. switches).

Network link verification

A node including processing circuitry configured to: generate anonymized data based at least in part on a first cryptographic key and network data, calculate a coordination vector, generate initialized data based at least in part on the anonymized data, a second cryptographic key and the coordination vector, transmit the initialized data, the random vector, a security policy and instructions to analyze n iterations of the initialized data and the security policy using the random vector and the second cryptographic key, and receive results of the analysis of the n iterations of the initialized data and the security policy using the random vector and the second cryptographic key. The analysis of an m iteration of the n iterations correspond to an analysis of the initialized data with prefix preservation where the analysis of the remaining iterations of the n iterations fail to be prefixed preserved.

Partition-based prefix preserving anonymization approach for network traces containing IP addresses

A node includes processing circuitry configured to encrypt first network data including a first tenant identifier using a first cryptographic key to generate first encrypted data and anonymize the first encrypted data to generate anonymized data where the anonymizing of the first encrypted data includes segmenting the first encrypted data and the anonymizing of the first encrypted data preserving relationships among the first network data associated with the first tenant identifier, encrypt the anonymized data using a second cryptographic key to generate encrypted anonymized data, transmit the encrypted anonymized data, at least one analysis parameter, at least one security policy and instructions to analyze the encrypted anonymized data using the at least one analysis parameter, the at least one security policy and the second cryptographic key, receive analysis data resulting from the analysis of the encrypted anonymized data, and determine verification results from the received analysis data.

Privacy-preserving data verification

Systems and methods for determining a safety level of a network vulnerable to attack from at least one origin to at least one target are described. Machines, components, and vulnerabilities in a network may be associated to one another. Degrees of similarity among the vulnerabilities may be determined and subsets of vulnerabilities may be grouped based on their determined degrees of similarity to one another. This data may be used to generate an attack graph describing exploitation of vulnerabilities and grouped vulnerabilities and defining vulnerability exploit condition relationships between at least one origin and at least one target. The attack graph may be analyzed using a k-zero day metric function to determine a safety level.

K-zero day safety

An attack graph analysis tool that includes a network configuration information input module, a domain knowledge input module, a network configuration information storage module, a domain knowledge storage module, and a result generation module. The network configuration information input module inputs network configuration information. The domain knowledge input module inputs domain knowledge for the network. The network configuration information storage module stores network configuration information in a network database table. The domain knowledge storage module stores the domain knowledge in an exploit database table. The result generation module generates a result using the network database table and exploit database table. The result may be generated in response to a query to a database management system that has access to the network database table and exploit database table. The network may be reconfigured to decrease the likelihood of future attacks using the attack information learned from the result.

Growing community of inventors

Montreal, Canada

Lingyu Wang