Abstract: One embodiment of the present invention provides a system for privacy-preserving aggregation of encrypted data. During operation, the system distributes secret keys to a plurality of devices. The system receives at least a pair of encrypted vectors from each device of a subset of the plurality of devices. One of the encrypted vectors is associated with a set of numerical values and the other encrypted vector is associated with corresponding square values of the set of numerical values. Each pair of encrypted vectors is encrypted using a respective secret key distributed to a device of the plurality of devices. The system then computes, for each pair of encrypted vector elements associated with a numerical value and a square of the numerical value, a mean and variance of a probability density function. The system then generates a plurality of probability density functions based on the computed mean and variance values.

Abstract: One embodiment of the present invention provides a system to facilitate collaboration for mitigating network threats. During operation, the system receives encrypted data sets from a plurality of entities. The data sets including data describing threats to network security. The system performs privacy-preserving operations on the encrypted data sets, such as private set intersection. The system then computes one or more metrics based on results of the private set intersection computations. The system may generate a similarity matrix based on the one or more metrics, and returns one or more similarity values from the similarity matrix to one or more entities of the plurality of entities.

Abstract: One embodiment of the present invention provides a system for stable selection of collaborating partners for exchanging security data. During operation, the system receives vectors of collaboration values from a plurality of entities. A collaboration value is a measure of an expected benefit of collaborating with a respective entity. The system sorts each of the vectors by the collaboration values of the respective vector. The system then determines matching entities given a number of partners wanted by each organization in N. The system may add matching entities to lists of collaborating partners given the number of partners wanted by each organization in N. Subsequently, the system sends the lists of collaborating partners to facilitate exchanging security data with partners in the list of collaborating partners.

Abstract: One embodiment of the present invention provides a system for privacy-preserving sharing of data for secure collaboration. During operation, the system obtains a first set of data describing network events associated with one or more network addresses. Next, the system negotiates with a potential partner to determine a metric for deciding whether to share data. The potential partner is associated with a second set of data describing network events. The system then computes a value for the metric in a privacy-preserving way, based on the first set of data and the second set of data. Subsequently, the system determines whether the metric value exceeds a predetermined threshold, and, responsive to determining that the metric value exceeds the predetermined threshold, the system shares the first set of data with the potential partner, while controlling how the data should be shared to optimize benefits and risks of collaboration.