International Business Machines Corporation

Indiana University

Yangyi Chen

Marc Philippe Stoecklin

Douglas Lee Schales

Reiner Sailer

Josyula R Rao

Xin Hu

Stefan Berger

XiaoFeng Wang

Bo Peng

Haixu Tang

Dimitrios Pendarakis

Dimitrious Pendarakis

A method includes collecting system calls and call parameters invoked by monitored applications for target computer systems. The system calls and call parameters are received from operating system kernels on the plurality of target computer systems. Sequences of systems calls and call parameters of the monitored applications are correlated among different target computer systems to deduce malicious activities. Remedial action(s) are performed in response to malicious activities being deduced as being malicious by the correlating. Another method includes determining that network activity at a specific time is deemed to be suspicious. Using IP addresses involved in the suspicious network activity, computer system(s) are determined that are sources of the suspicious network activity. Based on the specific time and the determined computer system(s), application(s) are determined that are executing on the determined computer system(s) that are causing the suspicious network activity. Remedial action(s) are performed for the determined computer system(s).

Computer implemented techniques for detecting, investigating and remediating security violations to IT infrastructure

System and methods are provided for performing privacy-preserving, high-performance, and scalable DNA read mapping on hybrid clouds including a public cloud and a private cloud. The systems and methods offer strong privacy protection and have the capacity to process millions of reads and allocate most of the workload to the public cloud at a small overall cost. The systems and methods perform seeding on the public cloud using keyed hash values of individual sequencing reads' seeds and then extend matched seeds on the private cloud. The systems and methods are designed to move the workload of read mapping from the extension stage to the seeding stage, thereby ensuring that the dominant portion of the overhead is shouldered by the public cloud.

Secure and scalable mapping of human sequencing reads on hybrid clouds

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Bloomington, IN, United States of America

Yangyi Chen