公开(公告)号：US20230422039A1

公开(公告)日：2023-12-28

申请号：US18035847

申请日：2021-11-08

Applicant: The Trustees of Princeton University

Inventor： Tanujay SAHA ,  Niraj K. JHA ,  Najwa AARAJ

IPC: H04W12/122 ,  H04L9/40 ,  G06N7/01

CPC classification number: H04W12/122 ,  H04L63/1433 ,  G06N7/01

Abstract: According to various embodiments, a method for detecting security vulnerabilities in a fifth generation core network (5GCN) is disclosed. The method includes constructing an attack graph from a plurality of regular expressions. Each regular expression corresponds to a sequence of system level operations for a known 5GCN attack. The method further includes performing a linear search on the attack graph to determine unexploited 5GCN attack vectors where path in the attack graph that does not represent a known 5GCN attack vector represents an unexploited 5GCN attack vector. The method also includes applying a trained machine learning module to the attack graph to predict new 5GCN attacks. The trained machine learning module is configured to determine a feasibility of linking unconnected nodes in the attack graph to create a new branch representing a new 5GCN vulnerability exploit.

公开(公告)号：US20230328094A1

公开(公告)日：2023-10-12

申请号：US18027765

申请日：2021-09-20

Applicant: The Trustees of Princeton University

Inventor： Jacob BROWN ,  Tanujay SAHA ,  Niraj K. JHA

IPC: H04L9/40

CPC classification number: H04L63/1433 ,  H04L63/1416 ,  H04L63/1425 ,  H04L63/1441

Abstract: According to various embodiments, a system for detecting security vulnerabilities in at least one of cyber-physical systems (CPSs) and Internet of Things (IoT) devices is disclosed. The system includes one or more processors configured to construct an attack directed acyclic graph (DAG) unique to each CPS or IoT device of the devices. The processors are further configured to generate an aggregate attack DAG from a classification of each device and a location of each device in network topology specified by a system administrator. The processors are also configured to calculate a vulnerability score and exploit risk score for each node in the aggregate attack DAG. The processors are further configured to optimize placement of defenses to reduce an adversary score of the aggregate attack DAG.