Columbia University

Sri International

Gabriela F Ciocarlie

Angelos D Keromytis

Salvatore J Stolfo

Angelos Stavrou

Janak Parekh

Joseph Sherrick

Vanessa Frias-Martinez

Michael E Locasto

Karim Eldefrawy

Tancrede Lepoint

Tancrède Lepoint

Dejan Jovanovic

Ulf E Lindqvist

Prashant Anantharaman

Matteo Campanelli

Chien-Ying Chen

Ioannis Agadakos

Bogdan Copos

Matthew Filippone

Cherita Corbett

Monowar Hasan

A method, apparatus and system for providing controlled access to data in a distributed computing environment include storing received data to be accessed via the distributed computing environment in at least one storage device, generating at least one integrity data structure identifying at least a storage location of at least a respective portion of the stored data, storing the generated at least one integrity data structure in a block of a blockchain, encrypting the at least one integrity data structure in the block of the blockchain, and selectively providing at least a portion of at least one decryption key for decrypting the encrypted at least one integrity data structure to enable access to the respective portion of the stored data for which the at least one integrity data structure is generated. Additionally, the stored data can be encrypted and a decryption key can be provided for decrypting the stored data.

Smart privacy and controlled exposure on blockchains

A method, apparatus and system for determining a weakness or risk for devices of an Internet-of-things (IoT) network include determining a representation of a physical environment of the IoT network and expected physical and cyber interactions between the devices of the IoT network based at least in part on operating characteristics of the devices of the IoT network, monitoring the physical environment and actual interactions between the devices to generate a network model including at least one of uncharacteristic physical or cyber interaction paths between the devices, based on the determined network model, determining at least one weakness or risk of at least one of the IoT network or of at least one of the devices, and providing a metric of security of at least one of the IoT network or of at least one of the devices based on at least one of the determined weakness or risk.

Modeling cyber-physical attack paths in the internet-of-things

Intrusion detection systems and methods monitor legal control messages in an operational control system to detect subtly malicious sequences of control messages with undesirable emergent effects on devices in the operational control system. A message provenance component may investigate system-level correlations between messages rather than detecting if individual messages are anomalous. A semantic fuzzing component may search, based on the operational effect of candidate message sequences, the space of legal messages for sequences that cause actual harm. Behavior oracles may be used to test message sequences to identify sequences that induce drift towards a failure state. The intrusion detection system is able to prevent harm and disruption arising from control messages that individually appear legitimate and benign but that, in combination with other messages, can cause undesirable outcomes.

Intrusion detection via semantic fuzzing and message provenance

Methods, media, and systems for securing communications between a first node and a second node are provided. In some embodiments, methods for securing communication between a first node and a second node are provided. The methods comprising: receiving at least one model of behavior of the second node at the first node; and authorizing the first node to receive traffic from the second node based on the difference between the at least one model of behavior of the second node and at least one model of behavior of the first node.

Methods, media, and systems for securing communications between a first node and a second node

Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and generating anomaly detection models are provided. In some embodiments, methods for sanitizing anomaly detection models are provided. The methods including: receiving at least one abnormal anomaly detection model from at least one remote location; comparing at least one of the at least one abnormal anomaly detection model to a local normal detection model to produce a common set of features common to both the at least one abnormal anomaly detection model and the local normal detection model; and generating a sanitized normal anomaly detection model by removing the common set of features from the local normal detection model.

Systems, methods, and media for generating sanitized data, sanitizing anomaly detection models, and/or generating sanitized anomaly detection models

Systems, methods, and media for recovering an application from a fault or an attack are disclosed herein. In some embodiments, a method is provided for enabling a software application to recover from a fault condition. The method includes specifying constrained data items and assigning a set of repair procedures to the constrained data items. The method further includes detecting a fault condition on the constrained data items during execution of the software application, which triggers at least one repair procedure. The triggered repair procedures are executed and the execution of the software application is restored. In some embodiments, the restoring comprises providing memory rollback to a point of execution of the software application before the fault condition was detected.

Systems, methods, and media for recovering an application from a fault or attack

Growing community of inventors

New York, NY, United States of America

Gabriela F Ciocarlie