Multi-factor deception management and detection for malicious actions in a computer network

• US 10,623,442 B2
• Filed: 04/02/2018
• Issued: 04/14/2020
• Est. Priority Date: 06/08/2015
• Status: Active Grant

• Current Assignee: illusive networks LTD.
• Original Assignee: illusive networks LTD.
• Inventors: Touboul, Shlomo, Levin, Hanan, Roubach, Stephane, Mischari, Assaf, Ben David, Itai, Avraham, Itay, Ozer, Adi, Kazaz, Chen, Israeli, Ofer, Vingurt, Olga, Gareh, Liad, Grimberg, Israel, Cohen, Cobby, Sultan, Sharon, Kubovsky, Matan
• Primary Examiner(s): Potratz, Daniel B
• Application Number:
  US15/942,593
• Publication Number:
  US 20180234438A1
• Time in Patent Office: 743 Days
• CPC Class Codes: G06F 21/55 Detecting local intrusion or implementing counter-measures
• CPC Class Codes: G06F 21/554 involving event detection and direct action
• CPC Class Codes: G06F 21/56 Computer malware detection or handling, e.g. anti-virus arrangements
• CPC Class Codes: G06F 21/577 Assessing vulnerabilities and evaluating computer system security
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 2463/146 Tracing the source of attacks
• CPC Class Codes: H04L 63/10 for controlling access to devices or network resources
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 63/1433 Vulnerability analysis
• CPC Class Codes: H04L 63/1441 Countermeasures against malicious traffic countermeasures against attacks on cryptographic mechanisms H04L9/002
• CPC Class Codes: H04L 63/1491 using deception as countermeasure, e.g. honeypots, honeynets, decoys or entrapment
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227

Abstract

A network surveillance method to detect attackers, including planting one or more honeytokens in one or more resources in a network of computers in which users access the resources in the network based on credentials, wherein a honeytoken is an object in memory or storage of a first resource that may be used by an attacker to access a second resource using decoy credentials, including planting a first honeytoken in a first resource, R₁, used to access a second resource, R₂, using first decoy credentials, and planting a second honeytoken in R₁, used to access a third resource, R₃, using second decoy credentials, and alerting that an attacker is intruding the network only in response to both (i) an attempt to access R₂ using the first decoy credentials, and (ii) a subsequent attempt to access R₃ using the second decoy credentials.

Claims

1. A network surveillance method to detect attackers, comprising:

planting one or more honeytokens in one or more resources in a network of computers in which users access the resources in the network based on credentials, wherein a honeytoken is an object in memory or storage of a first resource that may be used by an attacker to access a second resource using decoy credentials, comprising;

planting a first honeytoken in a first resource, R₁, used to access a second resource, R₂, using first decoy credentials; and

planting a second honeytoken in R₁, used to access a third resource, R₃, using second decoy credentials; and

alerting that an attacker is intruding the network only in response to both (i) an attempt to access R₂ using the first decoy credentials, and (ii) a subsequent attempt to access R₃ using the second decoy credentials.

2. The method of claim 1 wherein credentials include passwords for accessing resources in the network, and wherein the first and second decoy credentials include respective hash versions of first and second passwords.

3. The method of claim 1 wherein credentials of honeytokens include members of the group consisting of user credentials, FTP server credentials and SSH server credentials.