Granted Patent B2

US 12,401,688 · App. 18/841,556 · Granted Aug 26, 2025

Inventors: Tae Sung Kim (Chungcheongbuk-do, KR); Soonil Hwang (Chungcheongbuk-do, KR)

Assignee: CHUNGBUK NATIONAL UNIVERSITY INDUSTRY-ACADEMIC COOPERATION FOUNDATION

H04L63/1483H04L63/1425

Abstract

Claims (42)

1. A method for determining a false flag of a cyber attack and applying a determination result in detecting cyber attacks, which is performed by a computing device having one or more processors and a memory storing one or more programs executed by the one or more processors, the method comprising:

collecting, by the computing device, cyber infringement information from an external server;

selecting, by the computing device, artifacts from the collected cyber infringement information according to a preset criterion;

classifying, by the computing device, evaluation indicators according to properties of the selected artifacts;

calculating, by the computing device, a false flag index based on the classified evaluation indicators;

determining, by the computing device, a false flag for the collected cyber infringement information based on the calculated false flag index; and

applying the determined result to the computing device that detects cyber attacks to prevent detecting false attacks,

wherein the calculating of the camouflage tactic index further comprises:

calculating, by the computing device, an attack index for each selected artifact;

calculating, by the computing device, an attack index for each evaluation indicator based on the calculated attack index for each artifact;

calculating, by the computing device, a total attack index by adding up all of the calculated attack indices for each evaluation indicator;

calculating, by the computing device, an actual attack index based on a weight according to the calculated total attack index and a correlation between the calculated evaluation indicators; and

calculating, by the computing device, the camouflage tactic index based on the calculated actual attack index,

the calculating of the attack index further comprises:

setting, by the computing device, a weight for each artifact by assigning a preset weight to each of the selected artifacts;

calculating, by the computing device, the similarity for each artifact by comparing the previously stored artifacts and the selected artifacts; and

calculating, by the computing device, the attack index for each artifact based on the set weight for each artifact and the calculated similarity for each artifact, and

the weight according to the correlation between the evaluation indicators is a weight according to a correlation between the calculated similarity for each artifact and the classified evaluation indicators.

2. The method of claim 1 , further comprising:

providing the determination result to a user.

3. The method of claim 1 , wherein the collecting of the cyber infringement information further includes classifying the collected cyber infringement information by attacker and storing cyber infringement information for each attacker, by the computing device.

4. The method of claim 1 , wherein the artifacts are one or more of internet protocol (IP), Domain, Port, uniform resource locator (URL), C2 server (Command & Control server), Server hosting records, HTTP referrer, Log, Email address, Cryptocurrency address, Hardware Information, Encryption/decryption method, Obfuscation, Meta Data, Digital certificate, Packing, Development information, Time stamp, Region, Language, Hash value, File type, Behavior pattern, Library, Zero-day, N-day, Remote Code Execution (RCE), Privilege Escalation, Shellcode, Decoy document, Phishing & Pharming, SNS account, and Attack target.

5. The method of claim 1 , wherein the evaluation indicators are one or more of Network, Server, Host based on an infrastructure-related fundamental factor, and Anti-debugging, Development Environment, Malware, Vulnerability, Social Engineering based on an attack technique-related attack factor.

6. The method of claim 1 , wherein the calculating of the degree of similarity for each artifact further includes:

extracting, by the computing device, an artifact for a specific attacker from pre-stored artifacts for each attacker; and

comparing, by the computing device, the extracted artifacts for the specific attacker and the selected artifacts to calculate the degree of similarity for each artifact for the specific attacker.

7. The method of claim 1 , wherein the calculating of the attack index for each evaluation indicator further includes calculating, by the computing device, an attack index for each evaluation indicator by adding up the artifact attack index included in each evaluation indicator according to the classified evaluation indicator.

8. An apparatus for determining a false flag of a cyber attack and applying a determination result in detecting cyber attacks, comprising:

an information collection unit that collects cyber infringement information from an external server;

an artifact selection unit that selects artifacts from the collected cyber infringement information according to a preset criterion;

an evaluation indicator classification unit that classifies evaluation indicators according to properties of the selected artifacts;

a false flag index calculation unit that calculates a false flag index based on the classified evaluation indicators; and

a false flag determination unit configured to determine a false flag for the collected cyber infringement information based on the calculated false flag index, and apply the determined result to the computing device that detects cyber attacks to prevent detecting false attacks,

the camouflage tactic index calculation unit sets a weight for each artifact by assigning a preset weight to each of the selected artifacts, calculates the similarity for each artifact by comparing the previously stored artifacts and the selected artifacts, and calculates the attack index for each artifact based on the set weight for each artifact and the calculated similarity for each artifact, and

the weight according to the correlation between the evaluation indicators is a weight according to a correlation between the calculated similarity for each artifact and the classified evaluation indicators.

9. The apparatus of claim 8 , further comprising:

a false flag determination unit further configured to provide the determination result to a user.

10. The apparatus of claim 8 , wherein the information collection unit classifies the collected cyber infringement information by attacker and stores cyber infringement information for each attacker.

11. The apparatus of claim 8 , wherein the artifacts are one or more of internet protocol (IP), Domain, Port, uniform resource locator (URL), C2 server (Command & Control server), Server hosting records, HTTP referrer, Log, Email address, Cryptocurrency address, Hardware Information, Encryption/decryption method, Obfuscation, Meta Data, Digital certificate, Packing, Development information, Time stamp, Region, Language, Hash value, File type, Behavior pattern, Library, Zero-day, N-day, Remote Code Execution (RCE), Privilege Escalation, Shellcode, Decoy document, Phishing & Pharming, SNS account, and Attack target.

12. The apparatus of claim 8 , wherein the evaluation indicators are one or more of Network, Server, and Host based on an infrastructure-related fundamental factor, and Anti-debugging, Development Environment, Malware, Vulnerability, and Social Engineering based on an attack technique-related attack factor.

13. The apparatus of claim 8 , wherein the false flag index calculation unit extracts an artifact for a specific attacker from pre-stored artifacts for each attacker, and compares the extracted artifact for the specific attacker and the selected artifact to calculate the degree of similarity for each artifact for the specific attacker.

14. The apparatus of claim 8 , wherein the false flag index calculation unit calculates an attack index for each evaluation indicator by adding up the artifact attack index included in each evaluation indicator according to the classified evaluation indicators.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (17)