On the Use of Neurosymbolic AI for Defending Against Cyber Attacks

被引：0

作者：

Grov, Gudmund ^{[1
,2
]}

Halvorsen, Jonas ^{[1
]}

Eckhoff, Magnus Wiik ^{[1
,2
]}

Hansen, Bjorn Jervell ^{[1
]}

Eian, Martin ^{[3
]}

Mavroeidis, Vasileios ^{[2
]}

机构：

[1] Norwegian Def Res Estab FFI, Kjeller, Norway

[2] Univ Oslo, Oslo, Norway

[3] Mnemonic, Oslo, Norway

来源：

NEURAL-SYMBOLIC LEARNING AND REASONING, PT I, NESY 2024 | 2024年 / 14979卷

关键词：

AI; neurosymbolic AI; cyber security; incident detection and response;

D O I：

10.1007/978-3-031-71167-1_7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is generally accepted that all cyber attacks cannot be prevented, creating a need for the ability to detect and respond to cyber attacks. Both connectionist and symbolic AI are currently being used to support such detection and response. In this paper, we make the case for combining them using neurosymbolic AI. We identify a set of challenges when using AI today and propose a set of neurosymbolic use cases we believe are both interesting research directions for the neurosymbolic AI community and can have an impact on the cyber security field. We demonstrate feasibility through two proof-of-concept experiments.

引用

页码：119 / 140

页数：22

共 50 条

[31] TXAI-ADV: Trustworthy XAI for Defending AI Models against Adversarial Attacks in Realistic CIoT
Ojo, Stephen
Krichen, Moez
Alamro, Meznah A.
Mihoub, Alaeddine
ELECTRONICS, 2024, 13 (09)
[32] Defending our database against inside attacks
Scopinaro, Nicola
SURGERY FOR OBESITY AND RELATED DISEASES, 2012, 8 (06) : 814 - 814
[33] Towards Defending Connected Vehicles Against Attacks
AbdAllah, Eslam G.
Zulkernine, Mohammad
Gu, Yuan Xiang
Liem, Clifford
PROCEEDINGS OF THE FIFTH EUROPEAN CONFERENCE ON THE ENGINEERING OF COMPUTER-BASED SYSTEMS (ECBS 2017), 2017,
[34] Practical Techniques for Defending against DDoS Attacks
Chen, Eric Y.
Yonezawa, Akinori
3RD ACS/IEEE INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS, 2005, 2005,
[35] Defending Distributed Systems Against Adversarial Attacks
Su L.
Performance Evaluation Review, 2020, 47 (03): : 24 - 27
[36] Defending Against Attacks on Main Memory Persistence
Enck, William
Butler, Kevin
Richardson, Thomas
McDaniel, Patrick
Smith, Adam
24TH ANNUAL COMPUTER SECURITY APPLICATIONS CONFERENCE, PROCEEDINGS, 2008, : 65 - 74
[37] Defending against Sybil Attacks in Vehicular Platoons
Santhosh, Jesty
Sankaran, Sriram
13TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED NETWORKS AND TELECOMMUNICATION SYSTEMS (IEEE ANTS), 2019,
[38] Software protects against cyber attacks
Blume, Adrienne
HYDROCARBON PROCESSING, 2012, 91 (10): : 16 - 16
[39] Cyberspace Exercises: Defending against Malicious Cyber Actors
Bennett, Kelly
Robertson, James
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR MULTI-DOMAIN OPERATIONS APPLICATIONS V, 2023, 12538
[40] Causal Neurosymbolic AI: A Synergy Between Causality and Neurosymbolic Methods
Jaimini, Utkarshani
Henson, Cory
Sheth, Amit
IEEE INTELLIGENT SYSTEMS, 2024, 39 (03) : 13 - 19

← 1 2 3 4 5 →