TY - GEN
T1 - Attack graph obfuscation
AU - Polad, Hadar
AU - Puzis, Rami
AU - Shapira, Bracha
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2018/5/3
Y1 - 2018/5/3
N2 - Before executing an attack, adversaries usually explore the victim’s network in an attempt to infer the network topology and identify vulnerabilities in the victim’s servers and personal computers. In this research, we examine the effects of adding fake vulnerabilities to a real enterprise network to verify the hypothesis that the addition of such vulnerabilities will serve to divert the attacker and cause the adversary to perform additional activities while attempting to achieve its objectives. We use the attack graph to model the problem of an attacker making its way towards the target in a given network. Our results show that adding fake vulnerabilities forces the adversary to invest a significant amount of effort, in terms of time, exploitability cost, and the number of attack footprints within the network during the attack.
AB - Before executing an attack, adversaries usually explore the victim’s network in an attempt to infer the network topology and identify vulnerabilities in the victim’s servers and personal computers. In this research, we examine the effects of adding fake vulnerabilities to a real enterprise network to verify the hypothesis that the addition of such vulnerabilities will serve to divert the attacker and cause the adversary to perform additional activities while attempting to achieve its objectives. We use the attack graph to model the problem of an attacker making its way towards the target in a given network. Our results show that adding fake vulnerabilities forces the adversary to invest a significant amount of effort, in terms of time, exploitability cost, and the number of attack footprints within the network during the attack.
UR - http://www.scopus.com/inward/record.url?scp=85021700054&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-60080-2_20
DO - 10.1007/978-3-319-60080-2_20
M3 - Conference contribution
AN - SCOPUS:85021700054
SN - 9783319600796
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 269
EP - 287
BT - Cyber Security Cryptography and Machine Learning - 1st International Conference, CSCML 2017, Proceedings
A2 - Dolev, Shlomi
A2 - Lodha, Sachin
PB - Springer Verlag
T2 - 1st International Conference on Cyber Security Cryptography and Machine Learning, CSCML 2017
Y2 - 29 June 2017 through 30 June 2017
ER -