Results 261 to 270 of about 503,159 (305)

An evasive attack on SNORT flowbits

2012 IEEE Network Operations and Management Symposium, 2012
The support of stateful signatures is an important feature of signature-based Network Intrusion Detection Systems (NIDSs) which permits the detection of multi-stage attacks. However, due to the difficulty to completely simulate every application protocol, several NIDS evasion techniques exploit this Achilles' heel, making the NIDS and its protected ...
Tung Tran 0002, Issam Aib, Ehab Al-Shaer, Raouf Boutaba   +3 more
openaire   +1 more source

AppCon: Mitigating Evasion Attacks to ML Cyber Detectors [PDF]

Symmetry, 2020
Adversarial attacks represent a critical issue that prevents the reliable integration of machine learning methods into cyber defense systems. Past work has shown that even proficient detectors are highly affected just by small perturbations to malicious samples, and that existing countermeasures are immature.
Giovanni Apruzzese, Mirco Marchetti, Mauro Andreolini   +2 more
exaly   +3 more sources

Adversarial mRMR against Evasion Attacks

2018 International Joint Conference on Neural Networks (IJCNN), 2018
Machine learning (ML) algorithms provide a good solution for many security sensitive applications, they themselves, however, face the threats of adversary attacks. As a key problem in machine learning, how to design robust feature selection algorithms against these attacks becomes a hot issue.
Miaomiao Wu, Yun Li
openaire   +2 more sources

Harbor attack: A pursuit-evasion game

2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2011
This paper studies a concrete pursuit-evasion game in which the evader, a.k.a. the intruder, tries to reach a harbor via a rectangular channel, while the pursuer, a.k.a. the defender, tries to stop him. Our goal is to develop insight into the nature of this game, the impact of the quality of information, and the potential evasion and defense numerical ...
Jean C. Walrand, Elijah Polak, Hoam Chung   +2 more
openaire   +2 more sources

Evasion Attacks On Svm Classifier

2019 9th International Conference on Advances in Computing and Communication (ICACC), 2019
Support Vector Machine (SVM) is one of the main classification techniques used in many security-related applications like malware detection, spam filtering, etc. To incorporate SVM into real-world security applications they must be able to cope up with the attack patterns that will lead to misclassifications. In this system, the vulnerability of SVM to
null Maria, Mikhiya James, M Mruthula, Vismaya Bhaskaran, S Asha   +4 more
openaire   +1 more source

Memory Corruption Attacks, Defenses, and Evasions

2009
The chapter introduces and describes representative defense mechanisms to protect from both basic and advanced exploitation of low-level coding vulnerabilities. Exploitation of low-level coding vulnerabilities has evolved from a basic stack-based buffer overflow with code injection to highly sophisticated attack techniques.
C. Bellettini, J.L. RRushi
openaire   +2 more sources

Learning a Secure Classifier against Evasion Attack

2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 2016
In security sensitive applications, there is a crafty adversary component which intends to mislead the detection system. The presence of an adversary component conflicts with the stationary data assumption that is a common assumption in most machine learning methods.
Zeinab Khorshidpour, Sattar Hashemi, Ali Hamzeh   +2 more
openaire   +2 more sources

Optimal Defense Strategy against Evasion Attacks

2020 16th International Conference on Mobility, Sensing and Networking (MSN), 2020
Recent detection method based on machine learning demonstrates significant advantages against varieties of network attacks, and has been widely deployed in cloud applications. However, novel attacks such as Advanced Persistent Threats (APTs) could evade detection of the intrusion detection system, which may lead to serious data leakage in cloud ...
Jiachen Wu, Jipeng Li, Yan Wang 0083, Yanru Zhang, Yingjie Zhou 0001   +4 more
openaire   +1 more source

Persistent and Evasive Attacks Uncovered

Infosecurity, 2011
APTs – and more recently AETs – have divided industry experts in opinion and often been used to scaremonger.
openaire   +1 more source

Evasion and causative attacks with adversarial deep learning

MILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM), 2017
This paper presents a novel approach to launch and defend against the causative and evasion attacks on machine learning classifiers. As the preliminary step, the adversary starts with an exploratory attack based on deep learning (DL) and builds a functionally equivalent classifier by polling the online target classifier with input data and observing ...
Yi Shi 0001, Yalin E. Sagduyu
openaire   +1 more source