State-of-the-art survey of artificial intelligent techniques for IoT security

TA Ahanger, A Aljumah, M Atiquzzaman - Computer Networks, 2022 - Elsevier
The data protection problem concerning the Internet of Things (IoT) paradigm has drawn the
innovation community's considerable attention. Several surveys have covered different IoT …

Malicious URL detection using machine learning: A survey

D Sahoo, C Liu, SCH Hoi - arXiv preprint arXiv:1701.07179, 2017 - arxiv.org
Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …

Poisoning attacks against support vector machines

B Biggio, B Nelson, P Laskov - arXiv preprint arXiv:1206.6389, 2012 - arxiv.org
We investigate a family of poisoning attacks against Support Vector Machines (SVM). Such
attacks inject specially crafted training data that increases the SVM's test error. Central to the …

Practical evasion of a learning-based classifier: A case study

N Šrndić, P Laskov - 2014 IEEE symposium on security and …, 2014 - ieeexplore.ieee.org
Learning-based classifiers are increasingly used for detection of various forms of malicious
data. However, if they are deployed online, an attacker may attempt to evade them by …

{TESSERACT}: Eliminating experimental bias in malware classification across space and time

F Pendlebury, F Pierazzi, R Jordaney, J Kinder… - 28th USENIX security …, 2019 - usenix.org
Is Android malware classification a solved problem? Published F1 scores of up to 0.99
appear to leave very little room for improvement. In this paper, we argue that results are …

Prophiler: a fast filter for the large-scale detection of malicious web pages

D Canali, M Cova, G Vigna, C Kruegel - Proceedings of the 20th …, 2011 - dl.acm.org
Malicious web pages that host drive-by-download exploits have become a popular means
for compromising hosts on the Internet and, subsequently, for creating large-scale botnets. In …

{ZOZZLE}: Fast and precise {In-Browser}{JavaScript} malware detection

C Curtsinger, B Livshits, B Zorn, C Seifert - 20th USENIX Security …, 2011 - usenix.org
JavaScript malware-based attacks account for a large fraction of successful mass-scale
exploitation happening today. Attackers like JavaScript-based attacks because they can be …

Analyzing and defending against web-based malware

J Chang, KK Venkatasubramanian, AG West… - ACM Computing Surveys …, 2013 - dl.acm.org
Web-based malware is a growing threat to today's Internet security. Attacks of this type are
prevalent and lead to serious security consequences. Millions of malicious URLs are used …

Spotless sandboxes: Evading malware analysis systems using wear-and-tear artifacts

N Miramirkhani, MP Appini, N Nikiforakis… - … IEEE Symposium on …, 2017 - ieeexplore.ieee.org
Malware sandboxes, widely used by antivirus companies, mobile application marketplaces,
threat detection appliances, and security researchers, face the challenge of environment …

[PDF][PDF] Detection of malicious pdf files based on hierarchical document structure

N Šrndic, P Laskov - Proceedings of the 20th annual network & distributed …, 2013 - Citeseer
Malicious PDF files remain a real threat, in practice, to masses of computer users, even after
several high-profile security incidents. In spite of a series of a security patches issued by …