On the security of machine learning in malware c&c detection: A survey

J Gardiner, S Nagaraja - ACM Computing Surveys (CSUR), 2016 - dl.acm.org
One of the main challenges in security today is defending against malware attacks. As
trends and anecdotal evidence show, preventing these attacks, regardless of their …

Measuring and modeling the label dynamics of online {Anti-Malware} engines

S Zhu, J Shi, L Yang, B Qin, Z Zhang, L Song… - 29th USENIX Security …, 2020 - usenix.org
VirusTotal provides malware labels from a large set of anti-malware engines, and is heavily
used by researchers for malware annotation and system evaluation. Since different engines …

Opening the blackbox of virustotal: Analyzing online phishing scan engines

P Peng, L Yang, L Song, G Wang - Proceedings of the Internet …, 2019 - dl.acm.org
Online scan engines such as VirusTotal are heavily used by researchers to label malicious
URLs and files. Unfortunately, it is not well understood how the labels are generated and …

[PDF][PDF] Iotcandyjar: Towards an intelligent-interaction honeypot for iot devices

T Luo, Z Xu, X **, Y Jia, X Ouyang - Black Hat, 2017 - blackhat.com
In recent years, the emerging Internet-of-Things (IoT) has led to concerns about the security
of networked embedded devices. There is a strong need to develop suitable and …

The dropper effect: Insights into malware distribution with downloader graph analytics

BJ Kwon, J Mondal, J Jang, L Bilge… - Proceedings of the 22nd …, 2015 - dl.acm.org
Malware remains an important security threat, as miscreants continue to deliver a variety of
malicious programs to hosts around the world. At the heart of all the malware delivery …

A lustrum of malware network communication: Evolution and insights

C Lever, P Kotzias, D Balzarotti… - … IEEE Symposium on …, 2017 - ieeexplore.ieee.org
Both the operational and academic security communities have used dynamic analysis
sandboxes to execute malware samples for roughly a decade. Network information derived …

Looking from the mirror: Evaluating {IoT} device security through mobile companion apps

X Wang, Y Sun, S Nanda, XF Wang - 28th USENIX security symposium …, 2019 - usenix.org
Smart home IoT devices have increasingly become a favorite target for the cybercriminals
due to their weak security designs. To identify these vulnerable devices, existing …

{SIGL}: Securing software installations through deep graph learning

X Han, X Yu, T Pasquier, D Li, J Rhee… - 30th USENIX Security …, 2021 - usenix.org
Many users implicitly assume that software can only be exploited after it is installed.
However, recent supply-chain attacks demonstrate that application integrity must be ensured …

Bitter harvest: Systematically fingerprinting low-and medium-interaction honeypots at internet scale

A Vetterl, R Clayton - 12th USENIX Workshop on Offensive Technologies …, 2018 - usenix.org
The current generation of low-and medium interaction honeypots uses off-the-shelf libraries
to provide the transport layer. We show that this architecture is fatally flawed because the …

Multi-loss siamese neural network with batch normalization layer for malware detection

J Zhu, J Jang-Jaccard, PA Watters - IEEE access, 2020 - ieeexplore.ieee.org
Malware detection is an essential task in cyber security. As the trend of malicious attacks
grows, unknown malware detection with high accuracy becomes more and more …