On the security of machine learning in malware c&c detection: A survey
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 …
trends and anecdotal evidence show, preventing these attacks, regardless of their …
Measuring and modeling the label dynamics of online {Anti-Malware} engines
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 …
used by researchers for malware annotation and system evaluation. Since different engines …
Opening the blackbox of virustotal: Analyzing online phishing scan engines
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 …
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
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 …
of networked embedded devices. There is a strong need to develop suitable and …
The dropper effect: Insights into malware distribution with downloader graph analytics
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 …
malicious programs to hosts around the world. At the heart of all the malware delivery …
A lustrum of malware network communication: Evolution and insights
Both the operational and academic security communities have used dynamic analysis
sandboxes to execute malware samples for roughly a decade. Network information derived …
sandboxes to execute malware samples for roughly a decade. Network information derived …
Looking from the mirror: Evaluating {IoT} device security through mobile companion apps
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 …
due to their weak security designs. To identify these vulnerable devices, existing …
{SIGL}: Securing software installations through deep graph learning
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 …
However, recent supply-chain attacks demonstrate that application integrity must be ensured …
Bitter harvest: Systematically fingerprinting low-and medium-interaction honeypots at internet scale
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 …
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
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 …
grows, unknown malware detection with high accuracy becomes more and more …