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 …

A survey of botnet detection based on DNS

K Alieyan, A ALmomani, A Manasrah… - Neural Computing and …, 2017 - Springer
Botnet is a thorny and a grave problem of today's Internet, resulting in economic damage for
organizations and individuals. Botnet is a group of compromised hosts running malicious …

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 …

Detection of malicious web activity in enterprise computer networks

AM Oprea, Z Li, R Norris, KD Bowers - US Patent 9,838,407, 2017 - Google Patents
A processing device in one embodiment comprises a processor coupled to a memory and is
configured to obtain internal log data of a computer network of an enterprise, to extract …

Poirot: Aligning attack behavior with kernel audit records for cyber threat hunting

SM Milajerdi, B Eshete, R Gjomemo… - Proceedings of the …, 2019 - dl.acm.org
Cyber threat intelligence (CTI) is being used to search for indicators of attacks that might
have compromised an enterprise network for a long time without being discovered. To have …

From {Throw-Away} traffic to bots: Detecting the rise of {DGA-Based} malware

M Antonakakis, R Perdisci, Y Nadji… - 21st USENIX Security …, 2012 - usenix.org
Many botnet detection systems employ a blacklist of known command and control (C&C)
domains to detect bots and block their traffic. Similar to signature-based virus detection, such …

Identifying encrypted malware traffic with contextual flow data

B Anderson, D McGrew - Proceedings of the 2016 ACM workshop on …, 2016 - dl.acm.org
Identifying threats contained within encrypted network traffic poses a unique set of
challenges. It is important to monitor this traffic for threats and malware, but do so in a way …

Iotfinder: Efficient large-scale identification of iot devices via passive dns traffic analysis

R Perdisci, T Papastergiou, O Alrawi… - 2020 IEEE european …, 2020 - ieeexplore.ieee.org
Being able to enumerate potentially vulnerable IoT devices across the Internet is important,
because it allows for assessing global Internet risks and enables network operators to check …

Exposure: A passive dns analysis service to detect and report malicious domains

L Bilge, S Sen, D Balzarotti, E Kirda… - ACM Transactions on …, 2014 - dl.acm.org
A wide range of malicious activities rely on the domain name service (DNS) to manage their
large, distributed networks of infected machines. As a consequence, the monitoring and …

Beehive: Large-scale log analysis for detecting suspicious activity in enterprise networks

TF Yen, A Oprea, K Onarlioglu, T Leetham… - Proceedings of the 29th …, 2013 - dl.acm.org
As more and more Internet-based attacks arise, organizations are responding by deploying
an assortment of security products that generate situational intelligence in the form of logs …