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Ege Tekiner

dblp:264/0000 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 2 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Malware analysis · 88% Systems and software security · 12%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Malware analysis › malware detection
cryptojacking detection
1.122022
A Lightweight IoT Cryptojacking Detection Mechanism in Heterogeneous Smart Home Networks · NDSS 2022
MINOS: A Lightweight Real-Time Cryptojacking Detection System · NDSS 2021

Methods — techniques the papers use, named apart from their topics

lightweight real-time detection · 0.5
YearPublicationVenuePosition
2022 A Lightweight IoT Cryptojacking Detection Mechanism in Heterogeneous Smart Home Networks
Ege Tekiner, Abbas Acar, A. Selcuk Uluagac
NDSS1
2021 SoK: Cryptojacking Malware
abstract
Emerging blockchain and cryptocurrency-based technologies are redefining the way we conduct business in cyberspace. Today, a myriad of blockchain and cryp-tocurrency systems, applications, and technologies are widely available to companies, end-users, and even malicious actors who want to exploit the computational resources of regular users through cryptojacking malware. Especially with ready-to-use mining scripts easily provided by service providers (e.g., Coinhive) and untraceable cryptocurrencies (e.g., Monero), cryptojacking malware has become an indispensable tool for attackers. Indeed, the banking industry, major commercial websites, government and military servers (e.g., US Dept. of Defense), online video sharing platforms (e.g., Youtube), gaming platforms (e.g., Nintendo), critical infrastructure resources (e.g., routers), and even recently widely popular remote video conferencing/meeting programs (e.g., Zoom during the Covid-19 pandemic) have all been the victims of powerful cryptojacking malware campaigns. Nonetheless, existing detection methods such as browser extensions that protect users with blacklist methods or antivirus programs with different analysis methods can only provide a partial panacea to this emerging crypto-jacking issue as the attackers can easily bypass them by using obfuscation techniques or changing their domains or scripts frequently. Therefore, many studies in the literature proposed cryptojacking malware detection methods using various dynamic/behavioral features. However, the literature lacks a systemic study with a deep understanding of the emerging cryptojacking malware and a comprehensive review of studies in the literature. To fill this gap in the literature, in this SoK paper, we present a systematic overview of cryptojacking malware based on the information obtained from the combination of academic research papers, two large cryptojacking datasets of samples, and 45 major attack instances. Finally, we also present lessons learned and new research directions to help the research community in this emerging area.
Ege Tekiner, Abbas Acar, A. Selcuk Uluagac, Engin Kirda, Ali Aydin Selçuk
EuroS&P1
2021 MINOS: A Lightweight Real-Time Cryptojacking Detection System
Faraz Naseem Naseem, Ahmet Aris, Leonardo Babun, Ege Tekiner, A. Selcuk Uluagac
NDSS4