Security and Communication Networks

Emerging and Unconventional: New Attacks and Innovative Detection Techniques


Status
Published

Lead Editor

1National Research Council of Italy (CNR), Genoa, Italy

2Warsaw University of Technology, Warsaw, Poland

3Worms University of Applied Sciences, Worms, Germany

4Murdoch University, Perth, Australia


Emerging and Unconventional: New Attacks and Innovative Detection Techniques

Description

In the last years, advancements of the information and communication technologies have spawned a variety of innovative paradigms, such as cloud and fog computing, the Internet of Things (IoT), or complex vehicle-to-vehicle frameworks. As a consequence, the cybersecurity panorama is now getting populated with complex, emerging, and unconventional attacks, which require deep investigation and proper understanding. For example, the diffusion of online social networks brought social engineering to the next level, while IoT led to a completely new set of hazards also endangering the user at a physical level. Modern threats also exploit a variety of advanced methods to increase their stealthiness in order to remain unnoticed for long periods, as well as reduce the effectiveness of many digital forensics techniques and detection tools.

Therefore, new and emerging technologies changed the modern cybersecurity landscape, which nowadays is populated by novel attacks and also requires innovative detection and prevention methods. In this perspective, the special issue aims at investigating the most advanced and innovative forms of attacks and scenarios, for instance, considering automotive or building automation settings. To complete the picture, a relevant attention will be given to works dealing with innovative forms of detection and forensics analysis, which are mandatory to counteract sophisticated malware able to hide or take advantage of unconventional and complex scenarios. This issue accepts high quality papers containing novel original research results and review articles of exceptional merit covering the most cutting-edge cybersecurity threats and countermeasures.

Potential topics include but are not limited to the following:

  • Novel advanced and persistent threats aiming at automotive and smart buildings/cities
  • Security issues and profiling hazards in smart buildings/cities
  • IoT and device specific attacks, for example, battery drain attacks or attacks on IoT routing protocols
  • Hazards taking advantage from social media, for example, social bots and new social engineering attacks
  • Information hiding threats to counteract forensics tools and analysis
  • Network steganography for data exfiltration and new information-hiding-capable threats
  • Energy-based detection of slow and hidden attacks, including low-attention rising threats for mobile and handheld devices
  • Scalable countermeasures for preventing steganography in big-data-like sources
  • Novel threats targeting vehicles and cloud and software defined networking technologies
  • Bioinspired attacks and detection mechanisms
  • Ransomware: novel trends, characteristics, and detection
  • Moving Target Defense (MTD) solutions against infections

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 9672523
  • - Editorial

Emerging and Unconventional: New Attacks and Innovative Detection Techniques

Luca Caviglione | Wojciech Mazurczyk | ... | Sebastian Zander
  • Special Issue
  • - Volume 2018
  • - Article ID 7251750
  • - Research Article

Leverage Website Favicon to Detect Phishing Websites

Kang Leng Chiew | Jeffrey Soon-Fatt Choo | ... | Kelvin S. C. Yong
  • Special Issue
  • - Volume 2018
  • - Article ID 4216240
  • - Research Article

Leveraging KVM Events to Detect Cache-Based Side Channel Attacks in a Virtualization Environment

Ady Wahyudi Paundu | Doudou Fall | ... | Youki Kadobayashi
  • Special Issue
  • - Volume 2017
  • - Article ID 5960307
  • - Research Article

Detecting Web-Based Botnets Using Bot Communication Traffic Features

Fu-Hau Hsu | Chih-Wen Ou | ... | Po-Ching Lin
  • Special Issue
  • - Volume 2017
  • - Article ID 4184196
  • - Research Article

Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

Yang Yu | Jun Long | Zhiping Cai
  • Special Issue
  • - Volume 2017
  • - Article ID 1723658
  • - Research Article

Remotely Exploiting AT Command Attacks on ZigBee Networks

Ivan Vaccari | Enrico Cambiaso | Maurizio Aiello
  • Special Issue
  • - Volume 2017
  • - Article ID 7892182
  • - Research Article

Predictive Abuse Detection for a PLC Smart Lighting Network Based on Automatically Created Models of Exponential Smoothing

Tomasz Andrysiak | Łukasz Saganowski | Piotr Kiedrowski
Security and Communication Networks
 Journal metrics
Acceptance rate30%
Submission to final decision92 days
Acceptance to publication48 days
CiteScore1.810
Impact Factor1.376
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