Trends and Challenges in Network Covert Channels Countermeasures

Author:

Caviglione LucaORCID

Abstract

Network covert channels are increasingly used to endow malware with stealthy behaviors, for instance to exfiltrate data or to orchestrate nodes of a botnet in a cloaked manner. Unfortunately, the detection of such attacks is difficult as network covert channels are often characterized by low data rates and defenders do not know in advance where the secret information has been hidden. Moreover, neutralization or mitigation are hard tasks, as they require to not disrupt legitimate flows or degrade the quality perceived by users. As a consequence, countermeasures are tightly coupled to specific channel architectures, leading to poorly generalizable and often scarcely scalable approaches. In this perspective, this paper investigates trends and challenges in the development of countermeasures against the most popular network covert channels. To this aim, we reviewed the relevant literature by considering approaches that can be effectively deployed to detect general injection mechanisms or threats observed in the wild. Emphasis has been put on enlightening trajectories that should be considered when engineering mitigation techniques or planning the research to face the increasing wave of information-hiding-capable malware. Results indicate that many works are extremely specialized and an effective strategy for taming security risks caused by network covert channels may benefit from high-level and general approaches. Moreover, mechanisms to prevent the exploitation of ambiguities should be already considered in early design phases of both protocols and services.

Funder

Horizon 2020 Framework Programme

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 41 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Case Study on the Detection of Hash-Chain-based Covert Channels Using Heuristics and Machine Learning;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30

2. How to Circumvent and Beat the Ransomware in Android Operating System—A Case Study of Locker.CB!tr;Electronics;2024-06-06

3. Detecting Malicious Devices in IPSEC Traffic with IPv4 Steganography;Applied Sciences;2024-05-05

4. Network Covert channels;Steganography - The Art of Hiding Information [Working Title];2024-04-03

5. Recent Advances in Steganography;Steganography - The Art of Hiding Information [Working Title];2024-03-14

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3