Leveraging a Music Streaming Platform in Establishing a Novel Storage Covert Channel

Egbert, Connor; Alhenaki, Fawaz; Johnson, Daryl

doi:10.1109/lcn48667.2020.9314836

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…In their method, they used the Spotify API to create a playlist where the first word of each song in a playlist created a message. Their second implementation used hexadecimal characters embedded in the track ID to send a message [5]. Compared to previous work, we have used different methods to create a novel covert channel using Spotify.…”

Section: Related Workmentioning

confidence: 99%

Covert Communications via Spotify Playlists

Casalnova¹,

Gasper²,

Lombardi³

et al. 2022

World Congress on Electrical Engineering and Computer Systems and Science

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In this paper, we utilize a music streaming platform called Spotify to create two distinct covert channels. The usage for these covert channels is based on the ability for various users to access publicly available playlists. Users can use these playlists to send and receive covert messages. The first method uses the first letter of an album name to construct a message, and the second uses song's explicit tags to create binary messages. We concluded that these covert channels were successful. This is because they could send messages with adequate obscurity that outside actors would not be privy to the covert message contained.

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Section: Related Workmentioning

confidence: 99%

Covert Communications via Spotify Playlists

Casalnova¹,

Gasper²,

Lombardi³

et al. 2022

World Congress on Electrical Engineering and Computer Systems and Science

Self Cite

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“…Online streaming replaces the purchase of Compact Disc-CDs, and podcasts come and take the place of radio. In recent years, more and more people are changing their habits in the music industry because we are in the middle of rapid development [ 1 ]. The ability to listen to music directly on the mobile via the Internet, wherever we are, surpasses in ease any other method.…”

Section: Introductionmentioning

confidence: 99%

Privacy Leaks Protection in Music Streaming Services Using an Intelligent Permissions Management System

Wang

2022

Computational Intelligence and Neuroscience

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A security violation is referred to as a personal data breach when it leads to unintentional and unlawful destruction, loss, alteration, unauthorized disclosure, or access to personal data that has been communicated, stored, or otherwise processed in some other manner. Based on the principles of information security, we can define a breach of confidentiality as the unauthorized or accidental disclosure or access to personal data, a breach of integrity as the unauthorized or accidental alteration of personal data, and a breach of availability as the unauthorized or accidental loss of access to or destruction of personal data. This paper suggests designing an intelligent consensus policy management system based on the Markov chain approach. It is a novel system that would analyze the present status of the consensus elements for future development and anticipates the possibility of possible breaches of sensitive personal data. The evaluation of the proposed strategy is based on a policy scenario that involves a hypothetical consensus and a data breach of sensitive information to music streaming services.

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“…One of the current challenges associated with the pandemic is the massive increase in content consumption through pay-TV and other streaming services. Users are forced to isolate themselves and have trapped many people at home [1]. From the rst day of the enforcement of the measures, the music platforms available on the market and platforms for streaming content saw an increase in the number of their subscribers and the content they consume.…”

Section: Introductionmentioning

confidence: 99%

Cyberattacks Defense in Digital Music Streaming Platforms by Mobile Distributed Machine Learning

Fan

2022

Computational Intelligence and Neuroscience

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Given the massive popularity of digital music industry repositories and their corresponding targeting by cybercriminals, this paper presents an intelligent model for cyberattacks defense in digital music streaming platforms by mobile distributed machine learning. The basic idea of machine learning is to use large data sets to create a model that responds well to inputs it has never processed before. With the increase in data volume and complexity of models, it becomes increasingly challenging to complete machine learning processes in a single machine. Distributed ML was developed to solve this problem, and a standard procedure is completed through the collaboration of multiple servers. With the evolution of mobile devices and the increase in their number, it is possible to create an integrated and compact mobile distributed machine learning (MDML) system that could reduce the workload of servers. A distributed logit polynomial function model is proposed, which is used to model options in distributed binary regression accounting units, which are of low complexity and high stability in noisy environments.

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Leveraging a Music Streaming Platform in Establishing a Novel Storage Covert Channel

Cited by 3 publications

References 10 publications

Covert Communications via Spotify Playlists

Covert Communications via Spotify Playlists

Privacy Leaks Protection in Music Streaming Services Using an Intelligent Permissions Management System

Cyberattacks Defense in Digital Music Streaming Platforms by Mobile Distributed Machine Learning

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