You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
More and more people are regularly using mobile and battery-powered handsets, such as smartphones and tablets. At the same time, thanks to the technological innovation and to the high user demands, those devices are integrating extensive functionalities and developers are writing battery-draining apps, which results in a surge of energy consumption of these devices. This scenario leads many people to often look for opportunities to charge their devices at public charging stations: the presence of such stations is already prominent around public areas such as hotels, shopping malls, airports, gyms and museums, and is expected to significantly grow in the future. While most of the time the power comes for free, there is no guarantee that the charging station is not maliciously controlled by an adversary, with the intention to exfiltrate data from the devices that are connected to it. In this paper, we illustrate for the first time how an adversary could leverage a maliciously controlled charging station to exfiltrate data from the smartphone via a USB charging cable (i.e., without using the data transfer functionality), controlling a simple app running on the device, and without requiring any permission to be granted by the user to send data out of the device. We show the feasibility of the proposed attack through a prototype implementation in Android, which is able to send out potentially sensitive information, such as IMEI, contacts' phone number, and pictures.

Cited Abstract(s):
[1]: This paper presents a large, 4-week study of more than 4000 people to assess their smartphone charging habits to identify timeslots suitable for opportunistic data uploading and power intensive operations on such devices, as well as opportunities to provide interventions to support better charging behavior. The paper provides an overview of our study and how it was conducted using an online appstore as a software deployment mechanism, and what battery information was collected. We then describe how people charge their smartphones, the implications on battery life and energy usage, and discuss how to improve users' experience with battery life.

[2]: 

[3]: Modern smartphones that implement permission-based security mechanisms suffer from attacks by colluding applications. Users are not made aware of possible implications of application collusion attacks---quite the contrary---on existing platforms, users are implicitly led to believe that by approving the installation of each application independently, they can limit the damage that an application can cause. We implement and analyze a number of covert and overt communication channels that enable applications to collude and therefore indirectly escalate their permissions. Furthermore, we present and implement a covert channel between an installed application and a web page loaded in the system browser. We measure the throughput of all these channels as well as their bit-error rate and required synchronization for successful data transmission. The measured throughput of covert channels ranges from 3.7 bps to 3.27 kbps on a Nexus One phone and from 0.47 bps to 4.22 kbps on a Samsung Galaxy S phone; such throughputs are sufficient to efficiently exchange users' sensitive information (e.g., GPS coordinates or contacts). We test two popular research tools that track information flow or detect communication channels on mobile platforms, and confirm that even if they detect some channels, they still do not detect all the channels and therefore fail to fully prevent application collusion. Attacks using covert communication channels remain, therefore, a real threat to smartphone security and an open problem for the research community.

[4]: We explore the threat of smartphone malware with access to on-board sensors, which opens new avenues for illicit collection of private information. While existing work shows that such “sensory malware” can convey raw sensor data (e.g., video and audio) to a remote server, these approaches lack stealthiness, incur significant communication and computation overhead during data transmission and processing, and can easily be defeated by existing protections like denying installation of applications with access to both sensitive sensors and the network. We present Soundcomber, a Trojan with few and innocuous permissions, that can extract a small amount of targeted private information from the audio sensor of the phone. Using targeted profiles for context-aware analysis, Soundcomber intelligently “pulls out” sensitive data such as credit card and PIN numbers from both toneand speech-based interaction with phone menu systems. Soundcomber performs efficient, stealthy local extraction, thereby greatly reducing the communication cost for delivering stolen data. Soundcomber automatically infers the destination phone number by analyzing audio, circumvents known security defenses, and conveys information remotely without direct network access. We also design and implement a defensive architecture that foils Soundcomber, identify new covert channels specific to smartphones, and provide a video demonstration

[5]: Power side channel is a very important category of side channels, which can be exploited to steal confidential information from a computing system by analyzing its power consumption. In this paper, we demonstrate the existence of various power side channels on popular mobile devices such as smartphones. Based on unprivileged power consumption traces, we present a list of real-world attacks that can be initiated to identify running apps, infer sensitive UIs, guess password lengths, and estimate geo-locations. These attack examples demonstrate that power consumption traces can be used as a practical side channel to gain various confidential information of mobile apps running on smartphones. Based on these power side channels, we discuss possible exploitations and present a general approach to exploit a power side channel on an Android smartphone, which demonstrates that power side channels pose imminent threats to the security and privacy of mobile users. We also discuss possible countermeasures to mitigate the threats of power side channels.
A covert channel can be considered as a secret channel used to exfiltrate information from a secured environment in an undetected manner. [1] investigated the existence of different covert channels that can be used to communicate between two malicious applications. They examined the common resources (such as battery) shared between two malicious applications and how they could be exploited for covert communication. Similar studies presented in [2] [3] [4] [5] exploited unknown covert channels in malicious and clean applications to leak out private information.