A New Covert Channel Over Cellular Network Voice Channel

Smartphone security has become increasingly more significant as smartphones become a more important part of many individuals\u27 daily lives. Smartphones undergo all computer security issues; however, they also introduce a new set of security issues as various capabilities are added. Smartphone security researchers pay more attention to security issues inherited from the traditional computer security field than smartphone-related security issues. The primary network that smartphones are connected to is the cellular network, but little effort has been directed at investigating the potential security issues that could threaten this network and its end users. A new possible threat that could occur in the cellular network is introduced in this paper. This research proves the ability to use the cellular network voice channel as a covert channel that can convey covert information as speech, thus breaking the network policies. The study involves designing and implementing multiple subsystems in order to prove the theory. First, a software audio modem that is able to convert digital data into audio waves and inject the audio waves to the GSM voice channel was developed. Moreover, a user-mode rootkit was implemented in order to open the voice channels by stealthily answering the incoming voice call, thus breaking the security mechanisms of the smartphone. Multiple scenarios also were tested in order to verify the effectiveness of the proposed covert channel. The first scenario is a covert communication between two parties that intends to hide their communications by using a network that is unknown to the adversary and not protected by network security guards. The two parties communicate through the cellular network voice channel to send and receive text messages. The second scenario is a side channel that is able to leak data such as SMS or the contact of a hacked smartphone through the cellular network voice channel. The third scenario is a botnet system that uses the voice channel as command and control channel (C2). This study identifies a new potential smartphone covert channel, so the outcome should be setting countermeasures against this kind of breach

Image steganography applications for secure communication

To securely communicate information between parties or locations is not an easy task considering the possible attacks or unintentional changes that can occur during communication. Encryption is often used to protect secret information from unauthorised access. Encryption, however, is not inconspicuous and the observable exchange of encrypted information between two parties can provide a potential attacker with information on the sender and receiver(s). The presence of encrypted information can also entice a potential attacker to launch an attack on the secure communication. This dissertation investigates and discusses the use of image steganography, a technology for hiding information in other information, to facilitate secure communication. Secure communication is divided into three categories: self-communication, one-to-one communication and one-to-many communication, depending on the number of receivers. In this dissertation, applications that make use of image steganography are implemented for each of the secure communication categories. For self-communication, image steganography is used to hide one-time passwords (OTPs) in images that are stored on a mobile device. For one-to-one communication, a decryptor program that forms part of an encryption protocol is embedded in an image using image steganography and for one-to-many communication, a secret message is divided into pieces and different pieces are embedded in different images. The image steganography applications for each of the secure communication categories are discussed along with the advantages and disadvantages that the applications have over more conventional secure communication technologies. An additional image steganography application is proposed that determines whether information is modified during communication. CopyrightDissertation (MSc)--University of Pretoria, 2012.Computer Scienceunrestricte

Introductory Computer Forensics

INTERPOL (International Police) built cybercrime programs to keep up with emerging cyber threats, and aims to coordinate and assist international operations for ?ghting crimes involving computers. Although signi?cant international efforts are being made in dealing with cybercrime and cyber-terrorism, ?nding effective, cooperative, and collaborative ways to deal with complicated cases that span multiple jurisdictions has proven dif?cult in practic

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

“And all the pieces matter...” Hybrid Testing Methods for Android App's Privacy Analysis

Smartphones have become inherent to the every day life of billions of people worldwide, and they are used to perform activities such as gaming, interacting with our peers or working. While extremely useful, smartphone apps also have drawbacks, as they can affect the security and privacy of users. Android devices hold a lot of personal data from users, including their social circles (e.g., contacts), usage patterns (e.g., app usage and visited websites) and their physical location. Like in most software products, Android apps often include third-party code (Software Development Kits or SDKs) to include functionality in the app without the need to develop it in-house. Android apps and third-party components embedded in them are often interested in accessing such data, as the online ecosystem is dominated by data-driven business models and revenue streams like advertising. The research community has developed many methods and techniques for analyzing the privacy and security risks of mobile apps, mostly relying on two techniques: static code analysis and dynamic runtime analysis. Static analysis analyzes the code and other resources of an app to detect potential app behaviors. While this makes static analysis easier to scale, it has other drawbacks such as missing app behaviors when developers obfuscate the app’s code to avoid scrutiny. Furthermore, since static analysis only shows potential app behavior, this needs to be confirmed as it can also report false positives due to dead or legacy code. Dynamic analysis analyzes the apps at runtime to provide actual evidence of their behavior. However, these techniques are harder to scale as they need to be run on an instrumented device to collect runtime data. Similarly, there is a need to stimulate the app, simulating real inputs to examine as many code-paths as possible. While there are some automatic techniques to generate synthetic inputs, they have been shown to be insufficient. In this thesis, we explore the benefits of combining static and dynamic analysis techniques to complement each other and reduce their limitations. While most previous work has often relied on using these techniques in isolation, we combine their strengths in different and novel ways that allow us to further study different privacy issues on the Android ecosystem. Namely, we demonstrate the potential of combining these complementary methods to study three inter-related issues: • A regulatory analysis of parental control apps. We use a novel methodology that relies on easy-to-scale static analysis techniques to pin-point potential privacy issues and violations of current legislation by Android apps and their embedded SDKs. We rely on the results from our static analysis to inform the way in which we manually exercise the apps, maximizing our ability to obtain real evidence of these misbehaviors. We study 46 publicly available apps and find instances of data collection and sharing without consent and insecure network transmissions containing personal data. We also see that these apps fail to properly disclose these practices in their privacy policy. • A security analysis of the unauthorized access to permission-protected data without user consent. We use a novel technique that combines the strengths of static and dynamic analysis, by first comparing the data sent by applications at runtime with the permissions granted to each app in order to find instances of potential unauthorized access to permission protected data. Once we have discovered the apps that are accessing personal data without permission, we statically analyze their code in order to discover covert- and side-channels used by apps and SDKs to circumvent the permission system. This methodology allows us to discover apps using the MAC address as a surrogate for location data, two SDKs using the external storage as a covert-channel to share unique identifiers and an app using picture metadata to gain unauthorized access to location data. • A novel SDK detection methodology that relies on obtaining signals observed both in the app’s code and static resources and during its runtime behavior. Then, we rely on a tree structure together with a confidence based system to accurately detect SDK presence without the need of any a priory knowledge and with the ability to discern whether a given SDK is part of legacy or dead code. We prove that this novel methodology can discover third-party SDKs with more accuracy than state-of-the-art tools both on a set of purpose-built ground-truth apps and on a dataset of 5k publicly available apps. With these three case studies, we are able to highlight the benefits of combining static and dynamic analysis techniques for the study of the privacy and security guarantees and risks of Android apps and third-party SDKs. The use of these techniques in isolation would not have allowed us to deeply investigate these privacy issues, as we would lack the ability to provide real evidence of potential breaches of legislation, to pin-point the specific way in which apps are leveraging cover and side channels to break Android’s permission system or we would be unable to adapt to an ever-changing ecosystem of Android third-party companies.The works presented in this thesis were partially funded within the framework of the following projects and grants: • European Union’s Horizon 2020 Innovation Action program (Grant Agreement No. 786741, SMOOTH Project and Grant Agreement No. 101021377, TRUST AWARE Project). • Spanish Government ODIO NºPID2019-111429RB-C21/PID2019-111429RBC22. • The Spanish Data Protection Agency (AEPD) • AppCensus Inc.This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Srdjan Matic.- Secretario: Guillermo Suárez-Tangil.- Vocal: Ben Stoc