Unified Description for Network Information Hiding Methods

Until now hiding methods in network steganography have been described in arbitrary ways, making them difficult to compare. For instance, some publications describe classical channel characteristics, such as robustness and bandwidth, while others describe the embedding of hidden information. We introduce the first unified description of hiding methods in network steganography. Our description method is based on a comprehensive analysis of the existing publications in the domain. When our description method is applied by the research community, future publications will be easier to categorize, compare and extend. Our method can also serve as a basis to evaluate the novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie

Smart techniques and tools to detect Steganography - a viable practice to Security Office Department

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementInternet is today a commodity and a way for being connect to the world. It is through Internet is where most of the information is shared and where people run their businesses. However, there are some people that make a malicious use of it. Cyberattacks have been increasing all over the recent years, targeting people and organizations, looking to perform illegal actions. Cyber criminals are always looking for new ways to deliver malware to victims to launch an attack. Millions of users share images and photos on their social networks and generally users find them safe to use. Contrary to what most people think, images can contain a malicious payload and perform harmful actions. Steganography is the technique of hiding data, which, combined with media files, can be used to place malicious code. This problem, leveraged by the continuous media file sharing through massive use of digital platforms, may become a worldwide threat in malicious content sharing. Like phishing, people and organizations must be trained to suspect about inappropriate content and implement the proper set of actions to reduce probability of infections when accessing files supposed to be inoffensive. The aim of this study will try to help people and organizations by trying to set a toolbox where it can be possible to get some tools and techniques to assist in dealing with this kind of situations. A theoretical overview will be performed over other concepts such as Steganalysis, touching also Deep Learning and in Machine Learning to assess which is the range of its applicability in find solutions in detection and facing these situations. In addition, understanding the current main technologies, architectures and users’ hurdles will play an important role in designing and developing the proposed toolbox artifact

Detection and Mitigation of Steganographic Malware

A new attack trend concerns the use of some form of steganography and information hiding to make malware stealthier and able to elude many standard security mechanisms. Therefore, this Thesis addresses the detection and the mitigation of this class of threats. In particular, it considers malware implementing covert communications within network traffic or cloaking malicious payloads within digital images. The first research contribution of this Thesis is in the detection of network covert channels. Unfortunately, the literature on the topic lacks of real traffic traces or attack samples to perform precise tests or security assessments. Thus, a propaedeutic research activity has been devoted to develop two ad-hoc tools. The first allows to create covert channels targeting the IPv6 protocol by eavesdropping flows, whereas the second allows to embed secret data within arbitrary traffic traces that can be replayed to perform investigations in realistic conditions. This Thesis then starts with a security assessment concerning the impact of hidden network communications in production-quality scenarios. Results have been obtained by considering channels cloaking data in the most popular protocols (e.g., TLS, IPv4/v6, and ICMPv4/v6) and showcased that de-facto standard intrusion detection systems and firewalls (i.e., Snort, Suricata, and Zeek) are unable to spot this class of hazards. Since malware can conceal information (e.g., commands and configuration files) in almost every protocol, traffic feature or network element, configuring or adapting pre-existent security solutions could be not straightforward. Moreover, inspecting multiple protocols, fields or conversations at the same time could lead to performance issues. Thus, a major effort has been devoted to develop a suite based on the extended Berkeley Packet Filter (eBPF) to gain visibility over different network protocols/components and to efficiently collect various performance indicators or statistics by using a unique technology. This part of research allowed to spot the presence of network covert channels targeting the header of the IPv6 protocol or the inter-packet time of generic network conversations. In addition, the approach based on eBPF turned out to be very flexible and also allowed to reveal hidden data transfers between two processes co-located within the same host. Another important contribution of this part of the Thesis concerns the deployment of the suite in realistic scenarios and its comparison with other similar tools. Specifically, a thorough performance evaluation demonstrated that eBPF can be used to inspect traffic and reveal the presence of covert communications also when in the presence of high loads, e.g., it can sustain rates up to 3 Gbit/s with commodity hardware. To further address the problem of revealing network covert channels in realistic environments, this Thesis also investigates malware targeting traffic generated by Internet of Things devices. In this case, an incremental ensemble of autoencoders has been considered to face the ''unknown'' location of the hidden data generated by a threat covertly exchanging commands towards a remote attacker. The second research contribution of this Thesis is in the detection of malicious payloads hidden within digital images. In fact, the majority of real-world malware exploits hiding methods based on Least Significant Bit steganography and some of its variants, such as the Invoke-PSImage mechanism. Therefore, a relevant amount of research has been done to detect the presence of hidden data and classify the payload (e.g., malicious PowerShell scripts or PHP fragments). To this aim, mechanisms leveraging Deep Neural Networks (DNNs) proved to be flexible and effective since they can learn by combining raw low-level data and can be updated or retrained to consider unseen payloads or images with different features. To take into account realistic threat models, this Thesis studies malware targeting different types of images (i.e., favicons and icons) and various payloads (e.g., URLs and Ethereum addresses, as well as webshells). Obtained results showcased that DNNs can be considered a valid tool for spotting the presence of hidden contents since their detection accuracy is always above 90% also when facing ''elusion'' mechanisms such as basic obfuscation techniques or alternative encoding schemes. Lastly, when detection or classification are not possible (e.g., due to resource constraints), approaches enforcing ''sanitization'' can be applied. Thus, this Thesis also considers autoencoders able to disrupt hidden malicious contents without degrading the quality of the image

Steganography and Data Loss Prevention: An overlooked risk?

Steganography is the art or science of hiding information into a carrier in such a way that the hidden data could not be detected at first sight. Steganography techniques have broadened their scope of action, from hiding information into picture media, to audio steganography and to the field of network steganography. All these methods entail a potential threat to the information security policies of any business; having into the data leakage threats its likely focus. In this scenario, business corporations cannot remain blind to these types of threats and should consider adequate policies and prevention techniques to avoid these risks. We have analyzed in this article the potential dangers that an organization could face in the light of these types of steganography techniques along with a review of current commercial software vendors to analyze their offers and mishaps on Data Leakage Prevention regarding steganography risks

Information leakage and steganography: detecting and blocking covert channels

This PhD Thesis explores the threat of information theft perpetrated by malicious insiders. As opposite to outsiders, insiders have access to information assets belonging the organization, know the organization infrastructure and more importantly, know the value of the different assets the organization holds. The risk created by malicious insiders have led both the research community and commercial providers to spend efforts on creating mechanisms and solutions to reduce it. However, the lack of certain controls by current proposals may led security administrators to a false sense of security that could actually ease information theft attempts. As a first step of this dissertation, a study of current state of the art proposals regarding information leakage protections has been performed. This study has allowed to identify the main weaknesses of current proposals which are mainly the usage of steganographic algorithms, the lack of control of modern mobile devices and the lack of control of the action the insiders perform inside the different trusted applications they commonly use. Each of these drawbacks have been explored during this dissertation. Regarding the usage of steganographic algorithms, two different steganographic systems have been proposed. First, a steganographic algorithm that transforms source code into innocuous text has been presented. This system uses free context grammars and to parse the source code to be hidden and produce an innocuous text. This system could be used to extract valuable source code from software development environments, where security restrictions are usually softened. Second, a steganographic application for iOS devices has also been presented. This application, called “Hide It In” allows to embed images into other innocuous images and send those images through the device email account. This application includes a cover mode that allows to take pictures without showing that fact in the device screen. The usage of these kinds of applications is suitable in most of the environments which handle sensitive information, as most of them do not incorporate mechanisms to control the usage of advanced mobile devices. The application, which is already available at the Apple App Store, has been downloaded more than 5.000 times. In order to protect organizations against the malicious usage of steganography, several techniques can be implemented. In this thesis two different approaches are presented. First, steganographic detectors could be deployed along the organization to detect possible transmissions of stego-objects outside the organization perimeter. In this regard, a proposal to detect hidden information inside executable files has been presented. The proposed detector, which measures the assembler instruction selection made by compilers, is able to correctly identify stego-objects created through the tool Hydan. Second, steganographic sanitizers could be deployed over the organization infrastructure to reduce the capacity of covert channels that can transmit information outside the organization. In this regard, a framework to avoid the usage of steganography over the HTTP protocol has been proposed. The presented framework, diassembles HTTP messages, overwrites the possible carriers of hidden information with random noise and assembles the HTTP message again. Obtained results show that it is possible to highly reduce the capacity of covert channels created through HTTP. However, the system introduces a considerable delay in communications. Besides steganography, this thesis has also addressed the usage of trusted applications to extract information from organizations. Although applications execution inside an organization can be restricted, trusted applications used to perform daily tasks are generally executed without any restrictions. However, the complexity of such applications can be used by an insider to transform information in such a way that deployed information protection solutions are not able to detect the transformed information as sensitive. In this thesis, a method to encrypt sensitive information using trusted applications is presented. Once the information has been encrypted it is possible to extract it outside the organization without raising any alarm in the deployed security systems. This technique has been successfully evaluated against a state of the art commercial data leakage protection solution. Besides the presented evasion technique, several improvements to enhance the security of current DLP solutions are presented. These are specifically focused in avoiding information leakage through the usage of trusted applications. The contributions of this dissertation have shown that current information leakage protection mechanisms do not fully address all the possible attacks that a malicious insider can commit to steal sensitive information. However, it has been shown that it is possible to implement mechanisms to avoid the extraction of sensitive information by malicious insiders. Obviously, avoiding such attacks does not mean that all possible threats created by malicious insiders are addressed. It is necessary then, to continue studying the threats that malicious insiders pose to the confidentiality of information assets and the possible mechanisms to mitigate them. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Esta tesis doctoral explora la amenaza creada por los empleados maliciosos en lo referente a la confidencialidad de la información sensible (o privilegiada) en posesión de una organización. Al contrario que los atacantes externos a la organización, los atacantes internos poseen de acceso a los activos de información pertenecientes a la organización, conocen la infraestructura de la misma y lo más importante, conocen el valor de los mismos. El riesgo creado por los empleados maliciosos (o en general atacantes internos) ha llevado tanto a la comunidad investigadora como a los proveedores comerciales de seguridad de la información a la creación de mecanismos y soluciones para reducir estas amenazas. Sin embargo, la falta de controles por parte de ciertas propuestas actuales pueden inducir una falsa sensación de seguridad en los administradores de seguridad de las organizaciones, facilitando los posibles intentos de robo de información. Para la realización de esta tesis doctoral, en primer lugar se ha realizado un estudio de las propuestas actuales con respecto a la protección de fugas de información. Este estudio ha permitido identificar las principales debilidades de las mismas, que son principalmente la falta de control sobre el uso de algoritmos esteganográficos, la falta de control de sobre dispositivos móviles avanzados y la falta de control sobre las acciones que realizan los empleados en el interior de las organizaciones. Cada uno de los problemas identificados ha sido explorado durante la realización de esta tesis doctoral. En lo que respecta al uso de algoritmos esteganográficos, esta tesis incluye la propuesta de dos sistemas de ocultación de información. En primer lugar, se presenta un algoritmo esteganográfico que transforma código fuente en texto inocuo. Este sistema utiliza gramáticas libres de contexto para transformar el código fuente a ocultar en un texto inocuo. Este sistema podría ser utilizado para extraer código fuente valioso de entornos donde se realiza desarrollo de software (donde las restricciones de seguridad suelen ser menores). En segundo lugar, se propone una aplicación esteganográfica para dispositivos móviles (concretamente iOS). Esta aplicación, llamada “Hide It In” permite incrustar imágenes en otras inocuas y enviar el estegoobjeto resultante a través de la cuenta de correo electrónico del dispositivo. Esta aplicación incluye un modo encubierto, que permite tomar imágenes mostrando en el propio dispositivo elementos del interfaz diferentes a los de a cámara, lo que permite tomar fotografías de forma inadvertida. Este tipo de aplicaciones podrían ser utilizadas por empleados malicios en la mayoría de los entornos que manejan información sensible, ya que estos no suelen incorporar mecanismos para controlar el uso de dispositivos móviles avanzados. La aplicación, que ya está disponible en la App Store de Apple, ha sido descargada más de 5.000 veces. Otro objetivo de la tesis ha sido prevenir el uso malintencionado de técnicas esteganográficas. A este respecto, esta tesis presenta dos enfoques diferentes. En primer lugar, se pueden desplegar diferentes detectores esteganográficos a lo largo de la organización. De esta forma, se podrían detectar las posibles transmisiones de estego-objetos fuera del ámbito de la misma. En este sentido, esta tesis presenta un algoritmo de estegoanálisis para la detección de información oculta en archivos ejecutables. El detector propuesto, que mide la selección de instrucciones realizada por los compiladores, es capaz de identificar correctamente estego-objetos creados a través de la herramienta de Hydan. En segundo lugar, los “sanitizadores” esteganográficos podrían ser desplegados a lo largo de la infraestructura de la organización para reducir la capacidad de los posibles canales encubiertos que pueden ser utilizados para transmitir información sensible de forma descontrolada.. En este sentido, se ha propuesto un marco para evitar el uso de la esteganografía a través del protocolo HTTP. El marco presentado, descompone los mensajes HTTP, sobrescribe los posibles portadores de información oculta mediante la inclusión de ruido aleatorio y reconstruye los mensajes HTTP de nuevo. Los resultados obtenidos muestran que es posible reducir drásticamente la capacidad de los canales encubiertos creados a través de HTTP. Sin embargo, el sistema introduce un retraso considerable en las comunicaciones. Además de la esteganografía, esta tesis ha abordado también el uso de aplicaciones de confianza para extraer información sensible de las organizaciones. Aunque la ejecución de aplicaciones dentro de una organización puede ser restringida, las aplicaciones de confianza, que se utilizan generalmente para realizar tareas cotidianas dentro de la organización, se ejecutan normalmente sin ninguna restricción. Sin embargo, la complejidad de estas aplicaciones puede ser utilizada para transformar la información de tal manera que las soluciones de protección ante fugas de información desplegadas no sean capaces de detectar la información transformada como sensibles. En esta tesis, se presenta un método para cifrar información sensible mediante el uso de aplicaciones de confianza. Una vez que la información ha sido cifrada, es posible extraerla de la organización sin generar alarmas en los sistemas de seguridad implementados. Esta técnica ha sido evaluada con éxito contra de una solución comercial para la prevención de fugas de información. Además de esta técnica de evasión, se han presentado varias mejoras en lo que respecta a la seguridad de las actuales soluciones DLP. Estas, se centran específicamente en evitar la fuga de información a través del uso de aplicaciones de confianza. Las contribuciones de esta tesis han demostrado que los actuales mecanismos para la protección ante fugas de información no responden plenamente a todos los posibles ataques que puedan ejecutar empleados maliciosos. Sin embargo, también se ha demostrado que es posible implementar mecanismos para evitar la extracción de información sensible mediante los mencionados ataques. Obviamente, esto no significa que todas las posibles amenazas creadas por empleados maliciosos hayan sido abordadas. Es necesario por lo tanto, continuar el estudio de las amenazas en lo que respecta a la confidencialidad de los activos de información y los posibles mecanismos para mitigar las mismas

Security Hazards when Law is Code.

As software continues to eat the world, there is an increasing pressure to automate every aspect of society, from self-driving cars, to algorithmic trading on the stock market. As this pressure manifests into software implementations of everything, there are security concerns to be addressed across many areas. But are there some domains and fields that are distinctly susceptible to attacks, making them difficult to secure? My dissertation argues that one domain in particular—public policy and law— is inherently difficult to automate securely using computers. This is in large part because law and policy are written in a manner that expects them to be flexibly interpreted to be fair or just. Traditionally, this interpreting is done by judges and regulators who are capable of understanding the intent of the laws they are enforcing. However, when these laws are instead written in code, and interpreted by a machine, this capability to understand goes away. Because they blindly fol- low written rules, computers can be tricked to perform actions counter to their intended behavior. This dissertation covers three case studies of law and policy being implemented in code and security vulnerabilities that they introduce in practice. The first study analyzes the security of a previously deployed Internet voting system, showing how attackers could change the outcome of elections carried out online. The second study looks at airport security, investigating how full-body scanners can be defeated in practice, allowing attackers to conceal contraband such as weapons or high explosives past airport checkpoints. Finally, this dissertation also studies how an Internet censorship system such as China’s Great Firewall can be circumvented by techniques that exploit the methods employed by the censors themselves. To address these concerns of securing software implementations of law, a hybrid human-computer approach can be used. In addition, systems should be designed to allow for attacks or mistakes to be retroactively undone or inspected by human auditors. By combining the strengths of computers (speed and cost) and humans (ability to interpret and understand), systems can be made more secure and more efficient than a method employing either alone.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120795/1/ewust_1.pd

Programmable data gathering for detecting stegomalware

The 'arm race' against malware developers requires to collect a wide variety of performance measurements, for instance to face threats leveraging information hiding and steganography. Unfortunately, this process could be time-consuming, lack of scalability and cause performance degradations within computing and network nodes. Moreover, since the detection of steganographic threats is poorly generalizable, being able to collect attack-independent indicators is of prime importance. To this aim, the paper proposes to take advantage of the extended Berkeley Packet Filter to gather data for detecting stegomalware. To prove the effectiveness of the approach, it also reports some preliminary experimental results obtained as the joint outcome of two H2020 Projects, namely ASTRID and SIMARGL