Identifying and combating cyber-threats in the field of online banking

This thesis has been carried out in the industrial environment external to the University, as an industrial PhD. The results of this PhD have been tested, validated, and implemented in the production environment of Caixabank and have been used as models for others who have followed the same ideas. The most burning threats against banks throughout the Internet environment are based on software tools developed by criminal groups, applications running on web environment either on the computer of the victim (Malware) or on their mobile device itself through downloading rogue applications (fake app's with Malware APP). Method of the thesis has been used is an approximation of qualitative exploratory research on the problem, the answer to this problem and the use of preventive methods to this problem like used authentication systems. This method is based on samples, events, surveys, laboratory tests, experiments, proof of concept; ultimately actual data that has been able to deduce the thesis proposal, using both laboratory research and grounded theory methods of data pilot experiments conducted in real environments. I've been researching the various aspects related to e-crime following a line of research focusing on intrinsically related topics: - The methods, means and systems of attack: Malware, Malware families of banker Trojans, Malware cases of use, Zeus as case of use. - The fixed platforms, mobile applications and as a means for malware attacks. - forensic methods to analyze the malware and infrastructure attacks. - Continuous improvement of methods of authentication of customers and users as a first line of defense anti- malware. - Using biometrics as innovative factor authentication.The line investigating Malware and attack systems intrinsically is closed related to authentication methods and systems to infect customer (executables, APP's, etc.), because the main purpose of malware is precisely steal data entered in the "logon "authentication system, to operate and thus, fraudulently, steal money from online banking customers. Experiments in the Malware allowed establishing a new method of decryption establishing guidelines to combat its effects describing his fraudulent scheme and operation infection. I propose a general methodology to break the encryption communications malware (keystream), extracting the system used to encrypt such communications and a general approach of the Keystream technique. We show that this methodology can be used to respond to the threat of Zeus and finally provide lessons learned highlighting some general principles of Malware (in general) and in particular proposing Zeus Cronus, an IDS that specifically seeks the Zeus malware, testing it experimentally in a network production and providing an effective skills to combat the Malware are discussed. The thesis is a research interrelated progressive evolution between malware infection systems and authentication methods, reflected in the research work cumulatively, showing an evolution of research output and looking for a progressive improvement of methods authentication and recommendations for prevention and preventing infections, a review of the main app stores for mobile financial services and a proposal to these stores. The most common methods eIDAMS (authentication methods and electronic identification) implemented in Europe and its robustness are analyzed. An analysis of adequacy is presented in terms of efficiency, usability, costs, types of operations and segments including possibilities of use as authentication method with biometrics as innovation.Este trabajo de tesis se ha realizado en el entorno industrial externo a la Universidad como un PhD industrial Los resultados de este PhD han sido testeados, validados, e implementados en el entorno de producción de Caixabank y han sido utilizados como modelos por otras que han seguido las mismas ideas. Las amenazas más candentes contra los bancos en todo el entorno Internet, se basan en herramientas software desarrolladas por los grupos delincuentes, aplicaciones que se ejecutan tanto en entornos web ya sea en el propio ordenador de la víctima (Malware) o en sus dispositivos móviles mediante la descarga de falsas aplicaciones (APP falsa con Malware). Como método se ha utilizado una aproximación de investigación exploratoria cualitativa sobre el problema, la respuesta a este problema y el uso de métodos preventivos a este problema a través de la autenticación. Este método se ha basado en muestras, hechos, encuestas, pruebas de laboratorio, experimentos, pruebas de concepto; en definitiva datos reales de los que se ha podido deducir la tesis propuesta, utilizando tanto investigación de laboratorio como métodos de teoría fundamentada en datos de experimentos pilotos realizados en entornos reales. He estado investigando los diversos aspectos relacionados con e-crime siguiendo una línea de investigación focalizada en temas intrínsecamente relacionadas: - Los métodos, medios y sistemas de ataque: Malware, familias de Malware de troyanos bancarios, casos de usos de Malware, Zeus como caso de uso. - Las plataformas fijas, los móviles y sus aplicaciones como medio para realizar los ataques de Malware. - Métodos forenses para analizar el Malware y su infraestructura de ataque. - Mejora continuada de los métodos de autenticación de los clientes y usuarios como primera barrera de defensa anti- malware. - Uso de la biometría como factor de autenticación innovador. La línea investiga el Malware y sus sistemas de ataque intrínsecamente relacionada con los métodos de autenticación y los sistemas para infectar al cliente (ejecutables, APP's, etc.) porque el objetivo principal del malware es robar precisamente los datos que se introducen en el "logon" del sistema de autenticación para operar de forma fraudulenta y sustraer así el dinero de los clientes de banca electrónica. Los experimentos realizados en el Malware permitieron establecer un método novedoso de descifrado que estableció pautas para combatir sus efectos fraudulentos describiendo su esquema de infección y funcionamiento Propongo una metodología general para romper el cifrado de comunicaciones del malware (keystream) extrayendo el sistema utilizado para cifrar dichas comunicaciones y una generalización de la técnica de Keystream. Se demuestra que esta metodología puede usarse para responder a la amenaza de Zeus y finalmente proveemos lecciones aprendidas resaltando algunos principios generales del Malware (en general) y Zeus en particular proponiendo Cronus, un IDS que persigue específicamente el Malware Zeus, probándolo experimentalmente en una red de producción y se discuten sus habilidades y efectividad. En la tesis hay una evolución investigativa progresiva interrelacionada entre el Malware, sistemas de infección y los métodos de autenticación, que se refleja en los trabajos de investigación de manera acumulativa, mostrando una evolución del output de investigación y buscando una mejora progresiva de los métodos de autenticación y de la prevención y recomendaciones para evitar las infecciones, una revisión de las principales tiendas de Apps para servicios financieros para móviles y una propuesta para estas tiendas. Se analizan los métodos más comunes eIDAMS (Métodos de Autenticación e Identificación electrónica) implementados en Europa y su robustez y presentamos un análisis de adecuación en función de eficiencia, usabilidad, costes, tipos de operación y segmentos incluyendo un análisis de posibilidades con métodos biométricos como innovación.Postprint (published version

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.Comment: Work commissioned by CPNI, available at c2report.org. 38 pages. Listing abstract compressed from version appearing in repor

xLED: Covert Data Exfiltration from Air-Gapped Networks via Router LEDs

In this paper we show how attackers can covertly leak data (e.g., encryption keys, passwords and files) from highly secure or air-gapped networks via the row of status LEDs that exists in networking equipment such as LAN switches and routers. Although it is known that some network equipment emanates optical signals correlated with the information being processed by the device ('side-channel'), intentionally controlling the status LEDs to carry any type of data ('covert-channel') has never studied before. A malicious code is executed on the LAN switch or router, allowing full control of the status LEDs. Sensitive data can be encoded and modulated over the blinking of the LEDs. The generated signals can then be recorded by various types of remote cameras and optical sensors. We provide the technical background on the internal architecture of switches and routers (at both the hardware and software level) which enables this type of attack. We also present amplitude and frequency based modulation and encoding schemas, along with a simple transmission protocol. We implement a prototype of an exfiltration malware and discuss its design and implementation. We evaluate this method with a few routers and different types of LEDs. In addition, we tested various receivers including remote cameras, security cameras, smartphone cameras, and optical sensors, and also discuss different detection and prevention countermeasures. Our experiment shows that sensitive data can be covertly leaked via the status LEDs of switches and routers at a bit rates of 10 bit/sec to more than 1Kbit/sec per LED

Network traffic analysis for threats detection in the Internet of Things

As the prevalence of the Internet of Things (IoT) continues to increase, cyber criminals are quick to exploit the security gaps that many devices are inherently designed with. Users cannot be expected to tackle this threat alone, and many current solutions available for network monitoring are simply not accessible or can be difficult to implement for the average user, which is a gap that needs to be addressed. This article presents an effective signature-based solution to monitor, analyze, and detect potentially malicious traffic for IoT ecosystems in the typical home network environment by utilizing passive network sniffing techniques and a cloud application to monitor anomalous activity. The proposed solution focuses on two attack and propagation vectors leveraged by the infamous Mirai botnet, namely DNS and Telnet. Experimental evaluation demonstrates the proposed solution can detect 98.35 percent of malicious DNS traffic and 99.33 percent of Telnet traffic for an overall detection accuracy of 98.84 percent

A Practical Approach to Protect IoT Devices against Attacks and Compile Security Incident Datasets

open access articleThe Internet of Things (IoT) introduced the opportunity of remotely manipulating home appliances (such as heating systems, ovens, blinds, etc.) using computers and mobile devices. This idea fascinated people and originated a boom of IoT devices together with an increasing demand that was difficult to support. Many manufacturers quickly created hundreds of devices implementing functionalities but neglected some critical issues pertaining to device security. This oversight gave rise to the current situation where thousands of devices remain unpatched having many security issues that manufacturers cannot address after the devices have been produced and deployed. This article presents our novel research protecting IOT devices using Berkeley Packet Filters (BPFs) and evaluates our findings with the aid of our Filter.tlk tool, which is able to facilitate the development of BPF expressions that can be executed by GNU/Linux systems with a low impact on network packet throughput

Multi-Stage Detection Technique for DNS-Based Botnets

Domain Name System (DNS) is one of the most widely used protocols in the Internet. The main purpose of the DNS protocol is mapping user-friendly domain names to IP addresses. Unfortunately, many cyber criminals deploy the DNS protocol for malicious purposes, such as botnet communications. In this type of attack, the botmasters tunnel communications between the Command and Control (C&C) servers and the bot-infected machines within DNS request and response. Designing an effective approach for botnet detection has been done previously based on specific botnet types Since botnet communications are characterized by different features, botmasters may evade detection methods by modifying some of these features. This research aims to design and implement a multi-staged detection approach for Domain Generation Algorithm (DGA), Fast Flux Service Network, and Domain Flux-based botnets, as well as encrypted DNS tunneled-based botnets using the BRO Network Security Monitor. This approach is able to detect DNS-based botnet communications by relying on analyzing different techniques used for finding the C&C server, as well as encrypting the malicious traffic

Multilayer framework for botnet detection using machine learning algorithms

The authors wish to thank Universiti Teknologi Malaysia (UTM) for its support under Research University Grant Vot- 20H04, Malaysia Research University Network (MRUN) Vot 4L876. The authors would like to acknowledge that this work was supported/funded by the Ministry of Higher Education under the Fundamental Research Grant Scheme (FRGS/1/2018/ICT04/UTM/01/1). The work was also partially supported by the Specific Research project (SPEV) at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, under Grant 2102-2021. The authors are grateful for the support of student Sebastien Mambou in consultations regarding application aspects. The authors also wish to thank the Ministry of Education Malaysia for the Hadiah Latihan Persekutuan (HLP) scholarship to complete the research.A botnet is a malware program that a hacker remotely controls called a botmaster. Botnet can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and identity stealing. The botnet also can avoid being detected by a security system. The traditional method of detecting botnets commonly used signature-based analysis unable to detect unseen botnets. The behavior-based analysis seems like a promising solution to the current trends of botnets that keep evolving. This paper proposes a multilayer framework for botnet detection using machine learning algorithms that consist of a ltering module and classi cation module to detect the botnet's command and control server. We highlighted several criteria for our framework, such as it must be structure-independent, protocol-independent, and able to detect botnet in encapsulated technique. We used behavior-based analysis through ow-based features that analyzed the packet header by aggregating it to a 1-s time. This type of analysis enables detection if the packet is encapsulated, such as using a VPN tunnel. We also extend the experiment using different time intervals, but a 1-s time interval shows the most impressive results. The result shows that our botnet detection method can detect up to 92% of the f-score, and the lowest false-negative rate was 1.5%.Universiti Teknologi Malaysia (UTM) through the Research University Vot-20H04Malaysia Research University Network (MRUN) Vot4L876Ministry of Higher Education through the Fundamental Research Grant Scheme FRGS/1/2018/ICT04/UTM/01/1Hadiah Latihan Persekutuan (HLP) Scholarship through the Ministry of Education MalaysiaSpecific Research Project (SPEV) by the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republi