CLASSIFYING AND RESPONDING TO NETWORK INTRUSIONS

Intrusion detection systems (IDS) have been widely adopted within the IT community, as passive monitoring tools that report security related problems to system administrators. However, the increasing number and evolving complexity of attacks, along with the growth and complexity of networking infrastructures, has led to overwhelming numbers of IDS alerts, which allow significantly smaller timeframe for a human to respond. The need for automated response is therefore very much evident. However, the adoption of such approaches has been constrained by practical limitations and administrators' consequent mistrust of systems' abilities to issue appropriate responses. The thesis presents a thorough analysis of the problem of intrusions, and identifies false alarms as the main obstacle to the adoption of automated response. A critical examination of existing automated response systems is provided, along with a discussion of why a new solution is needed. The thesis determines that, while the detection capabilities remain imperfect, the problem of false alarms cannot be eliminated. Automated response technology must take this into account, and instead focus upon avoiding the disruption of legitimate users and services in such scenarios. The overall aim of the research has therefore been to enhance the automated response process, by considering the context of an attack, and investigate and evaluate a means of making intelligent response decisions. The realisation of this objective has included the formulation of a response-oriented taxonomy of intrusions, which is used as a basis to systematically study intrusions and understand the threats detected by an IDS. From this foundation, a novel Flexible Automated and Intelligent Responder (FAIR) architecture has been designed, as the basis from which flexible and escalating levels of response are offered, according to the context of an attack. The thesis describes the design and operation of the architecture, focusing upon the contextual factors influencing the response process, and the way they are measured and assessed to formulate response decisions. The architecture is underpinned by the use of response policies which provide a means to reflect the changing needs and characteristics of organisations. The main concepts of the new architecture were validated via a proof-of-concept prototype system. A series of test scenarios were used to demonstrate how the context of an attack can influence the response decisions, and how the response policies can be customised and used to enable intelligent decisions. This helped to prove that the concept of flexible automated response is indeed viable, and that the research has provided a suitable contribution to knowledge in this important domain

SUTMS - Unified Threat Management Framework for Home Networks

Home networks were initially designed for web browsing and non-business critical applications. As infrastructure improved, internet broadband costs decreased, and home internet usage transferred to e-commerce and business-critical applications. Today’s home computers host personnel identifiable information and financial data and act as a bridge to corporate networks via remote access technologies like VPN. The expansion of remote work and the transition to cloud computing have broadened the attack surface for potential threats. Home networks have become the extension of critical networks and services, hackers can get access to corporate data by compromising devices attacked to broad- band routers. All these challenges depict the importance of home-based Unified Threat Management (UTM) systems. There is a need of unified threat management framework that is developed specifically for home and small networks to address emerging security challenges. In this research, the proposed Smart Unified Threat Management (SUTMS) framework serves as a comprehensive solution for implementing home network security, incorporating firewall, anti-bot, intrusion detection, and anomaly detection engines into a unified system. SUTMS is able to provide 99.99% accuracy with 56.83% memory improvements. IPS stands out as the most resource-intensive UTM service, SUTMS successfully reduces the performance overhead of IDS by integrating it with the flow detection mod- ule. The artifact employs flow analysis to identify network anomalies and categorizes encrypted traffic according to its abnormalities. SUTMS can be scaled by introducing optional functions, i.e., routing and smart logging (utilizing Apriori algorithms). The research also tackles one of the limitations identified by SUTMS through the introduction of a second artifact called Secure Centralized Management System (SCMS). SCMS is a lightweight asset management platform with built-in security intelligence that can seamlessly integrate with a cloud for real-time updates

A Proactive Approach to Detect IoT Based Flooding Attacks by Using Software Defined Networks and Manufacturer Usage Descriptions

abstract: The advent of the Internet of Things (IoT) and its increasing appearances in Small Office/Home Office (SOHO) networks pose a unique issue to the availability and health of the Internet at large. Many of these devices are shipped insecurely, with poor default user and password credentials and oftentimes the general consumer does not have the technical knowledge of how they may secure their devices and networks. The many vulnerabilities of the IoT coupled with the immense number of existing devices provide opportunities for malicious actors to compromise such devices and use them in large scale distributed denial of service attacks, preventing legitimate users from using services and degrading the health of the Internet in general. This thesis presents an approach that leverages the benefits of an Internet Engineering Task Force (IETF) proposed standard named Manufacturer Usage Descriptions, that is used in conjunction with the concept of Software Defined Networks (SDN) in order to detect malicious traffic generated from IoT devices suspected of being utilized in coordinated flooding attacks. The approach then works towards the ability to detect these attacks at their sources through periodic monitoring of preemptively permitted flow rules and determining which of the flows within the permitted set are misbehaving by using an acceptable traffic range using Exponentially Weighted Moving Averages (EWMA).Dissertation/ThesisMasters Thesis Computer Science 201

Holistic Network Defense: Fusing Host and Network Features for Attack Classification

This work presents a hybrid network-host monitoring strategy, which fuses data from both the network and the host to recognize malware infections. This work focuses on three categories: Normal, Scanning, and Infected. The network-host sensor fusion is accomplished by extracting 248 features from network traffic using the Fullstats Network Feature generator and from the host using text mining, looking at the frequency of the 500 most common strings and analyzing them as word vectors. Improvements to detection performance are made by synergistically fusing network features obtained from IP packet flows and host features, obtained from text mining port, processor, logon information among others. In addition, the work compares three different machine learning algorithms and updates the script required to obtain network features. Hybrid method results outperformed host only classification by 31.7% and network only classification by 25%. The new approach also reduces the number of alerts while remaining accurate compared with the commercial IDS SNORT. These results make it such that even the most typical users could understand alert classification messages

Intrusion Detection and Security Assessment in a University Network

This thesis first explores how intrusion detection (ID) techniques can be used to provide an extra security layer for today‟s typically security-unaware Internet user. A review of the ever-growing network security threat is presented along with an analysis of the suitability of existing ID systems (IDS) for protecting users of varying security expertise. In light of the impracticality of many IDS for today‟s users, a web-enabled, agent-based, hybrid IDS is proposed. The motivations for the system are presented along with details of its design and implementation. As a test case, the system is deployed on the DCU network and results analysed. One of the aims of an IDS is to uncover security-related issues in its host network. The issues revealed by our IDS demonstrate that a full DCU network security assessment is warranted. This thesis describes how such an assessment should be carried out and presents corresponding results. A set of security-enhancing recommendations for the DCU network are presented

Adaptive Response System for Distributed Denial-of-Service Attacks

The continued prevalence and severe damaging effects of the Distributed Denial of Service (DDoS) attacks in today’s Internet raise growing security concerns and call for an immediate response to come up with better solutions to tackle DDoS attacks. The current DDoS prevention mechanisms are usually inflexible and determined attackers with knowledge of these mechanisms, could work around them. Most existing detection and response mechanisms are standalone systems which do not rely on adaptive updates to mitigate attacks. As different responses vary in their “leniency” in treating detected attack traffic, there is a need for an Adaptive Response System. We designed and implemented our DDoS Adaptive ResponsE (DARE) System, which is a distributed DDoS mitigation system capable of executing appropriate detection and mitigation responses automatically and adaptively according to the attacks. It supports easy integrations for both signature-based and anomaly-based detection modules. Additionally, the design of DARE’s individual components takes into consideration the strengths and weaknesses of existing defence mechanisms, and the characteristics and possible future mutations of DDoS attacks. These components consist of an Enhanced TCP SYN Attack Detector and Bloom-based Filter, a DDoS Flooding Attack Detector and Flow Identifier, and a Non Intrusive IP Traceback mechanism. The components work together interactively to adapt the detections and responses in accordance to the attack types. Experiments conducted on DARE show that the attack detection and mitigation are successfully completed within seconds, with about 60% to 86% of the attack traffic being dropped, while availability for legitimate and new legitimate requests is maintained. DARE is able to detect and trigger appropriate responses in accordance to the attacks being launched with high accuracy, effectiveness and efficiency. We also designed and implemented a Traffic Redirection Attack Protection System (TRAPS), a stand-alone DDoS attack detection and mitigation system for IPv6 networks. In TRAPS, the victim under attack verifies the authenticity of the source by performing virtual relocations to differentiate the legitimate traffic from the attack traffic. TRAPS requires minimal deployment effort and does not require modifications to the Internet infrastructure due to its incorporation of the Mobile IPv6 protocol. Experiments to test the feasibility of TRAPS were carried out in a testbed environment to verify that it would work with the existing Mobile IPv6 implementation. It was observed that the operations of each module were functioning correctly and TRAPS was able to successfully mitigate an attack launched with spoofed source IP addresses

Network Traffic Based Botnet Detection Using Machine Learning

The field of information and computer security is rapidly developing in today’s world as the number of security risks is continuously being explored every day. The moment a new software or a product is launched in the market, a new exploit or vulnerability is exposed and exploited by the attackers or malicious users for different motives. Many attacks are distributed in nature and carried out by botnets that cause widespread disruption of network activity by carrying out DDoS (Distributed Denial of Service) attacks, email spamming, click fraud, information and identity theft, virtual deceit and distributed resource usage for cryptocurrency mining. Botnet detection is still an active area of research as no single technique is available that can detect the entire ecosystem of a botnet like Neris, Rbot, and Virut. They tend to have different configurations and heavily armored by malware writers to evade detection systems by employing sophisticated evasion techniques. This report provides a detailed overview of a botnet and its characteristics and the existing work that is done in the domain of botnet detection. The study aims to evaluate the preprocessing techniques like variance thresholding and one-hot encoding to clean the botnet dataset and feature selection technique like filter, wrapper and embedded method to boost the machine learning model performance. This study addresses the dataset imbalance issues through techniques like undersampling, oversampling, ensemble learning and gradient boosting by using random forest, decision tree, AdaBoost and XGBoost. Lastly, the optimal model is then trained and tested on the dataset of different attacks to study its performance

Cyber-security of Cyber-Physical Systems (CPS)

This master's thesis reports on security of a Cyber-Physical System (CPS) in the department of industrial engineering at UiT campus Narvik. The CPS targets connecting distinctive robots in the laboratory in the department of industrial engineering. The ultimate objective of the department is to propose such a system for the industry. The thesis focuses on the network architecture of the CPS and the availability principle of security. This report states three research questions that are aimed to be answered. The questions are: what a secure CPS architecture for the purpose of the existing system is, how far the current state of system is from the defined secure architecture, and how to reach the proposed architecture. Among the three question, the first questions has absorbed the most attention of this project. The reason is that a secure and robust architecture would provide a touchstone that makes answering the second and third questions easier. In order to answer the questions, Cisco SAFE for IoT threat defense for manufacturing approach is chosen. The architectural approach of Cisco SAFE for IoT, with similarities to the Cisco SAFE for secure campus networks, provides a secure network architecture based on business flows/use cases and defining related security capabilities. This approach supplies examples of scenarios, business flows, and security capabilities that encouraged selecting it. It should be noted that Cisco suggests its proprietary technologies for security capabilities. According to the need of the project owners and the fact that allocating funds are not favorable for them, all the suggested security capabilities are intended to be open-source, replacing the costly Cisco-proprietary suggestions. Utilizing the approach and the computer networking fundamentals resulted in the proposed secure network architecture. The proposed architecture is used as a touchstone to evaluate the existing state of the CPS in the department of industrial engineering. Following that, the required security measures are presented to approach the system to the proposed architecture. Attempting to apply the method of Cisco SAFE, the identities using the system and their specific activities are presented as the business flow. Based on the defined business flow, the required security capabilities are selected. Finally, utilizing the provided examples of Cisco SAFE documentations, a complete network architecture is generated. The architecture consists of five zones that include the main components, security capabilities, and networking devices (such as switches and access points). Investigating the current state of the CPS and evaluating it by the proposed architecture and the computer networking fundamentals, helped identifying six important shortcomings. Developing on the noted shortcomings, and identification of open-source alternatives for the Cisco-proprietary technologies, nine security measures are proposed. The goal is to perform all the security measures. Thus, the implementations and solutions for each security measure is noted at the end of the presented results. The security measures that require purchasing a device were not considered in this project. The reasons for this decision are the time-consuming process of selecting an option among different alternatives, and the prior need for grasping the features of the network with the proposed security capabilities; features such as amount and type of traffic inside the network, and possible incidents detected using an Intrusion Detection Prevention System. The attempts to construct a secure cyber-physical system is an everlasting procedure. New threats, best practices, guidelines, and standards are introduced on a daily basis. Moreover, business needs could vary from time to time. Therefore, the selected security life-cycle is required and encouraged to be used in order to supply a robust lasting cyber-physical system

Standards and practices necessary to implement a successful security review program for intrusion management systems

Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2002Includes bibliographical references (leaves: 84-85)Text in English; Abstract: Turkish and Englishviii, 91 leavesIntrusion Management Systems are being used to prevent the information systems from successful intrusions and their consequences. They also have detection features. They try to detect intrusions, which have passed the implemented measures. Also the recovery of the system after a successful intrusion is made by the Intrusion Management Systems. The investigation of the intrusion is made by Intrusion Management Systems also. These functions can be existent in an intrusion management system model, which has a four layers architecture. The layers of the model are avoidance, assurance, detection and recovery. At the avoidance layer necessary policies, standards and practices are implemented to prevent the information system from successful intrusions. At the avoidance layer, the effectiveness of implemented measures are measured by some test and reviews. At the detection layer the identification of an intrusion or intrusion attempt is made in the real time. The recovery layer is responsible from restoring the information system after a successful intrusion. It has also functions to investigate the intrusion. Intrusion Management Systems are used to protect information and computer assets from intrusions. An organization aiming to protect its assets must use such a system. After the implementation of the system, continuous reviews must be conducted in order to ensure the effectiveness of the measures taken. Such a review can achieve its goal by using principles and standards. In this thesis, the principles necessary to implement a successful review program for Intrusion Management Systems have been developed in the guidance of Generally Accepted System Security Principles (GASSP). These example principles are developed for tools of each Intrusion Management System layer. These tools are firewalls for avoidance layer, vulnerability scanners for assurance layer, intrusion detection systems for detection layer and integrity checkers for recovery layer of Intrusion Management Systems

Exploring security controls for ICS/SCADA environments

Trabalho de projeto de mestrado, Segurança Informática, Universidade de Lisboa, Faculdade de Ciências, 2020Os Sistemas de Controlo Industriais (ICS) estão a começar a fundir-se com as soluções de IT, por forma a promover a interconectividade. Embora isto traga inúmeros benefícios de uma perspetiva de controlo, os ICS apresentam uma falta de mecanismos de segurança que consigam evitar possíveis ameaças informáticas, quando comparados aos comuns sistemas de informação [29], [64]. Dada a natureza crítica destes sistemas, e a ocorrências recentes de ciberataques desastrosos, a segurança ´e um tópico que deve ser incentivado. À luz deste problema, na presente dissertação apresentamos uma avaliação de possíveis aplicações e controlos de segurança a serem implantados nestes ambientes críticos e a implementação de uma solução de segurança extensível que dá resposta a certos ataques focados em sistemas industriais, capaz de ser implantada em qualquer rede industrial que permita a sua ligação. Com o auxilio de uma framework extensivel e portátil para testes de ICS, e outros ambientes industriais de testes, foi possível analisar diferentes cenários de ameaças, implantar mecanismos de segurança para os detetar e avaliar os resultados, com o intuito de fornecer uma ideia de como empregar estes mecanismos da melhor maneira possível num ambiente real de controlo industrial.Industrial Control Systems (ICS) are beginning to merge with IT solutions, in order to promote inter-connectivity. Although this brings countless benefits from a control perspective, ICS have been lacking in security mechanisms to ward off potential cyber threats, when compared to common information systems [29], [64]. Given the critical nature of these systems, and the recent occurrences of disastrous cyber-attacks, security is a topic that should be encouraged. In light of this problem, in this dissertation we present an assessment of possible security applications and controls that can be deployed in these critical environments and the implementation of an extensible security solution that responds to certain attacks focused on industrial systems, capable of being deployed in any industrial network that allows its connection. With the help of an extensible and portable framework for ICS testing, and other industrial testing environments, it was possible to analyze different threat scenarios, implement security mechanisms to detect them and evaluate the results in order to provide an idea on how to employ these mechanisms as best as possible in a real industrial control environment, without compromising it’s process