A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack Detection

Enterprise networks that host valuable assets and services are popular and frequent targets of distributed network attacks. In order to cope with the ever-increasing threats, industrial and research communities develop systems and methods to monitor the behaviors of their assets and protect them from critical attacks. In this paper, we systematically survey related research articles and industrial systems to highlight the current status of this arms race in enterprise network security. First, we discuss the taxonomy of distributed network attacks on enterprise assets, including distributed denial-of-service (DDoS) and reconnaissance attacks. Second, we review existing methods in monitoring and classifying network behavior of enterprise hosts to verify their benign activities and isolate potential anomalies. Third, state-of-the-art detection methods for distributed network attacks sourced from external attackers are elaborated, highlighting their merits and bottlenecks. Fourth, as programmable networks and machine learning (ML) techniques are increasingly becoming adopted by the community, their current applications in network security are discussed. Finally, we highlight several research gaps on enterprise network security to inspire future research.Comment: Journal paper submitted to Elseive

Practical Encryption Gateways to Integrate Legacy Industrial Machinery

Future industrial networks will consist of a mixture of old and new components, due to the very long life-cycles of industrial machines on the one hand and the need to change in the face of trends like Industry 4.0 or the industrial Internet of things on the other. These networks will be very heterogeneous and will serve legacy as well as new use cases in parallel. This will result in an increased demand for network security and precisely within this domain, this thesis tries to answer one specific question: how to make it possible for legacy industrial machines to run securely in those future heterogeneous industrial networks. The need for such a solution arises from the fact, that legacy machines are very outdated and hence vulnerable systems, when assessing them from an IT security standpoint. For various reasons, they cannot be easily replaced or upgraded and with the opening up of industrial networks to the Internet, they become prime attack targets. The only way to provide security for them, is by protecting their network traffic. The concept of encryption gateways forms the basis of our solution. These are special network devices, that are put between the legacy machine and the network. The gateways encrypt data traffic from the machine before it is put on the network and decrypt traffic coming from the network accordingly. This results in a separation of the machine from the network by virtue of only decrypting and passing through traffic from other authenticated gateways. In effect, they protect communication data in transit and shield the legacy machines from potential attackers within the rest of the network, while at the same time retaining their functionality. Additionally, through the specific placement of gateways inside the network, fine-grained security policies become possible. This approach can reduce the attack surface of the industrial network as a whole considerably. As a concept, this idea is straight forward and not new. Yet, the devil is in the details and no solution specifically tailored to the needs of the industrial environment and its legacy components existed prior to this work. Therefore, we present in this thesis concrete building blocks in the direction of a generally applicable encryption gateway solution that allows to securely integrate legacy industrial machinery and respects industrial requirements. This not only entails works in the direction of network security, but also includes works in the direction of guaranteeing the availability of the communication links that are protected by the gateways, works to simplify the usability of the gateways as well as the management of industrial data flows by the gateways

FAIR: Forwarding Accountability for Internet Reputability

This paper presents FAIR, a forwarding accountability mechanism that incentivizes ISPs to apply stricter security policies to their customers. The Autonomous System (AS) of the receiver specifies a traffic profile that the sender AS must adhere to. Transit ASes on the path mark packets. In case of traffic profile violations, the marked packets are used as a proof of misbehavior. FAIR introduces low bandwidth overhead and requires no per-packet and no per-flow state for forwarding. We describe integration with IP and demonstrate a software switch running on commodity hardware that can switch packets at a line rate of 120 Gbps, and can forward 140M minimum-sized packets per second, limited by the hardware I/O subsystem. Moreover, this paper proposes a "suspicious bit" for packet headers - an application that builds on top of FAIR's proofs of misbehavior and flags packets to warn other entities in the network.Comment: 16 pages, 12 figure

Policy-based Information Sharing using Software-Defined Networking in Cloud Systems

Cloud Computing is rapidly becoming a ubiquitous technology. It enables an escalation in computing capacity, storage and performance without the need to invest in new infrastructure and the maintenance expenses that follow. Security is among the major concerns of organizations that are still reluctant to adopt this technology: The cloud is dynamic, and with so many different parameters involved, it is a diffi cult task to regulate it. With an approach that blends Usage Management and Statistical Learning, this research yielded a novel approach to mitigate some of the issues arising due to questionable security, and to regulate performance (utilization of resources).This research also explored how to enforce the policies related to the resources inside a Virtual Machine(VM), apart from providing initial access control. As well, this research compared various encryption schemes and observed their behavior in the cloud. We considered various components in the cloud to deduce a multi-cost function, which in turn helps to regulate the cloud. While guaranteeing security policies in the cloud, it is essential to add security to the network because the virtual cloud and SDN tie together. Enforcing network-wide policies has always been a challenging task in the domain of communication networks. Software-defined networking (SDN) enables the use of a central controller to define policies, and to use each network switch to enforce policies. While this presents an attractive operational model, it uses a very low-level framework, and is not suitable for directly implement- ing high-level policies. Therefore, we present a new framework for defining policies and easily compiling them from a user interface directly into OpenFlow actions and usage management system processes. This demonstrated capability allows cloud administrators to enforce both network and usage polices on the cloud

Enhancing and Protecting Intrusion Detection Systems Using P4-Enabled Data Planes

As computer networks have evolved to form the Internet, there has been an ever-growing attack surface, ready to be exploited by malicious actors. Computer networks are fundamental to daily life, with dependence on them further increasing every single day. The Internet is used to facilitate manufacturing, finance, critical infrastructure and global communication. Networks also serve as a fundamental attack surface, exposing users and devices to malicious actors, internally and externally. The cost of weak security can now prove to be enormous, in terms of material costs, as well as outages to service and production. With the evolution of the uses of computer networks, with networks becoming more pervasive, there has been a need for more flexible and dynamic network management. To this end, the concept of Software-Defined Networking has evolved, taking the historically rigid realm of network management into open specifications and protocols. This paradigm shift from fixed-function to programmable platforms —referred to as softwarisation— has enabled innovation in both the management of networks, and how network devices process traffic. Network hardware can be involved not only in forwarding traffic, but also in actively determining how traffic is forwarded. In this thesis, we explore the intersection of programmable control with pro- grammable hardware. We examine how we can not only leverage existing technologies, but combine them to harness the benefits of distinct approaches. Building on this concept, we present a framework and prototype implementation to facilitate this combination with existing platforms. With the 4MIDable framework, we demonstrate how we can integrate existing network security appliances into emerging network architectures, disseminating their capability deeper into the network. We also show how programmable network infrastructure can be used to protect the network itself

Resilience to DDoS attacks

Tese de mestrado, Segurança Informática, 2022, Universidade de Lisboa, Faculdade de CiênciasDistributed Denial-of-Service (DDoS) is one of the most common cyberattack used by malicious actors. It has been evolving over the years, using more complex techniques to increase its attack power and surpass the current defense mechanisms. Due to the existent number of different DDoS attacks and their constant evolution, companies need to be constantly aware of developments in DDoS solutions Additionally, the existence of multiple solutions, also makes it hard for companies to decide which solution best suits the company needs and must be implemented. In order to help these companies, our work focuses in analyzing the existing DDoS solutions, for companies to implement solutions that can lead to the prevention, detection, mitigation, and tolerance of DDoS attacks, with the objective of improving the robustness and resilience of the companies against DDoS attacks. In our work, it is presented and described different DDoS solutions, some need to be purchased and other are open-source or freeware, however these last solutions require more technical expertise by cybersecurity agents. To understand how cybersecurity agents protect their companies against DDoS attacks, nowadays, it was built a questionnaire and sent to multiple cybersecurity agents from different countries and industries. As a result of the study performed about the different DDoS solutions and the information gathered from the questionnaire, it was possible to create a DDoS framework to guide companies in the decisionmaking process of which DDoS solutions best suits their resources and needs, in order to ensure that companies can develop their robustness and resilience to fight DDoS attacks. The proposed framework it is divided in three phases, in which the first and second phase is to understand the company context and the asset that need to be protected. The last phase is where we choose the DDoS solution based on the information gathered in the previous phases. We analyzed and presented for each DDoS solutions, which DDoS attack types they can prevent, detect and/or mitigate

Enhancing network robustness using software-defined networking

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringDon M. GruenbacherCaterina M. ScoglioAs today's networks are no longer individual networks, networks are less robust towards failures and attacks. For example, computer networks and power networks are interdependent. Computer networks provide smart control for power networks, while power networks provide power supply. Localized network failures and attacks are amplified and exacerbated back and forth between two networks due to their interdependencies. This dissertation focuses on finding solutions to enhance network robustness. Software-defined networking provides a programmable architecture, which can dynamically adapt to any changes and can reduce the complexities of network traffic management. This architecture brings opportunities to enhance network robustness, for example, adapting to network changes, routing traffic bypassing malfunction devices, dropping malicious flows, etc. However, as SDN is rapidly proceeding from vision to reality, the SDN architecture itself might be exposed to some robustness threats. Especially, the SDN control plane is tremendously attractive to attackers, since it is the "brain" of entire networks. Thus, researching on network robustness helps protect network from a destructive disaster. In this dissertation, we first build a novel, realistic interdependent network framework to model cyber-physical networks. We allocate dependency links under a limited budget and evaluate network robustness. We further revise a network flow algorithm and find solutions to obtain a basic robust network structure. Extensive simulations on random networks and real networks show that our deployment method produces topologies that are more robust than the ones obtained by other deployment techniques. Second, we tackle middlebox chain problems using SDN. In computer networks, applications require traffic to sequence through multiple types of middleboxes to accomplish network functionality. Middlebox policies, numerous applications' requirements, and resource allocations complicate network management. Furthermore, middlebox failures can affect network robustness. We formulate a mixed-integer linear programming problem to achieve a network load-balancing objective in the context of middlebox policy chain routing. Our global routing approach manages network resources efficiently by simplifying candidate-path selections, balancing the entire network and using the simulated annealing algorithm. Moreover, in case of middlebox failures, we design a fast rerouting mechanism by exploiting the remaining link and middlebox resources locally. We implement proposed routing approaches on a Mininet testbed and evaluate experiments' scalability, assessing the effectiveness of the approaches. Third, we build an adversary model to describe in detail how to launch distributed denial of service (DDoS) attacks to overwhelm the SDN controller. Then we discuss possible defense mechanisms to protect the controller from DDoS attacks. We implement a successful DDoS attack and our defense mechanism on the Mininet testbed to demonstrate its feasibility in the real world. In summary, we vertically dive into enhancing network robustness by constructing a topological framework, making routing decisions, and protecting the SDN controller

Deep learning : enhancing the security of software-defined networks

Software-defined networking (SDN) is a communication paradigm that promotes network flexibility and programmability by separating the control plane from the data plane. SDN consolidates the logic of network devices into a single entity known as the controller. SDN raises significant security challenges related to its architecture and associated characteristics such as programmability and centralisation. Notably, security flaws pose a risk to controller integrity, confidentiality and availability. The SDN model introduces separation of the forwarding and control planes. It detaches the control logic from switching and routing devices, forming a central plane or network controller that facilitates communications between applications and devices. The architecture enhances network resilience, simplifies management procedures and supports network policy enforcement. However, it is vulnerable to new attack vectors that can target the controller. Current security solutions rely on traditional measures such as firewalls or intrusion detection systems (IDS). An IDS can use two different approaches: signature-based or anomaly-based detection. The signature-based approach is incapable of detecting zero-day attacks, while anomaly-based detection has high false-positive and false-negative alarm rates. Inaccuracies related to false-positive attacks may have significant consequences, specifically from threats that target the controller. Thus, improving the accuracy of the IDS will enhance controller security and, subsequently, SDN security. A centralised network entity that controls the entire network is a primary target for intruders. The controller is located at a central point between the applications and the data plane and has two interfaces for plane communications, known as northbound and southbound, respectively. Communications between the controller, the application and data planes are prone to various types of attacks, such as eavesdropping and tampering. The controller software is vulnerable to attacks such as buffer and stack overflow, which enable remote code execution that can result in attackers taking control of the entire network. Additionally, traditional network attacks are more destructive. This thesis introduces a threat detection approach aimed at improving the accuracy and efficiency of the IDS, which is essential for controller security. To evaluate the effectiveness of the proposed framework, an empirical study of SDN controller security was conducted to identify, formalise and quantify security concerns related to SDN architecture. The study explored the threats related to SDN architecture, specifically threats originating from the existence of the control plane. The framework comprises two stages, involving the use of deep learning (DL) algorithms and clustering algorithms, respectively. DL algorithms were used to reduce the dimensionality of inputs, which were forwarded to clustering algorithms in the second stage. Features were compressed to a single value, simplifying and improving the performance of the clustering algorithm. Rather than using the output of the neural network, the framework presented a unique technique for dimensionality reduction that used a single value—reconstruction error—for the entire input record. The use of a DL algorithm in the pre-training stage contributed to solving the problem of dimensionality related to k-means clustering. Using unsupervised algorithms facilitated the discovery of new attacks. Further, this study compares generative energy-based models (restricted Boltzmann machines) with non-probabilistic models (autoencoders). The study implements TensorFlow in four scenarios. Simulation results were statistically analysed using a confusion matrix, which was evaluated and compared with similar related works. The proposed framework, which was adapted from existing similar approaches, resulted in promising outcomes and may provide a robust prospect for deployment in modern threat detection systems in SDN. The framework was implemented using TensorFlow and was benchmarked to the KDD99 dataset. Simulation results showed that the use of the DL algorithm to reduce dimensionality significantly improved detection accuracy and reduced false-positive and false-negative alarm rates. Extensive simulation studies on benchmark tasks demonstrated that the proposed framework consistently outperforms all competing approaches. This improvement is a further step towards the development of a reliable IDS to enhance the security of SDN controllers

A pattern-based framework for the design of secure and dependable SDN/NFV-enabled networks

As the world becomes an interconnected network where objects and humans interact, cyber and physical networks appear to play an important role in smart ecosystems due to their increasing use on critical infrastructure and smart cities. Software Defined Networking (SDN) and Network Function Virtualisation (NFV) are a promising combination for programmable connectivity, rapid service provisioning and service chaining as they offer the necessary end-to-end optimisations. However, with the actual exponential growth of connected devices, future networks, such as SDN and NFV, require open architectures, facilitated by standards and a strong ecosystem.In this thesis, a model-based approach is proposed to support the design and verification of secure and dependable SDN/NFV-enabled networks. The model is based on the development of a pattern-based approach to design executable patterns as solutions for reusable designs and interactions of objects, encoded in a rule based reasoning system, able to guarantee security and dependability (S&D) properties in SDN/NFV enabled networks. To execute S&D patterns, a pattern based framework is implemented for the insertion of patterns at design and at runtime level. The developed pattern framework highlights also the benefit of leveraging the flexibility of SDN/NFV-enabled networks to deploy enhanced reactive security mechanisms for the protection of the industrial network via the use of service function chaining (SFC). To prove the importance of this approach and the functionality of the pattern framework, different pattern instances are implemented to guarantee S&D in network infrastructures. The developed design patterns are able to design network topologies, guarantee network properties and offer security service provisioning and chaining. Finally, in order to evaluate the developed patterns in the pattern framework, three different use cases are described, where a number of usage scenarios are deployed and evaluated experimentally

On the Edge of Secure Connectivity via Software-Defined Networking

Securing communication in computer networks has been an essential feature ever since the Internet, as we know it today, was started. One of the best known and most common methods for secure communication is to use a Virtual Private Network (VPN) solution, mainly operating with an IP security (IPsec) protocol suite originally published in 1995 (RFC1825). It is clear that the Internet, and networks in general, have changed dramatically since then. In particular, the onset of the Cloud and the Internet-of-Things (IoT) have placed new demands on secure networking. Even though the IPsec suite has been updated over the years, it is starting to reach the limits of its capabilities in its present form. Recent advances in networking have thrown up Software-Defined Networking (SDN), which decouples the control and data planes, and thus centralizes the network control. SDN provides arbitrary network topologies and elastic packet forwarding that have enabled useful innovations at the network level. This thesis studies SDN-powered VPN networking and explains the benefits of this combination. Even though the main context is the Cloud, the approaches described here are also valid for non-Cloud operation and are thus suitable for a variety of other use cases for both SMEs and large corporations. In addition to IPsec, open source TLS-based VPN (e.g. OpenVPN) solutions are often used to establish secure tunnels. Research shows that a full-mesh VPN network between multiple sites can be provided using OpenVPN and it can be utilized by SDN to create a seamless, resilient layer-2 overlay for multiple purposes, including the Cloud. However, such a VPN tunnel suffers from resiliency problems and cannot meet the increasing availability requirements. The network setup proposed here is similar to Software-Defined WAN (SD-WAN) solutions and is extremely useful for applications with strict requirements for resiliency and security, even if best-effort ISP is used. IPsec is still preferred over OpenVPN for some use cases, especially by smaller enterprises. Therefore, this research also examines the possibilities for high availability, load balancing, and faster operational speeds for IPsec. We present a novel approach involving the separation of the Internet Key Exchange (IKE) and the Encapsulation Security Payload (ESP) in SDN fashion to operate from separate devices. This allows central management for the IKE while several separate ESP devices can concentrate on the heavy processing. Initially, our research relied on software solutions for ESP processing. Despite the ingenuity of the architectural concept, and although it provided high availability and good load balancing, there was no anti-replay protection. Since anti-replay protection is vital for secure communication, another approach was required. It thus became clear that the ideal solution for such large IPsec tunneling would be to have a pool of fast ESP devices, but to confine the IKE operation to a single centralized device. This would obviate the need for load balancing but still allow high availability via the device pool. The focus of this research thus turned to the study of pure hardware solutions on an FPGA, and their feasibility and production readiness for application in the Cloud context. Our research shows that FPGA works fluently in an SDN network as a standalone IPsec accelerator for ESP packets. The proposed architecture has 10 Gbps throughput, yet the latency is less than 10 µs, meaning that this architecture is especially efficient for data center use and offers increased performance and latency requirements. The high demands of the network packet processing can be met using several different approaches, so this approach is not just limited to the topics presented in this thesis. Global network traffic is growing all the time, so the development of more efficient methods and devices is inevitable. The increasing number of IoT devices will result in a lot of network traffic utilising the Cloud infrastructures in the near future. Based on the latest research, once SDN and hardware acceleration have become fully integrated into the Cloud, the future for secure networking looks promising. SDN technology will open up a wide range of new possibilities for data forwarding, while hardware acceleration will satisfy the increased performance requirements. Although it still remains to be seen whether SDN can answer all the requirements for performance, high availability and resiliency, this thesis shows that it is a very competent technology, even though we have explored only a minor fraction of its capabilities