Denial of Service (DoS) in Internet Protocol (IP) Network and Information Centric Network (ICN): An Impediment to Network Quality of Service (QoS).

This paper compares and analyses the Denial-of-Service attacks in the two different Network architectures. The two architectures are based on different routing approaches: Hop-by-Hop IP routing and source-routing using Bloom filters. In Hop-by-Hop IP routing, the packet header contains the address, and the route is decided node by node. Forwarding in this method requires a node to have a routing table which contains the port through which the packet should traverse depending on the address of the destination. Instead in source-routing, the forwarding identifier is encoded with the path a packet should take and it is placed in the packet header. The forwarding identifier in this approach does not require a forwarding table for look ups like the IP routing; it relies on Line Speed Publish/Subscribe (LIPSIN) forwarding solution that focuses on using named links not nodes or interfaces. The forwarding identifier encompasses a set of Link ID’s which specifies the path to the recipient and they are encoded in a Bloom filter. The In-packet Bloom filters serve as both path selectors and as capabilities, and they are generated dynamically. However, this thesis is going to focus on the latter network technology by looking at both its benefits and drawbacks as well as analysing the possibilities of having a Denial of service attack. Keywords: DoS, DDoS, TCP/IP Protocol Suite, ICMP flood, E-mail Bomb, Ping of Death, TCP and UD

5G Security Challenges and Solutions: A Review by OSI Layers

The Fifth Generation of Communication Networks (5G) envisions a broader range of servicescompared to previous generations, supporting an increased number of use cases and applications. Thebroader application domain leads to increase in consumer use and, in turn, increased hacker activity. Dueto this chain of events, strong and efficient security measures are required to create a secure and trustedenvironment for users. In this paper, we provide an objective overview of5G security issues and theexisting and newly proposed technologies designed to secure the5G environment. We categorize securitytechnologies usingOpen Systems Interconnection (OSI)layers and, for each layer, we discuss vulnerabilities,threats, security solutions, challenges, gaps and open research issues. While we discuss all sevenOSIlayers, the most interesting findings are in layer one, the physical layer. In fact, compared to other layers,the physical layer between the base stations and users’ device presents increased opportunities for attackssuch as eavesdropping and data fabrication. However, no singleOSI layer can stand on its own to provideproper security. All layers in the5G must work together, providing their own unique technology in an effortto ensure security and integrity for5G data

Information-Centric Design and Implementation for Underwater Acoustic Networks

Over the past decade, Underwater Acoustic Networks (UANs) have received extensive attention due to their vast benefits in academia and industry alike. However, due to the overall magnitude and harsh characteristics of underwater environments, standard wireless network techniques will fail because current technology and energy restrictions limit underwater devices due to delayed acoustic communications. To help manage these limitations we utilize Information-Centric Networking (ICN). More importantly, we look at ICN\u27s paradigm shift from traditional TCP/IP architecture to improve data handling and enhance network efficiency. By utilizing some of ICN\u27s techniques, such as data naming hierarchy, we can reevaluate each component of the network\u27s protocol stack given current underwater limitations to study the vast solutions and perspectives Information-Centric architectures can provide to UANs. First, we propose a routing strategy used to manage and route large data files in a network prone to high mobility. Therefore, due to UANs limited transmitting capability, we passively store sensed data and adaptively find the best path. Furthermore, we introduce adapted Named Data Networking (NDN) components to improve upon routing robustness and adaptiveness. Beyond naming data, we use tracers to assist in tracking stored data locations without using other excess means such as flooding. By collaborating tracer consistency with routing path awareness our protocol can adaptively manage faulty or high mobility nodes. Through this incorporation of varied NDN techniques, we are able to see notable improvements in routing efficiency. Second, we analyze the effects of Denial of Service (DoS) attacks on upper layer protocols. Since UANs are typically resource restrained, malicious users can advantageously create fake traffic to burden the already constrained network. While ICN techniques only provide basic DoS restriction we must expand our detection and restriction technique to meet the unique demands of UANs. To provide enhanced security against DoS we construct an algorithm to detect and restrict against these types of attacks while adapting to meet acoustic characteristics. To better extend this work we incorporate three node behavior techniques using probabilistic, adaptive, and predictive approaches for detecting malicious traits. Thirdly, to depict and test protocols in UANs, simulators are commonly used due to their accessibility and controlled testing aspects. For this section, we review Aqua-Sim, a discrete event-driven open-source underwater simulator. To enhance the core aspect of this simulator we first rewrite the current architecture and transition Aqua-Sim to the newest core simulator, NS-3. Following this, we clean up redundant features spread out between the various underwater layers. Additionally, we fully integrate the diverse NS-3 API within our simulator. By revamping previous code layout we are able to improve architecture modularity and child class expandability. New features are also introduced including localization and synchronization support, busy terminal problem support, multi-channel support, transmission range uncertainty modules, external noise generators, channel trace-driven support, security module, and an adapted NDN module. Additionally, we provide extended documentation to assist in user development. Simulation testing shows improved memory management and continuous validity in comparison to other underwater simulators and past iterations of Aqua-Sim

Enhancing Cache Robustness in Named Data Networks

Information-centric networks (ICNs) are a category of network architectures that focus on content, rather than hosts, to more effectively support the needs of today’s users. One major feature of such networks is in-network storage, which is realized by the presence of content storage routers throughout the network. These content storage routers cache popular content object chunks close to the consumers who request them in order to reduce latency for those end users and to decrease overall network congestion. Because of their prominence, network storage devices such as content storage routers will undoubtedly be major targets for malicious users. Two primary goals of attackers are to increase cache pollution and decrease hit rate by legitimate users. This would effectively reduce or eliminate the advantages of having in-network storage. Therefore, it is crucial to defend against these types of attacks. In this thesis, we study a specific ICN architecture called Named Data Networking (NDN) and simulate several attack scenarios on different network topologies to ascertain the effectiveness of different cache replacement algorithms, such as LRU and LFU (specifically, LFU-DA.) We apply our new per-face popularity with dynamic aging (PFP-DA) scheme to the content storage routers in the network and measure both cache pollution percentages as well as hit rate experienced by legitimate consumers. The current solutions in the literature that relate to reducing the effects of cache pollution largely focus on detection of attacker behavior. Since this behavior is very unpredictable, it is not guaranteed that any detection mechanisms will work well if the attackers employ smart attacks. Furthermore, current solutions do not consider the effects of a particularly aggressive attack against any single or small set of faces (interfaces.) Therefore, we have developed three related algorithms, namely PFP, PFP-DA, and Parameterized PFP-DA. PFP ensures that interests that ingress over any given face do not overwhelm the calculated popularity of a content object chunk. PFP normalizes the ranks on all faces and uses the collective contributions of these faces to determine the overall popularity, which in turn determines what content stays in the cache and what is evicted. PFP-DA adds recency to the original PFP algorithm and ensures that content object chunks do not remain in the cache longer than their true, current popularity dictates. Finally, we explore PFP-β, a parameterized version of PFP-DA, in which a β parameter is provided that causes the popularity calculations to take on Zipf-like characteristics, which in turn reduces the numeric distance between top rated items, and lower rated items, favoring items with multi-face contribution over those with single-face contributions and those with contributions over very few faces. We explore how the PFP-based schemes can reduce impact of contributions over any given face or small number of faces on an NDN content storage router. This in turn, reduces the impact that even some of the most aggressive attackers can have when they overwhelm one or a few faces, by normalizing the contributions across all contributing faces for a given content object chunk. During attack scenarios, we conclude that PFP-DA performs better than both LRU and LFU-DA in terms of resisting the effects of cache pollution and maintaining strong hit rates. We also demonstrate that PFP-DA performs better even when no attacks are being leveraged against the content store. This opens the door for further research both within and outside of ICN-based architectures as a means to enhance security and overall performance.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/145175/1/John Baugh Final Dissertation.pdfDescription of John Baugh Final Dissertation.pdf : Dissertatio

Machine Learning in IoT Security:Current Solutions and Future Challenges

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives. The participating nodes in IoT networks are usually resource-constrained, which makes them luring targets for cyber attacks. In this regard, extensive efforts have been made to address the security and privacy issues in IoT networks primarily through traditional cryptographic approaches. However, the unique characteristics of IoT nodes render the existing solutions insufficient to encompass the entire security spectrum of the IoT networks. This is, at least in part, because of the resource constraints, heterogeneity, massive real-time data generated by the IoT devices, and the extensively dynamic behavior of the networks. Therefore, Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, are leveraged to cope with different security problems. In this paper, we systematically review the security requirements, attack vectors, and the current security solutions for the IoT networks. We then shed light on the gaps in these security solutions that call for ML and DL approaches. We also discuss in detail the existing ML and DL solutions for addressing different security problems in IoT networks. At last, based on the detailed investigation of the existing solutions in the literature, we discuss the future research directions for ML- and DL-based IoT security

The use of computational intelligence for security in named data networking

Information-Centric Networking (ICN) has recently been considered as a promising paradigm for the next-generation Internet, shifting from the sender-driven end-to-end communication paradigma to a receiver-driven content retrieval paradigm. In ICN, content -rather than hosts, like in IP-based design- plays the central role in the communications. This change from host-centric to content-centric has several significant advantages such as network load reduction, low dissemination latency, scalability, etc. One of the main design requirements for the ICN architectures -since the beginning of their design- has been strong security. Named Data Networking (NDN) (also referred to as Content-Centric Networking (CCN) or Data-Centric Networking (DCN)) is one of these architectures that are the focus of an ongoing research effort that aims to become the way Internet will operate in the future. Existing research into security of NDN is at an early stage and many designs are still incomplete. To make NDN a fully working system at Internet scale, there are still many missing pieces to be filled in. In this dissertation, we study the four most important security issues in NDN in order to defense against new forms of -potentially unknown- attacks, ensure privacy, achieve high availability, and block malicious network traffics belonging to attackers or at least limit their effectiveness, i.e., anomaly detection, DoS/DDoS attacks, congestion control, and cache pollution attacks. In order to protect NDN infrastructure, we need flexible, adaptable and robust defense systems which can make intelligent -and real-time- decisions to enable network entities to behave in an adaptive and intelligent manner. In this context, the characteristics of Computational Intelligence (CI) methods such as adaption, fault tolerance, high computational speed and error resilient against noisy information, make them suitable to be applied to the problem of NDN security, which can highlight promising new research directions. Hence, we suggest new hybrid CI-based methods to make NDN a more reliable and viable architecture for the future Internet.Information-Centric Networking (ICN) ha sido recientemente considerado como un paradigma prometedor parala nueva generación de Internet, pasando del paradigma de la comunicación de extremo a extremo impulsada por el emisora un paradigma de obtención de contenidos impulsada por el receptor. En ICN, el contenido (más que los nodos, como sucede en redes IPactuales) juega el papel central en las comunicaciones. Este cambio de "host-centric" a "content-centric" tiene varias ventajas importantes como la reducción de la carga de red, la baja latencia, escalabilidad, etc. Uno de los principales requisitos de diseño para las arquitecturas ICN (ya desde el principiode su diseño) ha sido una fuerte seguridad. Named Data Networking (NDN) (también conocida como Content-Centric Networking (CCN) o Data-Centric Networking (DCN)) es una de estas arquitecturas que son objetode investigación y que tiene como objetivo convertirse en la forma en que Internet funcionará en el futuro. Laseguridad de NDN está aún en una etapa inicial. Para hacer NDN un sistema totalmente funcional a escala de Internet, todavía hay muchas piezas que faltan por diseñar. Enesta tesis, estudiamos los cuatro problemas de seguridad más importantes de NDN, para defendersecontra nuevas formas de ataques (incluyendo los potencialmente desconocidos), asegurar la privacidad, lograr una alta disponibilidad, y bloquear los tráficos de red maliciosos o al menos limitar su eficacia. Estos cuatro problemas son: detección de anomalías, ataques DoS / DDoS, control de congestión y ataques de contaminación caché. Para solventar tales problemas necesitamos sistemas de defensa flexibles, adaptables y robustos que puedantomar decisiones inteligentes en tiempo real para permitir a las entidades de red que se comporten de manera rápida e inteligente. Es por ello que utilizamos Inteligencia Computacional (IC), ya que sus características (la adaptación, la tolerancia a fallos, alta velocidad de cálculo y funcionamiento adecuado con información con altos niveles de ruido), la hace adecuada para ser aplicada al problema de la seguridad ND

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community