A software-defined architecture for next-generation cellular networks

In the recent years, mobile cellular networks are undergoing fundamental changes and many established concepts are being revisited. New emerging paradigms, such as Software-Defined Networking (SDN), Mobile Cloud Computing (MCC), Network Function Virtualization (NFV), Internet of Things (IoT),and Mobile Social Networking (MSN), bring challenges in the design of cellular networks architectures. Current Long-Term Evolution (LTE) networks are not able to accommodate these new trends in a scalable and efficient way. In this paper, first we discuss the limitations of the current LTE architecture. Second, driven by the new communication needs and by the advances in aforementioned areas, we propose a new architecture for next generation cellular networks. Some of its characteristics include support for distributed content routing, Heterogeneous Networks(HetNets) and multiple Radio Access Technologies (RATs). Finally, we present simulation results which show that significant backhaul traffic savings can be achieved by implementing caching and routing functions at the network edge

On the security of software-defined next-generation cellular networks

In the recent years, mobile cellular networks are ndergoing fundamental changes and many established concepts are being revisited. Future 5G network architectures will be designed to employ a wide range of new and emerging technologies such as Software Defined Networking (SDN) and Network Functions Virtualization (NFV). These create new virtual network elements each affecting the logic of the network management and operation, enabling the creation of new generation services with substantially higher data rates and lower delays. However, new security challenges and threats are also introduced. Current Long-Term Evolution (LTE) networks are not able to accommodate these new trends in a secure and reliable way. At the same time, novel 5G systems have proffered invaluable opportunities of developing novel solutions for attack prevention, management, and recovery. In this paper, first we discuss the main security threats and possible attack vectors in cellular networks. Second, driven by the emerging next-generation cellular networks, we discuss the architectural and functional requirements to enable appropriate levels of security

Proactive detection of DDOS attacks in Publish-Subscribe networks

Information centric networking (ICN) using architectures such as Publish-Subscribe Internet Routing Paradigm (PSIRP) or Publish-Subscribe Internet Technology (PURSUIT) has been proposed as an important candidate for the Internet of the future. ICN is an emerging research area that proposes a transformation of the current host centric Internet architecture into an architecture where information items are of primary importance. This change allows network functions such as routing and locating to be optimized based on the information items themselves. The Bloom filter based content delivery is a source routing scheme that is used in the PSIRP/PURSUIT architectures. Although this mechanism solves many issues of today’s Internet such as the growth of the routing table and the scalability problems, it is vulnerable to distributed denial-of-service (DDoS) attacks. In this paper, we present a new content delivery scheme that has the advantages of Bloom filter based approach while at the same time being able to prevent DDoS attacks on the forwarding mechanism. Our security analysis suggests that with the proposed approach, the forwarding plane is able to resist attacks such as DDoS with very high probabilit

Scalability of Information Centric Networking Using Mediated Topology Management

Information centric networking is a new concept that places emphasis on the information items themselves rather than on where the information items are stored. Consequently, routing decisions can be made based on the information items rather than on simply destination addresses. There are a number of models proposed for information centric networking and it is important that these models are investigated for their scalability if we are to move from early prototypes towards proposing that these models are used for networks operating at the scale of the current Internet. This paper investigates the scalability of an ICN system that uses mediation between information providers and information consumers using a publish/subscribe delivery mechanism. The scalability is investigated by extrapolating current IP traffic models for a typical national-scale network provider in the UK to estimate mediation workload. The investigation demonstrates that the mediation workload for route determination is on a scale that is comparable to, or less than, that of current IP routing while using a forwarding mechanism with considerably smaller tables than current IP routing tables. Additionally, the work shows that this can be achieved using a security mechanism that mitigates against maliciously injected packets thus stopping attacks such as denial of service that is common with the current IP infrastructure

Toward Information-Centric Software-Defined Cellular Networks

The concept of software-defined networking (SDN) is able to offer important advantages over the traditional communication paradigms. This is achieved by decoupling the decision-making process from the underlying network infrastructure that forwards the traffic. Recently, there have been efforts in applying the SDN approach to wireless and cellular networks. In fact, SDN is considered as one of the key enablers for future 5G communication networks. Information-centric networking (ICN) is another emerging communication paradigm that has been proposed to improve the content delivery efficiency compared to the traditional host-centric communication protocols. ICN decouples the data from their location, application, and means of transportation. This feature makes ICN particularly suitable for efficient dissemination of large volumes of data, especially in highly dynamic and heterogeneous mobile environments. In this work, we consider an SDN-enabled cellular network and propose an ICN protocol to ensure fast and efficient content dissemination to mobile users. The proposed protocol has been evaluated by means of computer simulations for the use case of a live video streaming service. Our experimental results show significant improvements in terms of response times over the current long-term evolution (LTE) networks

Thorough analysis of brute-force attacks on stateless forwarding in information centric networks

Abstract:Information-centric networking (ICN) is an emerging revolutionary technology that has recently gained lots of interest in the research community. ICN aims at solving the inefficiencies of the current Internet by promoting the information objects into the first class citizens. Information-aware routing, caching, and other network functions are expected to boost the network performance and to enable new, advanced services. Nevertheless, the ICN solutions proposed so far are not very mature for the security viewpoint. It has been demonstrated, that the basic ICN mechanisms are vulnerable to brute force and denial-of-service (DoS) attacks. In this paper, we first perform a thorough security analysis of one of the most popular ICN Bloom-filter based forwarding mechanisms. Next, we propose a mitigation technique that provides a sufficient level of security against brute-force attacks

Provable Privacy Preserving Authentication Solution for Internet of Things Environment

The Internet of Things (IoT) has become an important technology which permits different devices and machines to interconnect with each other using heterogeneous networks. The integration of numerous techniques is expected to offer extraordinary growth in future and current promising applications of IoT. In these days, the secure communication among interconnected IoT components has become an important issue of concern. Therefore, it has become a foremost need to design such authentication protocol which can make the secure communication among IoT components. In this article, we proposed an identity-based authentication and key agreement protocol for the IoT environment in order to offer the secure communication between various IoT entities. The devised protocol utilizes the physically unclonable function which helps to robustly resist the physical attack on IoT components. We analyze the proposed protocol informally which clearly shows that the proposed protocol offers the perfect forward secrecy, device anonymity and untraceability and also resists the desynchronization, IoT node impersonation and server impersonation attacks. The security features of proposed protocol are also analyzed formally using well known Random Oracle Model (ROM). Moreover, the performance of the devised protocol has also been determined in terms of communication and computational overhead. The performance and security analysis shows the supremacy of the devised protocol over the various related protocols

Attention Mechanism Guided Deep Regression Model for Acne Severity Grading

Acne vulgaris is the common form of acne that primarily affects adolescents, characterised by an eruption of inflammatory and/or non-inflammatory skin lesions. Accurate evaluation and severity grading of acne play a significant role in precise treatment for patients. Manual acne examination is typically conducted by dermatologists through visual inspection of the patient skin and counting the number of acne lesions. However, this task costs time and requires excessive effort by dermatologists. This paper presents automated acne counting and severity grading method from facial images. To this end, we develop a multi-scale dilated fully convolutional regressor for density map generation integrated with an attention mechanism. The proposed fully convolutional regressor module adapts UNet with dilated convolution filters to systematically aggregate multi-scale contextual information for density maps generation. We incorporate an attention mechanism represented by prior knowledge of bounding boxes generated by Faster R-CNN into the regressor model. This attention mechanism guides the regressor model on where to look for the acne lesions by locating the most salient features related to the understudied acne lesions, therefore improving its robustness to diverse facial acne lesion distributions in sparse and dense regions. Finally, integrating over the generated density maps yields the count of acne lesions within an image, and subsequently the acne count indicates the level of acne severity. The obtained results demonstrate improved performance compared to the state-of-the-art methods in terms of regression and classification metrics. The developed computer-based diagnosis tool would greatly benefit and support automated acne lesion severity grading, significantly reducing the manual assessment and evaluation workload.</jats:p