Biblio

The 5G network solutions currently standardised and deployed do not yet enable the full potential of pervasive networking and computing envisioned in 5G initial visions: network services and slices with different QoS profiles do not span multiple operators; security, trust and automation is limited. The evolution of 5G towards a truly production-level stage needs to heavily rely on automated end-to-end network operations, use of distributed Artificial Intelligence (AI) for cognitive network orchestration and management and minimal manual interventions (zero-touch automation). All these elements are key to implement highly pervasive network infrastructures. Moreover, Distributed Ledger Technologies (DLT) can be adopted to implement distributed security and trust through Smart Contracts among multiple non-trusted parties. In this paper, we propose an initial concept of a zero-touch security and trust architecture for ubiquitous computing and connectivity in 5G networks. Our architecture aims at cross-domain security & trust orchestration mechanisms by coupling DLTs with AI-driven operations and service lifecycle automation in multi-tenant and multi-stakeholder environments. Three representative use cases are identified through which we will validate the work which will be validated in the test facilities at 5GBarcelona and 5TONIC/Madrid.

With the development of network services and people's privacy requirements continue to increase. On the basis of providing anonymous user communication, it is necessary to protect the anonymity of the server. At the same time, there are many threatening crime messages in the dark network. However, many scholars lack the ability or expertise to conduct research on dark-net threat intelligence. Therefore, this paper designs a framework based on Hadoop is hidden threat intelligence. The framework uses HDFS as the underlying storage system to build a HBase-based distributed database to store and manage threat intelligence information. According to the heterogeneous type of the forum, the web crawler is used to collect data through the anonymous TOR tool. The framework is used to identify the characteristics of key dark network criminal networks, which is the basis for the later dark network research.

Distributed Denial of Service (DDoS) attack is one of the major threats to the network services. In this paper, we propose a DDoS attack detection algorithm based on the probability distributions of source IP addresses and destination IP addresses. According to the behavior of source and destination IP addresses during DDoS attack, the distance between these features is calculated and used.It is calculated with using the Greedy algorithm which eliminates some requirements associated with Kullback-Leibler divergence such as having the same rank of the probability distributions. Then frequency modulation is proposed in the detection phase to reduce false alarm rates and to avoid using static threshold. This algorithm is tested on the real data collected from Boğaziçi University network.

The amount of connected devices in the industrial environment is growing continuously, due to the ongoing demands of new features like predictive maintenance. New business models require more data, collected by IIoT edge node sensors based on inexpensive and low performance Microcontroller Units (MCUs). A negative side effect of this rise of interconnections is the increased attack surface, enabled by a larger network with more network services. Attaching badly documented and cheap devices to industrial networks often without permission of the administrator even further increases the security risk. A decent method to monitor the network and detect “unwanted” devices is network scanning. Typically, this scanning procedure is executed by a computer or server in each sub-network. In this paper, we introduce network scanning and mapping as a building block to scan directly from the Industrial Internet of Things (IIoT) edge node devices. This module scans the network in a pseudo-random periodic manner to discover devices and detect changes in the network structure. Furthermore, we validate our approach in an industrial testbed to show the feasibility of this approach.

The operation and management of network is facing increasing complexities brought by the evolution of network protocols and the demands of rapid service delivery. In this paper, we propose a programmable network management architecture, which manages network based on NETCONF protocol and provides REST APIs to upper layer so that further programming can be done based on the APIs to implement flexible management. Functions of devices can be modeled based on YANG language, and the models can be translated into REST APIs. We apply it to the management of ADN (Address Driven Network), an innovative network architecture proposed by Tsinghua University to inhibit IP spoofing, improve network security and provide high service quality. We model the functions of ADN based on YANG language, and implement the network management functions based on the REST APIs. We deploy and evaluate it in a laboratory environment. Test result shows that the programmable network management architecture is flexible to implement management for new network services.

The uptake of virtualization and cloud technologies has pushed novel development and operation models for the software, bringing more agility and automation. Unfortunately, cyber-security paradigms have not evolved at the same pace and are not yet able to effectively tackle the progressive disappearing of a sharp security perimeter. In this paper, we describe a novel cyber-security architecture for cloud-based distributed applications and network services. We propose a security orchestrator that controls pervasive, lightweight, and programmable security hooks embedded in the virtual functions that compose the cloud application, pursuing better visibility and more automation in this domain. Our approach improves existing management practice for service orchestration, by decoupling the management of the business logic from that of security. We also describe the current implementation stage for a programmable monitoring, inspection, and enforcement framework, which represents the ground technology for the realization of the whole architecture.

The intrinsic use of SDN/NFV technologies in 5G infrastructures promise to enable the flexibility and programmability of networks to ensure lower cost of network and service provisioning and operation, however it brings new challenges and requirements due to new architectural changes. In terms of security, authentication and authorization functions need to evolve towards the new and emerging 5G virtualization platforms in order to meet the requirements of service providers and infrastructure operators. Over the years, a lot of authentication techniques have been used. Now, a wide range of options arise allowing to extend existing authentication and authorization mechanisms. This paper focuses on proposing and showcasing a 5G platform oriented solution among different approaches to integrate authentication and authorization functionalities, an adapted secure and stateless mechanism, providing identity and permissions management to handle not only users, but also system micro-services, in a network functions virtualization management and orchestration (NFV MANO) system, oriented to deploy virtualized services. The presented solution uses the NFV-based SONATA Service Platform which offers capabilities for a continuous integration and delivery DevOps methodology that allow high levels of programmability and flexibility to manage the entire life cycle of Virtual Network Functions, and enables the perfect scenario to showcase different approaches for authentication and authorization mechanisms for users and micro-services in a 5G platform.

SDN is a new network architecture for control and data forwarding logic separation, able to provide a high degree of openness and programmability, with many advantages not available by traditional networks. But there are still some problems unsolved, for example, it is easy to cause the controller to be attacked due to the lack of verifying the source of the packet, and the limited range of match fields cannot meet the requirement of the precise control of network services etc. Aiming at the above problems, this paper proposes a SDN network security control forwarding mechanism based on cipher identification, when packets flow into and out of the network, the forwarding device must verify their source to ensure the user's non-repudiation and the authenticity of packets. Besides administrators control the data forwarding based on cipher identification, able to form network management and control capabilities based on human, material, business flow, and provide a new method and means for the future of Internet security.

As the number of devices that gain connectivity and join the category of smart-objects increases every year reaching unprecedented numbers, new challenges are imposed on our networks. While specialized solutions for certain use cases have been proposed, more flexible and scalable new approaches to networking will be required to deal with billions or trillions of smart objects connected to the Internet. With this paper, we take a step back looking at the set of basic problems that are posed by this group of devices. In order to develop an analysis on how these issues could be approached, we define which fundamental abstractions might help solving or at least reducing their impact on the network by offering support for fundamental matters such as mobility, group based delivery and support for distributed computing resources. Based on the concept of named-objects, we propose a set of solutions that network and show how this approach can address both scalability and functional requirements. Finally, we describe a comprehensive clean-slate network architecture (MobiityFirst) which attempts to realize the proposed capabilities.

ID/password-based authentication is commonly used in network services. Some users set different ID/password pairs for different services, but other users reuse a pair of ID/password to other services. Such recycling allows the list attack in which an adversary tries to spoof a target user by using a list of IDs and passwords obtained from other system by some means (an insider attack, malwares, or even a DB leakage). As a countermeasure agains the list attack, biometric authentication attracts much attention than before. In 2012, Hattori et al. proposed a cancelable biometrics authentication scheme (fundamental scheme) based on homomorphic encryption algorithms. In the scheme, registered biometric information (template) and biometric information to compare are encrypted, and the similarity between these biometric information is computed with keeping encrypted. Only the privileged entity (a decryption center), who has a corresponding decryption key, can obtain the similarity by decrypting the encrypted similarity and judge whether they are same or not. Then, Hirano et al. showed the replay attack against this scheme, and, proposed two enhanced authentication schemes. In this paper, we propose a spoofing attack against the fundamental scheme when the feature vector, which is obtained by digitalizing the analogue biometric information, is represented as a binary coding such as Iris Code and Competitive Code. The proposed attack uses an unexpected vector as input, whose distance to all possible binary vectors is constant. Since the proposed attack is independent from the replay attack, the attack is also applicable to two revised schemes by Hirano et al. as well. Moreover, this paper also discusses possible countermeasures to the proposed spoofing attack. In fact, this paper proposes a countermeasure by detecting such unexpected vector.