Biblio

Technological progress in cloud networking, 5G networks, and the IoT (Internet of Things) are remarkable. In addition, demands for flexible construction of SoEs (Systems on Engagement) for various type of businesses are increasing. In such environments, dynamic changes of network rules, such as access control (AC) or packet forwarding, are required to ensure function and security in networks. On the other hand, it is becoming increasingly difficult to grasp the exact situation in such networks by utilizing current well-known network verification technologies since a huge number of network rules are complexly intertwined. To mitigate these issues, we have proposed a scalable network verification approach utilizing the concept of "Packet Equivalence Class (PEC)," which enable precise network function verification by strictly recognizing the impact range of each network rule. However, this approach is still not scalable for very large-scale networks which consist of tens of thousands of routers. In this paper, we enhanced our impact range detection algorithm for practical large-scale networks. Through evaluation in the network with more than 80,000 AC rules, we confirmed that our enhanced algorithm can achieve precise impact range detection in under 600 seconds.

More than 75% of the Internet traffic is now encrypted, while this percentage is constantly increasing. The majority of communications are secured using common encryption protocols such as SSL/TLS and IPsec to ensure security and protect the privacy of Internet users. Yet, encryption can be exploited to hide malicious activities. Traditionally, network traffic inspection is based on techniques like deep packet inspection (DPI). Common applications for DPI include but are not limited to firewalls, intrusion detection and prevention systems, L7 filtering and packet forwarding. The core functionality of such DPI implementations is based on pattern matching that enables searching for specific strings or regular expressions inside the packet contents. With the widespread adoption of network encryption though, DPI tools that rely on packet payload content are becoming less effective, demanding the development of more sophisticated techniques in order to adapt to current network encryption trends. In this work, we present HeaderHunter, a fast signature-based intrusion detection system even in encrypted network traffic. We generate signatures using only network packet metadata extracted from packet headers. Also, to cope with the ever increasing network speeds, we accelerate the inner computations of our proposed system using off-the-shelf GPUs.

With the progress over technology, it is becoming viable to set up mobile ad hoc networks for non-military services as like well. Examples consist of networks of cars, law about communication facilities into faraway areas, and exploiting the solidity between urban areas about present nodes such as cellular telephones according to offload or otherwise keep away from using base stations. In such networks, there is no strong motive according to assume as the nodes cooperate. Some nodes may also be disruptive and partial may additionally attempt according to save sources (e.g. battery power, memory, CPU cycles) through “selfish” behavior. The proposed method focuses on the robustness of packet forwarding: keeping the usual packet throughput over a mobile ad hoc network in the rear regarding nodes that misbehave at the routing layer. Proposed system listen at the routing layer or function no longer try after address attacks at lower layers (eg. jamming the network channel) and passive attacks kind of eavesdropping. Moreover such functionate now not bear together with issues kind of node authentication, securing routes, or message encryption. Proposed solution addresses an orthogonal problem the encouragement concerning proper routing participation.

Tactical Mobile Ad-hoc NETworks (T-MANETs) are mainly used in self-configuring automatic vehicles and robots (also called nodes) for the rescue and military operations. A high dynamic network architecture, nodes unreliability, nodes misbehavior as well as an open wireless medium make it very difficult to assume the nodes cooperation in the `ad-hoc network or comply with routing rules. The routing protocols in the T-MANET are unprotected and subsequently result in various kinds of nodes misbehavior's (such as selfishness and denial of service). This paper introduces a comprehensive analysis of the packet dropping attack includes three types of misbehavior conducted by insiders in the T-MANETs namely black hole, gray hole, and selfish behaviours. An insider threat model is appended to a state-of-the-art routing protocol (such as DSR) and analyze the effect of packet dropping attack on the performance evaluation of DSR in the T-MANET. This paper contributes to the existing knowledge in a way it allows further security research to understand the behaviours of the main threats in MANETs which depends on nods defection in the packet forwarding. The simulation of the packet dropping attack is conducted using the Network Simulator 2 (NS2). It has been found that the network throughput has dropped considerably for black and gray hole attacks whereas the selfish nodes delay the network flow. Moreover, the packet drop rate and energy consumption rate are higher for black and gray hole attacks.

We propose a clean-slate network architecture called Centralized Identifier Network (CIN) which jointly considers the ideas of both control plane/forwarding plane separation and identifier/locator separation. In such an architecture, a controller cluster is designed to perform routers' link states gathering and routing calculation/handing out. Meanwhile, a tailor-made router without routing calculation function is designed to forward packets and communicate with its controller. Furthermore, A router or a host owns a globally unique ID and a host should be registered to a router whose ID will be the host's location. Control plane/forwarding plane separation enables CIN easily re-splitting the network functions into finer optional building blocks for sufficient flexibility and adaptability. Identifier/locator separation helps CIN deal with serious scaling problems and offer support for host mobility. This article mainly shows the routing mechanism of CIN. Furthermore, numerical results are presented to demonstrate the performance of the proposed mechanism.

The key challenge to a datacenter network is its scalability to handle many customers and their applications. In a datacenter network, packet classification plays an important role in supporting various network services. Previous algorithms store classification rules with the same length combinations in a hash table to simplify the search procedure. The search performance of hash-based algorithms is tied to the number of hash tables. To achieve fast and scalable packet classification, we propose an algorithm, encoded rule expansion, to transform rules into an equivalent set of rules with fewer distinct length combinations, without affecting the classification results. The new algorithm can minimize the storage penalty of transformation and achieve a short search time. In addition, the scheme supports fast incremental updates. Our simulation results show that more than 90% hash tables can be eliminated. The reduction of length combinations leads to an improvement on speed performance of packet classification by an order of magnitude. The results also show that the software implementation of our scheme without using any hardware parallelism can support up to one thousand customer VLANs and one million rules, where each rule consumes less than 60 bytes and each packet classification can be accomplished under 50 memory accesses.
 

Security issues in computer networks have focused on attacks on end systems and the control plane. An entirely new class of emerging network attacks aims at the data plane of the network. Data plane forwarding in network routers has traditionally been implemented with custom-logic hardware, but recent router designs increasingly use software-programmable network processors for packet forwarding. These general-purpose processing devices exhibit software vulnerabilities and are susceptible to attacks. We demonstrate-to our knowledge the first-practical attack that exploits a vulnerability in packet processing software to launch a devastating denial-of-service attack from within the network infrastructure. This attack uses only a single attack packet to consume the full link bandwidth of the router's outgoing link. We also present a hardware-based defense mechanism that can detect situations where malicious packets try to change the operation of the network processor. Using a hardware monitor, our NetFPGA-based prototype system checks every instruction executed by the network processor and can detect deviations from correct processing within four clock cycles. A recovery system can restore the network processor to a safe state within six cycles. This high-speed detection and recovery system can ensure that network processors can be protected effectively and efficiently from this new class of attacks.