Biblio

Network-on-Chip (NoC) is the communication platform of the data among the processing cores in Multiprocessors System-on-Chip (MPSoC). NoC has become a target to security attacks and by outsourcing design, it can be infected with a malicious Hardware Trojan (HT) to degrades the system performance or leaves a back door for sensitive information leaking. In this paper, we proposed a HT model that applies a denial of service attack by deliberately discarding the data packets that are passing through the infected node creating a black hole in the NoC. It is known as Black Hole Router (BHR) attack. We studied the effect of the BHR attack on the NoC. The power and area overhead of the BHR are analyzed. We studied the effect of the locations of BHRs and their distribution in the network as well. The malicious nodes has very small area and power overhead, 1.98% and 0.74% respectively, with a very strong violent attack.

The Named Data Network (NDN) is a promising network paradigm for content distribution based on caching. However, it may put consumer privacy at risk, as the adversary may identify the content, the name and the signature (namely a certificate) through side-channel timing responses from the cache of the routers. The adversary may identify the content name and the consumer node by distinguishing between cached and un- cached contents. In order to mitigate the timing attack, effective countermeasure methods have been proposed by other authors, such as random caching, random freshness, and probabilistic caching. In this work, we have implemented a timing attack scenario to evaluate the efficiency of these countermeasures and to demonstrate how the adversary can be detected. For this goal, a brute force timing attack scenario based on a real topology was developed, which is the first brute force attack model applied in NDN. Results show that the adversary nodes can be effectively distinguished from other legitimate consumers during the attack period. It is also proposed a multi-level mechanism to detect an adversary node. Through this approach, the content distribution performance can be mitigated against the attack.

Present networks within safety-critical systems rely on complex and inflexible network configurations. New technologies such as software-defined networking are more dynamic and offer more flexibility, but due care needs to be exercised to ensure that safety and security are not compromised by incorrect configurations. To this end, this paper proposes the use of pre-generated and optimized configuration templates. These provide alternate routes for traffic considering availability, resilience and timing constraints where network components fail due to attacks or faults.To obtain these templates, two heuristics based on Dijkstra's algorithm and an optimization algorithm providing the maximum resilience were investigated. While the configurations obtained through optimization yield appropriate templates, the heuristics investigated are not suitable to obtain configuration templates, since they cannot fulfill all requirements.

Large-scale failures in communication networks due to natural disasters or malicious attacks can severely affect critical communications and threaten lives of people in the affected area. In the absence of a proper communication infrastructure, rescue operation becomes extremely difficult. Progressive and timely network recovery is, therefore, a key to minimizing losses and facilitating rescue missions. To this end, we focus on network recovery assuming partial and uncertain knowledge of the failure locations. We proposed a progressive multi-stage recovery approach that uses the incomplete knowledge of failure to find a feasible recovery schedule. Next, we focused on failure recovery of multiple interconnected networks. In particular, we focused on the interaction between a power grid and a communication network. Then, we focused on network monitoring techniques that can be used for diagnosing the performance of individual links for localizing soft failures (e.g. highly congested links) in a communication network. We studied the optimal selection of the monitoring paths to balance identifiability and probing cost. Finally, we addressed, a minimum disruptive routing framework in software defined networks. Extensive experimental and simulation results show that our proposed recovery approaches have a lower disruption cost compared to the state-of-the-art while we can configure our choice of trade-off between the identifiability, execution time, the repair/probing cost, congestion and the demand loss.

A spectral-resource-utilization-efficient and highly resilient coarse granular routing optical network architecture is proposed. The improvement in network resiliency is realized by a novel concept named loop inflation that aims to enhance the geographical diversity of a working path and its redundant path. The trade-off between the inflation and the growth in circumference length of loops is controlled by the Simulated Annealing technique. Coarse granular routing is combined with resilient path design to realize higher spectral resource utilization. The routing scheme defines virtual direct links (VDLs) bridging distant nodes to alleviate the spectrum narrowing effect at the nodes traversed, allowing optical channels to be more densely accommodated by the fibers installed. Numerical experiments elucidate that the proposed networks successfully achieve a 30+0/0 route diversity improvement and a 12% fiber number reduction over conventional networks.

Routing on the Internet is defined among autonomous systems (ASes) based on a weak trust model where it is assumed that ASes are honest. While this trust model strengthens the connectivity among ASes, it results in an attack surface which is exploited by malicious entities to hijacking routing paths. One such attack is known as the BGP prefix hijacking, in which a malicious AS broadcasts IP prefixes that belong to a target AS, thereby hijacking its traffic. In this paper, we proposeRouteChain: a blockchain-based secure BGP routing system that counters BGP hijacking and maintains a consistent view of the Internet routing paths. Towards that, we leverage provenance assurance and tamper-proof properties of blockchains to augment trust among ASes. We group ASes based on their geographical (network) proximity and construct a bihierarchical blockchain model that detects false prefixes prior to their spread over the Internet. We validate strengths of our design by simulations and show its effectiveness by drawing a case study with the Youtube hijacking of 2008. Our proposed scheme is a standalone service that can be incrementally deployed without the need of a central authority.

Internet of Things is nowadays growing faster than ever before. Operators are planning or already creating dedicated networks for this type of devices. There is a need to create dedicated solutions for this type of network, especially solutions related to information security. In this article we present a mechanism of security-aware routing, which takes into account the evaluation of trust in devices and packet flows. We use trust relationships between flows and network nodes to create secure SDN paths, not ignoring also QoS and energy criteria. The system uses SDN infrastructure, enriched with Cognitive Packet Networks (CPN) mechanisms. Routing decisions are made by Random Neural Networks, trained with data fetched with Cognitive Packets. The proposed network architecture, implementing the security-by-design concept, was designed and is being implemented within the SerIoT project to demonstrate secure networks for the Internet of Things (IoT).

Military communities have come to rely heavily on commercial off the shelf (COTS) standards and technologies for Internet of Things (IoT) operations. One of the major obstacles to military use of COTS IoT devices is the security of data transfer. In this paper, we successfully design and develop a lightweight, trust-based security architecture to support routing in a mobile IoT network. Specifically, we modify the RPL IoT routing algorithm using common security techniques, including a nonce identity value, timestamp, and network whitelist. Our approach allows RPL to select a routing path over a mobile IoT wireless network based on a computed node trust value and average received signal strength indicator (ARSSI) value across network members. We conducted simulations using the Cooja network simulator and Wireshark to validate the algorithm against stipulated threat models. We demonstrate that our algorithm can protect the network against Denial of Service (DoS) and Sybil based identity attacks. We also show that the control overhead required for our algorithm is less than 5% and that the packet delivery rate improves by nearly 10%.

This research proposes an inspection on Trust Based Routing protocols to protect Internet of Things directing to authorize dependability and privacy amid to direction-finding procedure in inaccessible systems. There are number of Internet of Things (IOT) gadgets are interrelated all inclusive, the main issue is the means by which to protect the routing of information in the important systems from different types of stabbings. Clients won't feel secure on the off chance that they know their private evidence could without much of a stretch be gotten to and traded off by unapproved people or machines over the system. Trust is an imperative part of Internet of Things (IOT). It empowers elements to adapt to vulnerability and roughness caused by the through and through freedom of other devices. In Mobile Ad-hoc Network (MANET) host moves frequently in any bearing, so that the topology of the network also changes frequently. No specific algorithm is used for routing the packets. Packets/data must be routed by intermediate nodes. It is procumbent to different occurrences ease. There are various approaches to compute trust for a node such as fuzzy trust approach, trust administration approach, hybrid approach, etc. Adaptive Information Dissemination (AID) is a mechanism which ensures the packets in a specific transmission and it analysis of is there any attacks by hackers.It encompasses of ensuring the packet count and route detection between source and destination with trusted path.Trust estimation dependent on the specific condition or setting of a hub, by sharing the setting information onto alternate hubs in the framework would give a superior answer for this issue.Here we present a survey on various trust organization approaches in MANETs. We bring out instantaneous of these approaches for establishing trust of the partaking hubs in a dynamic and unverifiable MANET atmosphere.

The threat of side-channels is becoming increasingly prominent for resource-constrained internet-connected devices. While numerous power side-channel countermeasures have been proposed, a promising approach to protect the non-invasive electromagnetic side-channel attacks has been relatively scarce. Today's availability of high-resolution electromagnetic (EM) probes mandates the need for a low-overhead solution to protect EM side-channel analysis (SCA) attacks. This work, for the first time, performs a white-box analysis to root-cause the origin of the EM leakage from an integrated circuit. System-level EM simulations with Intel 32 nm CMOS technology interconnect stack, as an example, reveals that the EM leakage from metals above layer 8 can be detected by an external non-invasive attacker with the commercially available state-of-the-art EM probes. Equipped with this `white-box' understanding, this work proposes S℡LAR: Signature aTtenuation Embedded CRYPTO with Low-Level metAl Routing, which is a two-stage solution to eliminate the critical signal radiation from the higher-level metal layers. Firstly, we propose routing the entire cryptographic core within the local lower-level metal layers, whose leakage cannot be picked up by an external attacker. Then, the entire crypto IP is embedded within a Signature Attenuation Hardware (SAH) which in turn suppresses the critical encryption signature before it routes the current signature to the highly radiating top-level metal layers. System-level implementation of the S℡LAR hardware with local lower-level metal routing in TSMC 65 nm CMOS technology, with an AES-128 encryption engine (as an example cryptographic block) operating at 40 MHz, shows that the system remains secure against EM SCA attack even after 1M encryptions, with 67% energy efficiency and 1.23× area overhead compared to the unprotected AES.

The need for sensors to deliver, communicate, collect, alert, and share information in various applications has made wireless sensor networks very popular. However, due to its limited resources in terms of computation power, battery life and memory storage of the sensor nodes, it is challenging to add security features to provide the confidentiality, integrity, and availability. Blockchain technology ensures security and avoids the need of any trusted third party. However, applying Blockchain in a resource-constrained wireless sensor network is a challenging task because Blockchain is power, computation, and memory hungry in nature and demands heavy bandwidth due to control overheads. In this paper, a new routing and a private communication Blockchain framework is designed and tested with Constant Bit rate (CBR). The proposed Load Balancing Multi-Hop (LBMH) routing shares and enhances the battery life of the Cluster Heads and reduce control overhead during Block updates, but due to limited storage and energy of the sensor nodes, Blockchain in sensor networks may never become a reality unless computation, storage and battery life are readily available at low cost.

Many routing mechanisms of the wireless sensor network have been suggested in the literature, but there has not been a successful one that was designed with security. In this paper, we discuss the vulnerabilities of wireless sensor networks, how attackers can exploit these vulnerabilities, and the solutions to defend against these attacks. Furthermore, we will suggest solutions and measures secure routing mechanisms in sensor networks and study how it will affect it positively.

Wireless sensor networks are called wireless networks consisting of low-cost sensor nodes that use limited resources, collect and distribute data. Wireless sensor networks make observation and control of physical environments from distance easier. They are used in a variety of areas, such as environmental surveillance, military purposes, and the collection of information in specific areas. While the low cost of sensor nodes allows it to spread and increase it's quantitative, battery and computational constraints, noise and manipulation threats from the environment cause various challenges in wireless sensor applications. To overcome these challenges, researches have conducted a lot of researches on various fields like power consumption, use of resources and security approaches. In these studies, routing, placement algorithms and system designs are generally examined for efficient energy consumption. In this article, the relationship between the security of sensor networks and efficient resource usage and various scenarios are presented.

A recent proposed physical layer encryption technique uses an all-optical setup based on spatial light modulators to split two or more wavelength division multiplexed (WDM) signals in several spectral slices and to shuffle these slices. As a result, eavesdroppers aimed to recover information from a single target signal need to handle all the signals involved in the shuffling process. In this work, computer simulations are used to analyse the case where the shuffled signals propagate through different optical routes. From a security point of view, this is an interesting possibility because it obliges eavesdroppers to tap different optical fibres/ cables. On the other hand, each shuffled signal experiences different physical impairments and the deleterious consequences of these effects must be carefully investigated. Our results indicate that, in a metropolitan area network environment, penalties caused by attenuation and dispersion differences may be easily compensated with digital signal processing algorithms that are presently deployed.

Named Data Networking (NDN) is a promising candidate for future internet architecture. It is one of the implementations of the Information-Centric Networking (ICN) architectures where the focus is on the data rather than the owner of the data. While the data security is assured by definition, these networks are susceptible of various Denial of Service (DoS) attacks, mainly Interest Flooding Attacks (IFA). IFAs overwhelm an NDN router with a huge amount of interests (Data requests). Various solutions have been proposed in the literature to mitigate IFAs; however; these solutions do not make a difference between intentional and unintentional misbehavior due to the network congestion. In this paper, we propose a novel congestion-aware IFA detection and mitigation solution. We performed extensive simulations and the results clearly depict the efficiency of our proposal in detecting truly occurring IFA attacks.

Devices on the Internet of Things (IoT) are usually battery-powered and have limited resources. Hence, energy-efficient and lightweight protocols were designed for IoT devices, such as the popular Constrained Application Protocol (CoAP). Yet, CoAP itself does not include any defenses against denial-of-sleep attacks, which are attacks that aim at depriving victim devices of entering low-power sleep modes. For example, a denial-of-sleep attack against an IoT device that runs a CoAP server is to send plenty of CoAP messages to it, thereby forcing the IoT device to expend energy for receiving and processing these CoAP messages. All current security solutions for CoAP, namely Datagram Transport Layer Security (DTLS), IPsec, and OSCORE, fail to prevent such attacks. To fill this gap, Seitz et al. proposed a method for filtering out inauthentic and replayed CoAP messages "en-route" on 6LoWPAN border routers. In this paper, we expand on Seitz et al.'s proposal in two ways. First, we revise Seitz et al.'s software architecture so that 6LoWPAN border routers can not only check the authenticity and freshness of CoAP messages, but can also perform a wide range of further checks. Second, we propose a couple of such further checks, which, as compared to Seitz et al.'s original checks, more reliably protect IoT devices that run CoAP servers from remote denial-of-sleep attacks, as well as from remote exploits. We prototyped our solution and successfully tested its compatibility with Contiki-NG's CoAP implementation.

The intense incursion of the Internet of Things (IoT) into all areas of modern life has led to a need for a more detailed study of these technologies and their mechanisms of work. It is necessary to study mechanisms in order to improve QoS, security, identifying shortest routes, mobility, etc. This paper proposes an enhanced simulation framework that implements an improved mechanism for prioritising traffic on 6LoWPAN networks and the realisation of micro-mobility.

In recent years, the attacks on systems have increased and among such attack is Distributed Denial of Service (DDoS) attack. The path identifiers (PIDs) used for inter-domain routing are static, which makes it easier the attack easier. To address this vulnerability, this paper addresses the usage of Dynamic Path Identifiers (D-PIDs) for routing. The PID of inter-domain path connector is kept oblivious and changes dynamically, thus making it difficult to attack the system. The prototype designed with major components like client, server and router analyses the outcome of D-PID usage instead of PIDs. The results show that, DDoS attacks can be effectively prevented if Dynamic Path Identifiers (D-PIDs) are used instead of Static Path Identifiers (PIDs).

Vehicular ad hoc networks (VANETs) are eminent type of Mobile ad hoc Networks. The network created in VANETs is quite prone to security problem. In this work, a new mechanism is proposed to study the security of VANETs against DDoS attack. The proposed mechanism focuses on distributed denial of service attacks. The main idea of the paper is to detect the DDoS attack and mitigate it. The work consists of two stages, initially attack topology and network congestion is created. The second stage is to detect and mitigate the DDoS attack. The existing method is compared with the proposed method for mitigating DDoS attacks in VANETs. The existing solutions presented by the various researchers are also compared and analyzed. The solution for such kind of problem is provided which is used to detect and mitigate DDoS attack by using greedy approach. The network environment is created using NS-2. The results of simulation represent that the proposed approach is better in the terms of network packet loss, routing overhead and network throughput.

In recent time it has become very crucial for the data center networks (DCN) to broaden the system limit to be able to meet with the increasing need of cloud based applications. A decent DCN topology must comprise of numerous properties for low diameter, high bisection bandwidth, ease of organization and so on. In addition, a DCN topology should depict aptness in failure resiliency, scalability, construction and routing. In this paper, we introduce a new Data Center Network topology termed LevelTree built up with several modules grows as a tree topology and each module is constructed from a complete graph. LevelTree demonstrates great topological properties and it beats critical topologies like Jellyfish, VolvoxDC, and Fattree regarding providing a superior worthwhile plan with greater capacity.

Wireless sensor networks consist of various sensors that are deployed to monitor the physical world. And many existing security schemes use traditional cryptography theory to protect message content and contextual information. However, we are concerned about location security of nodes. In this paper, we propose an anonymous routing strategy for preserving location privacy (ARPLP), which sets a proxy source node to hide the location of real source node. And the real source node randomly selects several neighbors as receivers until the packets are transmitted to the proxy source. And the proxy source is randomly selected so that the adversary finds it difficult to obtain the location information of the real source node. Meanwhile, our scheme sets a branch area around the sink, which can disturb the adversary by increasing the routing branch. According to the analysis and simulation experiments, our scheme can reduce traffic consumption and communication delay, and improve the security of source node and base station.

Routers are important devices in the networks that carry the burden of transmitting information among the communication devices on the Internet. If a malicious adversary wants to intercept the information or paralyze the network, it can directly attack the routers and then achieve the suspicious goals. Thus, preventing router security is of great importance. However, router systems are notoriously difficult to understand or diagnose for their inaccessibility and heterogeneity. The common way of gaining access to the router system and detecting the anomaly behaviors is to inspect the router syslogs or monitor the packets of information flowing to the routers. These approaches just diagnose the routers from one aspect but do not consider them from multiple views. In this paper, we propose an approach to detect the anomalies and faults of the routers with multiple information learning. We try to use the routers' information not from the developer's view but from the user' s view, which does not need any expert knowledge. First, we do the offline learning to transform the benign or corrupted user actions into the syslogs. Then, we try to decide whether the input routers' conditions are poor or not with clustering. During the detection phase, we use the distance between the event and the cluster to decide if it is the anomaly event and we can provide the corresponding solutions. We have applied our approach in a university network which contains Cisco, Huawei and Dlink routers for three months. We aligned our experiment with former work as a baseline for comparison. Our approach can gain 89.6% accuracy in detecting the attacks which is 5.1% higher than the former work. The results show that our approach performs in limited time as well as memory usages and has high detection and low false positives.

With the growth of smartphone sales and app usage, fingerprinting and identification of smartphone apps have become a considerable threat to user security and privacy. Traffic analysis is one of the most common methods for identifying apps. Traditional countermeasures towards traffic analysis includes traffic morphing and multipath routing. The basic idea of multipath routing is to increase the difficulty for adversary to eavesdrop all traffic by splitting traffic into several subflows and transmitting them through different routes. Previous works in multipath routing mainly focus on Wireless Sensor Networks (WSNs) or Mobile Ad Hoc Networks (MANETs). In this paper, we propose a multipath routing scheme for smartphones with edge network assistance to mitigate traffic analysis attack. We consider an adversary with limited capability, that is, he can only intercept the traffic of one node following certain attack probability, and try to minimize the traffic an adversary can intercept. We formulate our design as a flow routing optimization problem. Then a heuristic algorithm is proposed to solve the problem. Finally, we present the simulation results for our scheme and justify that our scheme can effectively protect smartphones from traffic analysis attack.

MANET is vulnerable to so many attacks like Black hole, Wormhole, Jellyfish, Dos etc. Attackers can easily launch Wormhole attack by faking a route from original within network. In this paper, we propose an algorithm on AD (Absolute Deviation) of statistical approach to avoid and prevent Wormhole attack. Absolute deviation covariance and correlation take less time to detect Wormhole attack than classical one. Any extra necessary conditions, like GPS are not needed in proposed algorithms. From origin to destination, a fake tunnel is created by wormhole attackers, which is a link with good amount of frequency level. A false idea is created by this, that the source and destination of the path are very nearby each other and will take less time. But the original path takes more time. So it is necessary to calculate the time taken to avoid and prevent Wormhole attack. Better performance by absolute deviation technique than AODV is proved by simulation, done by MATLAB simulator for wormhole attack. Then the packet drop pattern is also measured for Wormholes using Absolute Deviation Correlation Coefficient.

A Mobile ad hoc network (MANET) is a set of nodes that communicate together in a cooperative way using the wireless medium, and without any central administration. Due to its inherent open nature and the lack of infrastructure, security is a complicated issue compared to other networks. That is, these networks are vulnerable to a a wide range of attacks at different network layers. At the network level, malicious nodes can perform several attacks ranging from passive eavesdropping to active interfering. Wormhole is an example of severe attack that has attracted much attention recently. It involves the redirection of traffic between two end-nodes through a Wormhole tunnel, and manipulates the routing algorithm to give illusion that nodes located far from each other are neighbors. To handle with this issue, we propose a novel detection model to allow a node to check whether a presumed shortest path contains a Wormhole tunnel or not. Our approach is based on the fact that the Wormhole tunnel reduces significantly the length of the paths passing through it.