Biblio

Internet of Things (IoT) is flourishing in several application areas, such as smart cities, smart factories, smart homes, smart healthcare, etc. With the adoption of IoT in critical scenarios, it is crucial to investigate its security aspects. All the layers of IoT are vulnerable to severely disruptive attacks. However, the attacks in IoT Network layer have a high impact on communication between the connected objects. Routing in most of the IoT networks is carried out by IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). RPL-based IoT offers limited protection against routing attacks. A trust-based approach for routing security is suitable to be integrated with IoT systems due to the resource-constrained nature of devices. This research proposes a trust-based secure routing protocol to provide security against packet dropping attacks in RPL-based IoT networks. IoT networks are dynamic and consist of both static and mobile nodes. Hence the chosen trust metrics in the proposed method also include the mobility-based metrics for trust evaluation. The proposed solution is integrated into RPL as a modified objective function, and the results are compared with the default RPL objective function, MRHOF. The analysis and evaluation of the proposed protocol indicate its efficacy and adaptability in a mobile IoT environment.

Smart grid monitoring, automation and control will completely rely on PMU based sensor data soon. Accordingly, a high throughput, low latency Information and Communication Technology (ICT) infrastructure should be opted in this regard. Due to the low cost, low power profile, dynamic nature, improved accuracy and scalability, wireless sensor networks (WSNs) can be a good choice. Yet, the efficiency of a WSN depends a lot on the network design and the routing technique. In this paper a new design of the ICT network for smart grid using WSN is proposed. In order to understand the interactions between different entities, detect their operational levels, design the routing scheme and identify false data injection by particular ICT entities, a new model of interdependency called the Multi State Implicative Interdependency Model (MSIIM) is proposed in this paper, which is an updated version of the Modified Implicative Interdependency Model (MIIM) [1]. MSIIM considers the data dependency and operational accuracy of entities together with structural and functional dependencies between them. A multi-path secure routing technique is also proposed in this paper which relies on the MSIIM model for its functioning. Simulation results prove that MSIIM based False Data Injection (FDI) detection and mitigation works better and faster than existing methods.

Underwater Wireless Sensor Networks (UWSN) has vast application areas. Due to the unprotected nature, underwater security is a prime concern. UWSN becomes vulnerable to different attacks due to malicious nodes. Sybil attack is one of the major attacks in UWSN. Most of the proposed security methods are based on encryption and decryption which consumes resources of the sensor nodes. In this paper, a simple authentication mechanism is proposed for securing the UWSN from the Sybil attack. As the nodes have very less computation power and energy resources so this work is not followed any kind of encryption and decryption technique. An authentication process is designed in such a way that node engaged in communication authenticate neighboring nodes by node ID and the data stored in the cluster head. This work is also addressed sensor node compromisation issue through Hierarchical Fuzzy System (HFS) based trust management model. The trust management model has been simulated in Xfuzzy-3.5. After the simulation conducted, the proposed trust management mechanism depicts significant performance on detecting compromised nodes.

Underwater networks have the potential to enable unexplored applications and to enhance our ability to observe and predict the ocean. Underwater acoustic sensor networks (UASNs) are often deployed in unprecedented and hostile waters and face many security threats. Applications based on UASNs such as coastal defense, pollution monitoring, assisted navigation to name a few, require secure communication. A new set of communication protocols and cooperative coordination algorithms have been proposed to enable collaborative monitoring tasks. However, such protocols overlook security as a key performance indicator. Spoofing, altering, or replaying routing information can affect the entire network, making UASN vulnerable to routing attacks such as selective forwarding, sinkhole attack, Sybil attack, acknowledgement spoofing and HELLO flood attack. The lack of security against such threats is startling if maintained that security is indeed an important requirement in many emerging civilian and military applications. In this work, we look at one of the most prevalent attacks among UASNs which is Sybill attack and discuss mitigation approaches for it. Then, feasibly implemented the attack in UnetStack3 to simulate real-life scenario.

Security is the main concern for wireless sensor nodes and exposed against malicious attacks. To secure the communication between sensor nodes several key managing arrangements are already implemented. The key managing method for any protected application must minimally deliver safety facilities such as truthfulness. Diffie–Hellman key exchange in the absence of authentication is exposed to MITM (man-in-the-middle) attacks due to which the attacker node can easily interrupt the communication, by appearing as a valid node in the network. In wireless sensor networks, single path routing is very common but it suffers with the two problems i:e link failure which results in data loss and if any node in single path is compromised, there is no alternative to send the data to the destination securely. To overcome this problem, multipath routing protocol is used which provides both availability and consistency of data. AOMDV (Ad-hoc On-demand Multipath Distance Vector Routing Protocol) is used in a proposed algorithm which provides alternative paths to reach the data packets to the destination. This paper presents an algorithm DH-SAM (Diffie-Hellman- Sybil Attack Mitigation) to spot and mitigate Sybil nodes and make the network trusted with the objective of solving the issue of MITM attack in the network. After node authentication, secure keys are established between two communicating nodes for data transmission using the Diffie-Hellman algorithm. Performance evaluation of DH-SAM is done by using different metrics such as detection rate, PDR, throughput, and average end to end (AE2E) delay.

Cyber attacks are increasing at a rapid pace targeting financial institutions and the corporate sector, especially during pandemics such as COVID-19. Honeypots are implemented in data centers and servers, to capture these types of attacks and malicious activities. In this work, an experimental prototype is created simulating the attacker and victim environments and the results are consolidated. Attacker information is extracted using the Meterpreter framework and uses reverse TCP for capturing the data. Normal honeypots does not capture an attacker and his identity. Information such as user ID, Internet Protocol(IP) address, proxy servers, incoming and outgoing traffic, webcam snapshot, Media Access Control(MAC) address, operating system architecture, and router information of the attacker such as ARP cache can be extracted by this honeypot with "biteback" feature.

The ecosystem of the Internet of Things (IoT) continues growing now and covers more and more fields. One of these areas is the Industrial Internet of Things (IIoT) which integrates sensors and actuators, business applications, open web applications, multimedia security systems, positioning, and tracking systems. Each of these components creates its own data stream and has its own parameters of the probability distribution when transmitting information packets. One such distribution, specific to the TrumpfTruPrint 1000 IIoT system, is the beta distribution. We described issues of the processing of such a data flow by an agent model of the \$5\textbackslashtextbackslashtimes5\$ NoC switch fabric. The concepts of modern telecommunication networks 5G/6G imply the processing of “small” data in the place of their origin, not excluding the centralized processing of big data. This process, which involves the transmission, distribution, and processing of data, involves a large number of devices: routers, multiprocessor systems, multi-core systems, etc. We assumed that the data stream is processed by a device with the network structure, such as NoC, and goes to its built-in router. We carried out a study how the average queues of the \$5\textbackslashtextbackslashtimes5\$ router change with changes in the parameters of a data stream that has a beta distribution.

Numerous measurement researches have been performed to discover the IPv4 network security issues by leveraging the fast Internet-wide scanning techniques. However, IPv6 brings the 128-bit address space and renders brute-force network scanning impractical. Although significant efforts have been dedicated to enumerating active IPv6 hosts, limited by technique efficiency and probing accuracy, large-scale empirical measurement studies under the increasing IPv6 networks are infeasible now. To fill this research gap, by leveraging the extensively adopted IPv6 address allocation strategy, we propose a novel IPv6 network periphery discovery approach. Specifically, XMap, a fast network scanner, is developed to find the periphery, such as a home router. We evaluate it on twelve prominent Internet service providers and harvest 52M active peripheries. Grounded on these found devices, we explore IPv6 network risks of the unintended exposed security services and the flawed traffic routing strategies. First, we demonstrate the unintended exposed security services in IPv6 networks, such as DNS, and HTTP, have become emerging security risks by analyzing 4.7M peripheries. Second, by inspecting the periphery's packet routing strategies, we present the flawed implementations of IPv6 routing protocol affecting 5.8M router devices. Attackers can exploit this common vulnerability to conduct effective routing loop attacks, inducing DoS to the ISP's and home routers with an amplification factor of \textbackslashtextbackslashgt 200. We responsibly disclose those issues to all involved vendors and ASes and discuss mitigation solutions. Our research results indicate that the security community should revisit IPv6 network strategies immediately.

The initially designed internet aimed to create a communication network. The hosts share specific IP addresses to establish a communication channel to transfer messages. However, with the advancement of internet technologies as well as recent growth in various applications such as social networking, web sites, and number of smart phone users, the internet today act as distribution network. The content distribution for large volume traffic on internet mainly suffers from two issues 1) IP addresses allocation for each request message and 2) Real time content delivery. Moreover, users nowadays care only about getting data irrespective of its location. To meet need of the hour for content centric networking (CCN), Information centric networking (ICN) has been proposed as the future internet architecture. Named data networks (NDN) found its roots under the umbrella of ICN as one of its project to overcome the above listed issues. NDN is based on the technique of providing named data retrieval from intermediate nodes. This conceptual shift raises questions on its design, services and challenges. In this paper, we contribute by presenting architectural design of NDN with its routing and forwarding mechanism. Subsequently, we cover services offered by NDN for request-response message communication. Furthermore, the challenges faced by NDN for its implementation has been discussed in last.

Network-on-Chip (NoC) is widely used as an efficient communication architecture in multi-core and many-core System-on-Chips (SoCs). However, the shared communication resources in NoCs, e.g., channels, buffers, and routers might be used to conduct attacks compromising the security of NoC-based SoCs. Almost all of the proposed encryption-based protection methods in the literature need to leave some parts of the packet unencrypted to allow the routers to process/forward packets accordingly. This uncovers the source/destination information of the packet to malicious routers, which can be used in various attacks. In this paper, we propose the idea of secure anonymous routing with minimal hardware overhead to hide the source/destination information while exchanging secure information over the network. The proposed method uses a novel source-routing algorithm that works with encrypted destination addresses and prevents malicious routers from discovering the source/destination of secure packets. To support our proposal, we have designed and implemented a new NoC architecture that works with encrypted addresses. The conducted hardware evaluations show that the proposed security solution combats the security threats at an affordable cost of 1% area and 10% power overheads chip-wide.

Tor is a famous routing overlay network based on the Onion multi-layered encryption to support communication anonymity in a threat model in which some network nodes are malicious. However, Tor does not provide any protection against the global passive adversary. In this threat model, an idea to obtain recipient anonymity, which is enough to have relationship anonymity, is to hide the recipient among a sufficiently large anonymity set. However, this would lead to high latency both in the set-up phase (which has a quadratic cost in the number of involved nodes) and in the successive communication. In this paper, we propose a way to arrange a Tor circuit with a tree-like topology, in which the anonymity set consists of all its nodes, whereas set-up and communication latency depends on the number of the sole branch nodes (which is a small fraction of all the nodes). Basically, the cost goes down from quadratic to linear. Anonymity is obtained by applying a broadcast-based technique for the forward message, and cover traffic (generated by the terminal-chain nodes) plus mixing over branch nodes, for the response.

Anonymous Communication Networks (ACNs) are networks in which, beyond data confidentiality, also traffic flow confidentiality is provided. The most popular routing approach for ACNs also used in practice is Onion. Onion is based on multiple encryption wrapping combined with the proxy mechanism (relay nodes). However, it offers neither sender anonymity nor recipient anonymity in a global passive adversary model, simply because the adversary can observe (at the first relay node) the traffic coming from the sender, and (at the last relay node) the traffic delivered to the recipient. This may also cause a loss of relationship anonymity if timing attacks are performed. This paper presents Onion-Ring, a routing protocol that improves anonymity of Onion in the global adversary model, by achieving sender anonymity and recipient anonymity, and thus relationship anonymity.

Mobile Ad-hoc Networks (MANET) is an autonomous network consisting of movable devices that can form a network using wireless media. MANET routing protocols can be used for selecting an efficient and shortest path for data transmission between nodes in a smart environment formed by the Internet of Things (IoT). Networking in such MANET-enabled IoT system is based on the routing protocols of MANET, data sensing from things, and data handling and processing using IoT. This paper studies proactive approach-based secure routing protocols for MANET-enabled IoT and analyses these protocols to identify security issues in it. Since this fusion network is resource-constrained in nature, each of the studied protocol is evaluated to check if it is lightweight or not. Also, the solution to defend against active attacks in this network is discussed.

The Intrusion Detection System (IDS) is one of the technologies available to protect mobile ad hoc networks. The system monitors the network and detects intrusion from malicious nodes, aiming at passive (eavesdropping) or positive attack to disrupt the network. This paper proposes a new Intrusion detection system using three Machine Learning (ML) techniques. The ML techniques were Random Forest (RF), support vector machines (SVM), and Naïve Bayes(NB) were used to classify nodes in MANET. The data set was generated by the simulator network simulator-2 (NS-2). The routing protocol was used is Dynamic Source Routing (DSR). The type of IDS used is a Network Intrusion Detection System (NIDS). The dataset was pre-processed, then split into two subsets, 67% for training and 33% for testing employing Python Version 3.8.8. Obtaining good results for RF, SVM and NB when applied randomly selected features in the trial and error method from the dataset to improve the performance of the IDS and reduce time spent for training and testing. The system showed promising results, especially with RF, where the accuracy rate reached 100%.

Mobile Ad hoc Networks ‘MANETs’ are still defenseless against peripheral threats due to the fact that this network has vulnerable access and also the absence of significant fact of administration. The black hole attack is a kind of some routing attack, in this type of attack the attacker node answers to the Route Requests (RREQs) thru faking and playing itself as an adjacent node of the destination node in order to get through the data packets transported from the source node. To counter this situation, we propose to deploy some nodes (exhibiting some distinctive functionality) in the network called DPS (Detection and Prevention System) nodes that uninterruptedly monitor the RREQs advertised by all other nodes in the networks. DPS nodes target to satisfy the set objectives in which it has to sense the mischievous nodes by detecting the activities of their immediate neighbor. In the case, when a node demonstrates some peculiar manners, which estimates according to the experimental data, DPS node states that particular distrustful node as black hole node by propagation of a threat message to all the remaining nodes in the network. A protocol with a clustering approach in AODV routing protocol is used to sense and avert the black hole attack in the mentioned network. Consequently, empirical evaluation shows that the black hole node is secluded and prohibited from the whole system and is not allowed any data transfer from any node thereafter.

In the recent years, mobile ad hoc wireless networks (MANETs) have experienced a tremendous rise in popularity and usage due to their flexibility and ability to provide connectivity from anywhere at any time. In general, MANETs provide mobile communication to participating nodes in situation where nodes do not need access to an existing network infrastructure. MANETs have a network topology that changes over time due to lack of infrastructure and mobility of nodes. Detection of a malicious node in MANETs is hard to achieve due to the dynamic nature of the relationships between moving node and the nature of the wireless channel. Most traditional Intrusion Detection System (IDS) are designed to operate in a centralized manner; and do not operate properly in MANET because data in MANETs is distributed in different network devices. In this paper, we present an Hierarchical Cooperative Intrusion Detection Method (HCIDM) to secure packets routing in MANETs. HCIDM is a distributed intrusion detection mechanism that uses collaboration between nodes to detect active attacks against the routing table of a mobile ad hoc network. HCIDM reduces the effectiveness of the attack by informing other nodes about the existence of a malicious node to keep the performance of the network within an acceptable level. The novelty of the mechanism lies in the way the responsibility to protect the networks is distributed among nodes, the trust level is computed and the information about the presence of a malicious is communicated to potential victim. HCIDM is coded using the Network Simulator (NS-2) in an ad hoc on demand distance vector enable MANET during a black hole attack. It is found that the HCIDM works efficiently in comparison with an existing Collaborative Clustering Intrusion Detection Mechanism (CCIDM), in terms of delivery ratio, delay and throughput.

Mobile Ad Hoc Network (MANET) is one of the types of Ad-hoc Network which is comprised of wireless in a network. The main problem in this research is the vulnerability of the protocol routing Dymo against jellyfish attack, so it needs detection from a jellyfish attack. This research implements the DELPHI method to detect jellyfish attacks on a DYMO protocol which has better performance because the Delay Per-Hop Indicator (DELPHI) gathers the amount of hop and information delay from the disjoint path and calculates the delays per-hop as an indicator of a jellyfish attack. The evaluation results indicate an increase in the end-to-end delay average, start from 112.59s in 10 nodes increased to 143.732s in 30 nodes but reduced to 84,2142s in 50 nodes. But when the DYMO routing did not experience any jellyfish attacks both the delivery ratio and throughput are decreased. The delivery ratio, where decreased from 10.09% to 8.19% in 10 nodes, decreased from 20.35% to 16.85%, and decreased from 93.5644% to 82.825% in 50 nodes. As for the throughput, for 10 nodes decreased from 76.7677kbps to 68.689kbps, for 30 nodes decreased from 100kbps to 83.5821kbps and for 50 nodes decreased from 18.94kbps to 15.94kbps.

One of the most dynamic network is the Mobile Adhoc (MANET) network. It is a list of numerous mobile nodes. Dynamic topology and lack of centralization are the basic characteristics of MANET. MANETs are prone to many attacks due to these characteristics. One of the attacks carried out on the network layer is the blackhole attack. In a black-hole attack, by sending false routing information, malicious nodes interrupt data transmission. There are two kinds of attacks involving a black-hole, single and co-operative. There is one malicious node in a single black-hole attack that can act as the node with the highest sequence number. The node source would follow the direction of the malicious node by taking the right direction. There is more than one malicious node in the collaborative black-hole attack. One node receives a packet and sends it to another malicious node in this attack. It is very difficult to detect and avoid black-hole attacks. Many researchers have invented black-hole attack detection and prevention systems. In this paper, We find a problem in the existing solution, in which validity bit is used. This paper also provides a comparative study of many scholars. The source node is used to detect and prevent black hole attacks by using a binary partition clustering based algorithm. We compared the performance of the proposed solution with existing solution and shown that our solution outperforms the existing one.

Logic locking is a well-explored defense mechanism against various types of hardware security attacks. Recent approaches to logic locking replace portions of a circuit with reconfigurable blocks such as look-up tables (LUTs) and switch boxes (SBs) to primarily achieve logic and routing obfuscation, respectively. However, these techniques may incur significant design overhead, and methods that can mitigate the implementation cost for a given security level are desirable. In this paper, we address this challenge by proposing an algorithm for deciding the location and inputs of the LUTs in LUT-based obfuscation to enhance security and reduce design overhead. We then introduce a locking method that combines LUTs with SBs to further robustify LUT-based obfuscation, largely independently of the specific LUT locations. We illustrate the effectiveness of the proposed approaches on a set of ISCAS benchmark circuits.

Over the past decade, an infotelecommunication technology has made significant strides forward. With the advent of new generation wireless networks and the massive digitalization of industries, the object of protection has changed. The digital transformation has led to an increased opportunity for cybercriminals. The ability of computational intelligence to quickly process large amounts of data makes the intrusions tailored to specific environments. Polymorphic attacks that have mutations in their sequences of acts adapt to the communication environments, operating systems and service frameworks, and also try to deceive the defense tools. The poor protection of most Internet of Things devices allows the attackers to take control over them creating the megabotnets. In this regard, traditional methods of network protection become rigid and low-effective. The paper reviews a computational intelligence (CI) enabled software- defined network (SDN) for the network management, providing dynamic network reconfiguration to improve network performance and security control. Advanced machine learning and artificial neural networks are promising in detection of false data injections. Bioinformatics methods make it possible to detect polymorphic attacks. Swarm intelligence detects dynamic routing anomalies. Quantum machine learning is effective at processing the large volumes of security-relevant datasets. The CI technology stack provides a comprehensive protection against a variative cyberthreats scope.

Adhoc On-demand Distance Vector (AODV) is the well-known reactive routing protocol of Mobile Adhoc Network (MANET). Absence of security mechanism in AODV disturbs the routing because of misbehavior of attack and hence, degrades MANET's performance. Secure and efficient routing is a need of various commercial and non-commercial applications of MANET including military and war, disaster and earthquake, and riot control. This paper presents a design of important network layer attacks include black-hole (BH), gray-hole (GH) and worm-hole (WH) attacks. The performance analysis of AODV protocol is carried out under the influence of each designed attack by using the network simulator, NetSim. Simulation results show that, the network layer attacks affect packet delivery ability of AODV protocol with low energy consumption and in short time. Design of attacks helps to understand attack's behavior and hence, to develop security mechanism in AODV.

Advancing artificial neural networks to the coherent optical domain offers several advantages, such as a filterless synaptic interconnect with increased routing flexibility. Towards this direction, a coherent synaptic receptor with integrated multiplication function will be experimentally evaluated for a 1-GHz train of 130-ps spikes.

Random K-out graphs, denoted \$$\backslash$mathbbH(n;K)\$, are generated by each of the \$n\$ nodes drawing \$K\$ out-edges towards \$K\$ distinct nodes selected uniformly at random, and then ignoring the orientation of the arcs. Recently, random K-out graphs have been used in applications as diverse as random (pairwise) key predistribution in ad-hoc networks, anonymous message routing in crypto-currency networks, and differentially-private federated averaging. In many applications, connectivity of the random K-out graph when some of its nodes are dishonest, have failed, or have been captured is of practical interest. We provide a comprehensive set of results on the connectivity and giant component size of \$$\backslash$mathbbH(n;K\_n,$\backslash$gamma\_n)\$, i.e., random K-out graph when \textsubscriptn of its nodes, selected uniformly at random, are deleted. First, we derive conditions for \textsubscriptn and \$n\$ that ensure, with high probability (whp), the connectivity of the remaining graph when the number of deleted nodes is \$$\backslash$gamma\_n=Ømega(n)\$ and \$$\backslash$gamma\_n=o(n)\$, respectively. Next, we derive conditions for \$$\backslash$mathbbH(n;K\_n, $\backslash$gamma\_n)\$ to have a giant component, i.e., a connected subgraph with \$Ømega(n)\$ nodes, whp. This is also done for different scalings of \textsubscriptn and upper bounds are provided for the number of nodes outside the giant component. Simulation results are presented to validate the usefulness of the results in the finite node regime.

Anonymity is an essential asset for a variety of communication systems, like humans' communication, the internet of things, and sensor networks. Establishing and maintaining such communication systems requires the exchange of information about their participants (called subjects). However, protecting anonymity reduces the availability of subject information, as these can be leveraged to break anonymity. Additionally, established techniques for providing anonymity often reduce the efficiency of communication networks. In this paper, we model four mechanisms to share routing information and discuss them with respect to their influence on anonymity and efficiency. While there is no ``one fits all'' solution, there are suitable trade-offs to establish routing information complying with the technical capabilities of the subjects. Distributed solutions like decentralized lookup tables reduce routing information in messages at the cost of local memory consumption; other mechanisms like multi-layer encrypted path information come with higher communication overhead but reduce memory consumption for each subject.

Cognitive Radio Networks (CRNs) promise efficient spectrum utilization by operating over the unused frequencies where Vehicular Ad-hoc Networks (VANETs) facilitate information exchanging among vehicles to avoid accidents, collisions, congestion, etc. Thus, CR enabled vehicular networks (CR-VANETs), a thriving area in wireless communication research, can be the enabler of Intelligent Transportation Systems (ITS) and autonomous driver-less vehicles. Similar to others, efficient and reliable communication in CR-VANETs is vital. Besides, security in such networks may exhibit unique characteristics for overall data transmission performance. For efficient and reliable communication, the proposed routing protocol considers the mobility patterns, spectrum availability, and trustworthiness to be the routing metrics. Hence, the protocol considers the vehicle's speed, mobility direction, inter-vehicles distance, and node's reliability to estimate the mobility patterns of a node. Besides, a trust-based reliability factor is also introduced to ensure secure communications by detecting malicious nodes or other external threats. Therefore, the proposed protocol detects malicious nodes by establishing trustworthiness among nodes and preserves security. Simulation is conducted for performance evaluation that shows the proposed routing selects the efficient routing path by discarding malicious nodes from the network and outperforms the existing routing protocols.