Pending Interest Table Control Management with Optimal Forwarder Selection in Named Data Network

Named data networking (NDN) supports receiver-driven content retrieval with stateful forwarding (pending interest table (PIT)/forwarding information base) and in-network caching, yet many deployments still rely on classical cryptography that may be undermined by quantum-capable adversaries. Despite NDN’s built-in data authenticity via producer signatures, quantum-enabled attacks become plausible once RSA/ECC-based trust anchors are weakened by Shor-type attacks. Existing quantum-security efforts for NDN largely focus on post-quantum replacements of signatures or key exchange, but do not address the tension between confidentiality-preserving payload protection and NDN’s in-network processing (forwarding/caching decisions) in a quantum setting. This paper presents a quantum-enhanced NDN architecture that preserves NDN’s content-centric semantics—naming, PIT-driven forwarding, and cache-assisted dissemination of verifiable control objects—while delivering privacy-sensitive payloads as quantum homomorphic encryption (QHE)-encrypted quantum states over an underlying quantum network. QHE provides end-to-end confidentiality and enables authorized operations on encrypted quantum payloads without exposing plaintext. To make the design compatible with NDN forwarding, the proposed protocol encrypts the payload while keeping name-based forwarding semantics intact, and supports ciphertext-domain processing for selected policy functions. To protect provenance and integrity of NDN metadata, routing instructions, and session state, we incorporate quantum digital signatures (QDS) bound to NDN names and session identifiers. The main contributions are: (i) a QHE+QDS layered protection model tailored to NDN’s Interest and Data exchange; (ii) a session workflow that couples proactive entanglement distribution with NDN-style stateful signaling for efficient establishment and recovery; and (iii) a security analysis clarifying the achieved guarantees and the remaining trust assumptions. Security analysis indicates robustness against quantum man-in-the-middle and tampering attacks, with modest overhead on NDN control traffic.

Named Data Networking (NDN) is a newly proposed next-generation Internet architecture that uses the name of data to forward and route packets. As a potential candidate for future Internet architecture, it is crucial to address the security and privacy issues in NDN. NDN is vulnerable to a new type of Distributed Denial of Service (DDoS) attacks called Interest Flooding Attacks (IFAs). The attackers can send a massive amount of Interest requests to overwhelm the Pending Interest Table (PIT) at routers resulting in network disruption for legitimate users. In this paper, we propose a Binary Tree-Based Interest Flooding Attack Detection and Mitigation Scheme (BTIFADMS) to protect NDNs. The proposed scheme allows each NDN router to use binary trees to detect IFAs and mitigates IFAs by limiting the number of Interest requests forwarded from the contaminated routers. The simulation evaluation shows that BTIFADMS can quickly and accurately identify and respond to the IFAs in the NDNs.

Named Data Networking (NDN) is a new network architecture derived from the success of the Internet. Specifically, NDN addresses and identifies data by naming. Source and destination host addresses are not required for data communication in the NDN because the data is uniquely named instead. In the NDN network, the Forwarding Information Base (FIB) table is responsible for data forwarding, the Pending Interest Table (PIT) is liable for holding the state of data forwarding process, and the Content Store (CS) is used to stock data chunks within the network to optimize the forwarding time to the data without contacting to the content producer. All these data structures consume the memory of devices existing in the Named Data Networking of Things (NDNoT). Accordingly, the size of the FIB, PIT and CS needs to be carefully adjusted in NDNoT environments for performance tuning and Quality of Service (QoS) provisioning. In this study, we explore the issues of FIB sizing on average and maximum occupancy, reliability and maximum delay for constant bit rate (CBR) traffic where each content producer is addressed with a prefix name in the Cooja simulator environment. The results indicate that FIB table size has an impact on the reliability and maximum delay. During the number of records in FIB outpaces the count of nodes in the network, the reliability decreases gradually. Therefore, in constrained NDNoT environment careful allocation of the memory among FIB, PIT and CS becomes an important issue. According to our knowledge so far, this work is the first study showing the effect of FIB table on the performance in an NDNoT environment.

The large expansion in network services and applications seen in the last few years requires new network architectures to satisfy an increasing number of users and enhance content delivery. Named Data Networking (NDN) has recently appeared as a new paradigm to solve many shortcomings in the current TCP/IP architecture. Its main characteristics like stateful forwarding and in-network caching made NDN networks an efficient environment for data delivery where the data is retrieved based on content names rather than IP addresses. The NDN, by its nature, defends against the well-known Distributed Denial of Service (DDoS) attacks that take place in the traditional TCP/IP architecture. However, a special kind of DoS attack called Collusive Interest Flooding Attack (CIFA) has appeared to overwhelm the resources of NDN routers by filling their Pending Interest Tables (PIT) with long-lasting malicious entries. The network throughput and consumer satisfaction rate are highly affected by CIFA. A lightweight yet efficient stateless CIFA detection algorithm is proposed in this research utilizing the non-parametric CUSUM algorithm; a change point detection approach that detects the point in time when a transition occurs in the network. The proposed algorithm is characterized by its low computational overhead, highly accurate detection, and quick response. To detect the malicious name prefixes and eliminate the CIFA effect, a mitigation algorithm that uses the average response time vales of all name prefixes is proposed in this research. Experimental results show that this approach detects CIFA after 199.5 ms from when an attack is launched in the large-scale topology. In addition, the mitigation approach effectively reduces the PIT utilization and increases the average consumer satisfaction rate.

Named Data Networking (NDN) has emerged as a promising information-centric networking paradigm that addresses the limitations of the traditional IP-based Internet architecture. The core principle of NDN relies on content naming instead of host addressing, to provide efficient, secure, and scalable content delivery. Routing is a critical component of NDN and is responsible for discovering and maintaining optimal paths to named content. This paper presents a comprehensive review of routing techniques in NDN, focusing on the design principles, algorithms, and performance metrics, especially in wired network architecture. We first summarize the NDN architecture and discuss its key components. We then delve into the fundamental routing concepts in NDN and categorize and examine various routing techniques, including link state, distance vector, and centralized approaches based on Software Defined Network. We also summarize the relevant research efforts proposed to address NDN routing challenges by focusing more on wired network architecture. Finally, we identify open research issues and future directions in NDN routing, emphasizing the need for scalable, efficient, and secure routing techniques that can fulfill the growing demands of the modern Internet. In conclusion, this review serves as a valuable reference for researchers and practitioners in NDN, offering a comprehensive understanding of the current state-of-the-art routing techniques, limitations, and potential future advancements.

Radient: Scalable, memory efficient name lookup algorithm for named data networking

As a key component in implementing Named Data Networking (NDN), Pending Interest Table (PIT) requires an efficient exact-matching algorithm for a scalable and fast PIT lookup. A Bloom filter (BF) is a memory-efficient data structure for performing exact matching operations. In this paper, three different BF-based PIT architectures are proposed: PIT using functional Bloom filters (FBF-PIT), PIT using counting Bloom filters with return values (rCBF-PIT), and a refined rCBF-PIT with signatures (R-rCBF-PIT). The proposed BF-based PITs incrementally allocate a new BF for storing multiple incoming faces of Interest packets with the same content name. For a Data packet lookup, the proposed PIT architectures simultaneously access every BF structure to find matching faces and delete the faces (i.e., matching Interest packet information). The functional Bloom filter (FBF) used in an FBF-PIT is a key-value data structure that stores values only without keys. However, because the number of non-reusable conflict cells in the FBF increases as the number of stored packets increases in the FBF-PIT, the indeterminable rate increases. To decrease the indeterminable rate, we propose the rCBF-PIT, which uses counting Bloom filters with return values (rCBFs), allowing reusable conflict cells. False positives for Interest packets lead to incorrect deletions that can cause false negatives for incoming Data packets. Because most of the false positives occur in the first BF structure, we finally propose the R-rCBF-PIT, in which the first rCBF is replaced with an rCBF with a signature field. The proposed PITs also provide an aging mechanism using a valid bit and a hit bit for entry expiration. Simulation results show that rCBF-PIT and R-rCBF-PIT both reduce the indeterminable rate by more than 81% compared with FBF-PIT. The results also show that R-rCBF-PIT resolves false negatives caused by incorrect deletions by including the signature fields in the first rCBF.

International audience

To viably identify interest flooding assault (IFA) in Named Data Networking (NDN), this paper proposes a discovery technique for interest flooding assault dependent on chi-square test and similitude test. Initially, it decides the identification window size dependent on the dissemination of data name prefixes (that is data entropy) in the current organization traffic. The assailants might annex subjective irregular suffix to a certain prefix in the organization traffic, and afterward send an enormous number of interest parcels that can't get the reaction. Focused on at this issue, the affectability of chi-square test is utilized to distinguish the difference in pre-fix of interest parcels. Premium parcels started by IFA assailants are generally joined to a genuine prefix, yet with an arbitrarily created suffix appended. Considering of this issue, the similitude of interest parcel prefixes is additionally identified. At long last, the location consequences of the two viewpoints are consolidated to hinder mine if interest flooding assault has happened. Moreover, as indicated by the symmetric steering normal for Pending Interest Table (PIT), likewise the fashioned interest parcel will be sent back to the aggressor, and afterward confine the corresponding port of the assailant, to viably smother the IFA assault. The test results show that the proposed technique cannot just identify IFA in NDN toward the start of the assault, yet in addition is more precise and powerful than different strategies.

Named Data Networking (NDN) is considered as a prominent architecture towards future Wireless Local Area Networks (WLAN), and multicast plays an important role in data delivery such as media streaming, multipoint videoconferencing, etc. However, to achieve high-efficiency multicast in NDN WLAN is challenging for two significant reasons. First, without feedback mechanism in IEEE 802.11 standards, to guarantee reliability, the current multicast scheme transmits the multicast data with the basic rate (e.g., 1 Mbps for IEEE 802.11b), which inevitably increases the transmission delay for high-speed consumers. Second, as a NDN multicast group is constituted by consumers who are requesting the same content, multicast groups are easy to form and evolve rapidly, where a data rate adaptation scheme is requisite to accommodate differential multicast groups. In this paper, we propose a multi-stage multicast rate adaptation scheme for NDN WLAN, named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NDN-MMRA</i> , to minimize the total transmission time with reliability guarantee for multicast group members. In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NDN-MMRA</i> , by checking the Pending Interest Table (PIT) status information, the number of consumers in each multicast group as well as their receiving capabilities are known ahead; with the available data rates in a specific 802.11 standard, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NDN-MMRA</i> determines: 1) how many transmission stages are required; and 2) in each stage, which data rate should be adopted. The merit is that with multi-stage transmissions, the data rate can be adapted in descending order to accommodate high-speed consumers with delay minimized, and low-speed consumers with reliability guaranteed. We implement <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NDN-MMRA</i> in NS-3 by adopting the ndnSIM module, and conduct extensive experiments to demonstrate its efficacy under different IEEE 802.11 standards and various underlying WLAN topologies.

ABSTRACTSoftware‐defined networking (SDN), a cornerstone of future‐generation networks, is adopted in Named Data Networks (NDN) for large‐scale deployment. The forwarding strategies proposed for SDN‐based NDN primarily use the centralized controller to optimize Interest forwarding and Data delivery. The nodes direct the Interests to the controller to discover the content source(s) and suppress the suboptimal responses. To support such content discovery and delivery, the controller experiences frequent path calculation and trades excessive control messages to install the paths in the nodes due to rapid cache admission and replacement. Besides, the typical NDN forwarding solutions are not viable to realize or need considerable modifications in SDN‐based NDN. To that end, the proposed strategy optimizes Interest forwarding and Data delivery using a Single‐State Q‐learning‐based technique, namely, SDN‐Q. In SDN‐Q, each content source learns to suppress the suboptimal responses, with the learning task offloaded to the controller. The controller communicates the learning decision to the nodes. Each node only retains the action (decision) to entertain an incoming Interest. Once an Interest hits, the source either replies with the Data or remains silent and sends the Interest's information (meta‐data) to the controller for the learning task. Thus, SDN‐Q enables the NDN nodes to remain light‐loaded. Each node can instantly answer an Interest request without redirecting it to the controller. Additionally, we optimize Interest forwarding using a hop‐based scoped‐flooding approach. The proof‐of‐concept implementation in software (simulation) reveals that the proposed system outperforms the competing strategies by reducing the traffic load, latency, and control messages in SDN‐based NDN (at most by 40%, 7%, and four (4) times respectively), without negotiating packet delivery ratio.

The proposed Internet paradigm The Flying Ad Hoc Network (FANET), Named Data Network (NDN), and Software Defined Network (SDN) have attracted the interest of the scientific community. The TCP/IP protocol is the present Internet standard, while NDN is the future internet architecture that builds on it. Data availability is improved via NDN, which substitutes named data for the nodes' addresses. SDN is a good option for communicating effectively, utilizing resources effectively, and supporting developing technologies. The SDN has attracted interest because of its high-level programmability and flexibility. Numerous applications in the military, business, and civil sectors make extensive use of FANE T. The broadcast characteristic of NDN causes an issue known as a broadcast storm in dense FANET environments. The issue is caused by duplicate packets, which raises the overall amount of traffic and retransmissions. FANET has a problem with the timely and quick transmission of essential packets. In this paper, we suggested a new scheme named "Novel Adaptive Broadcast Storm Avoidance (NABA)" for SDN and NDN-enabled FANET, which uses a controller to lessen the broadcast issue. Our scheme made use of the SDN controller's effective flow management to regulate the broadcast storm and facilitate packet transfers. Additionally, we divided up the packet into categories based on priority. The priority of the packet is determined by the naming criterion. In terms of the overall number of Interests and content retrieval time, the findings show that NAB A performs better than native NDN floods.

Even though the most recent proposal to change the architecture of internet from network-based to data-based, called Named Data Networking (NDN) is rapidly evolving, mobility support is still an open issue. Mobile IP-enabled devices are currently in the billions and increasing; as a consequence, mobility represents a challenge to overcome for the success of NDN. In this paper, we target NDN on a widespread mobile content delivery problem: highway-restricted path mobility. We propose a solution on the infrastructure side using selective interest forwarding to neighbouring nodes, and furthermore, we show that this strategy reduces the delay and increases the hit rate compared to the standard NDN approach.

Using Interests (requests that elicit content) and maintaining per-Interest forwarding state in Pending Interest Tables (PIT) are integral to the design of the Named Data Networking (NDN) and Content-Centric Networking (CCNx) architectures. However, using PITs makes the network vulnerable to Interest-flooding attacks, and PITs can become very large. It is shown that in-network caching eliminates the need for Interest aggregation and obviates the use of PITs. A new approach to content-centric networking (CCN-GRAM) is introduced that provides all the benefits of NDN and CCNx, eliminates the use of PITs by means of anonymous datagrams, and is immune to Interest-flooding attacks. Routers maintain routes to the anonymous origins of Interests using an on-demand routing approach in the data plane that can also be used to provide native support for multicasting in the dat a plane. Simulation experiments show that the number of forwarding entries required in CCN-GRAM is orders of magnitude smaller than the number of PIT entries.

Detecting interest flooding attacks in NDN: A probability-based event-driven approach