Edge Artificial Intelligence (Edge AI) is driving the widespread deployment of neural network models on resource-constrained microcontroller units (MCUs), enabling real-time, on-device data processing. This approach significantly reduces cloud dependency, making it ideal for applications in industrial automation and IoT. However, the deployment of deep learning models on such constrained devices poses significant challenges due to limitations in memory, computational power, and energy capacity. This paper presents a real-time object detection system optimized for energy efficiency and scalability, which integrates well-established model compression techniques, such as quantization, with a low-cost MCU-based platform. The system leverages MobileNetV2, a lightweight neural network, quantized to achieve the best trade-offs between accuracy and resource consumption. The proposed solution integrates a camera and Wi-Fi module for capturing and transmitting image data, utilizing dual-mode TCP/UDP communication to balance reliability and low-latency transmission for IoT applications. We present a comprehensive system-level analysis, exploring the trade-offs between latency, memory, energy consumption, and model size. The Visual Wake Words (VWW) dataset is used for this research, which demonstrates the practical performance and scalability of the system for real-time applications in smart devices, industrial monitoring, and environmental sensing. This work emphasizes the integration of TinyML models with constrained hardware and offers a foundation for scalable, autonomous, energy-efficient Edge AI solutions. Quantitatively, 8-bit post-training quantization achieved 3– storage reduction, yielding deployable flash footprints of 286-536 KB within a 1 MB flash / 256 KB SRAM budget, on-device inference latency ranged from 3.47 to 14.98 ms per frame with energy per inference of 10.6–22.1 J, while quantized MobileNet variants maintained accuracy. In wireless reporting, UDP reduced one-way latency relative to TCP, whereas TCP provided higher delivery reliability, underscoring application-dependent protocol trade-offs for real-time embedded deployments.

With the rapid development of the Internet of Things (IoT), modern Maritime Transportation Systems (MTS) have played a crucial role in the transport industry. The various potential privacy and security concerns (such as vessels’ location tracking, message tampering, unauthorized access to data, etc.) have increased substantially in IoT-enabled MTS. Considering the above issues, we propose a secure, robust, and efficient authentication scheme for MTS based on Elliptic-Curve Cryptography (ECC) and Hash-based Message Authentication Code (HMAC) called PSAS-MTS. The proposed PSAS-MTS scheme not only monitors the vessel’s condition but also ensures protection against collisions in route management and provides safety to the vessel’s passengers. The scheme uses simple XOR, a cryptographic one-way hash, an ECC cryptosystem, and HMAC to achieve a high level of security in MTS. The formal security analysis is carried out using a well-known Real-Or-Random (ROR) model, which ensures the security harness features. A rigorous informal security analysis is also done, which ensures various privacy and security features such as mutual authentication, anonymity, forward and backward secrecy, etc. The proposed PSAS-MTS scheme resists various possible well-known active and passive security attacks. The performance analysis shows that the proposed PSAS-MTS scheme is more efficient in terms of computation and communication overheads when compared to other competitive schemes.

One of the significant services provided by IoV in Smart cities is vehicular navigation. Drivers often find it difficult and time-consuming to complete their trip in a crowded city without real-time knowledge about the traffic and road conditions. So, a proper routing mechanism can help drivers reach their destination in minimum time and with less fuel consumption. However, it has been found that such protocols often face security challenges. In this paper, we have proposed an authenticated navigation scheme with the help of pseudonym-based asymmetric-key cryptography that discovers and secures the route to the destination in real time. The architecture embodies a geolocation provider (GLP) to get the possible static routes to a particular destination. Further, it uses the message-forwarding capability of RSUs to develop a dynamic route, after receiving feedback from the respective RSUs about the traffic conditions. While doing so, this protocol ensures proper message integrity, anonymity, unlinkability and robust protection from important security threats. Our approach ensures minimal end-to-end delay and efficient real-time route finding from a source to a destination with no extra overhead on the vehicles. We have simulated our authentication protocol using the Scyther simulator and found it safe from various adversarial attacks.

In the field of network security and management, accurately identifying and managing encrypted traffic is essential for mitigating potential attacks and optimizing resource usage. However, conventional methods often underperform in adapting to new traffic classes, require more manual intervention, time-consuming, and resource-intensive. These limitations reduce system performance and increase vulnerability issues. Conventional models also face scalability issues and are prone to catastrophic forgetting, where previously learned traffic patterns are lost as new ones are introduced, leading to reduced classification accuracy over time. To address these challenges, we propose a novel method: Network Traffic Classification using Class-Incremental Learning (NTC-CIL). NTC-CIL combines a random forest classifier with the Learning without Forgetting (LwF) method, an incremental learning method based on knowledge distillation. This approach enables the model to retain previously learned patterns while incorporating new traffic classes, including encrypted and evolving types. As a result, NTC-CIL can continuously adapt to unfamiliar network traffic without retraining from scratch. Experimental evaluations demonstrate that NTC-CIL outperforms existing techniques by achieving an accuracy of 97%. This marks a significant advancement for network security, offering a scalable and adaptive solution capable of detecting new threats in dynamic traffic environments.

The integration of the Internet of Things (IoT) with fog computing has significantly enhanced the capabilities of IoT applications by extending their reach and reducing latency. Fog nodes, being transient and authorized service providers, necessitate reauthentication of IoT end devices when contact is lost, requiring the device to connect to a new fog node. In this research, we propose an innovative security protocol designed to ensure seamless failover among fog nodes. This protocol facilitates quick and easy failover authentication among IoT devices and fognodes using the key agreement among fog nodes. LEFAM overcomes the requirement for the end device to communicate with the fog node atleast once to get the security token in order to execute failover authentication. This work proposes efficient, scalable and robust scheme required for fog-IoT environment to provide solution in case of failure of the primary fognodes. Our approach effectively mitigates various security threats, as demonstrated through informal analysis. Furthermore, simulation results obtained using the Scyther tool confirm the robustness of our protocol in terms of security. A formal analysis conducted using the RoR model further substantiates the reliability of our protocol. Notably, our protocol involves fewer message exchanges, indicating a lower communication overhead compared to other existing schemes. The key finding indicates that the LEFAM scheme offers an average improvement of ≈ 76% and 1188 bits for computation and communication overheads, respectively. Overall, our protocol not only enhances security but also offers superior performance relative to existing protocols.

The real challenge in Wireless Body Area Network (WBAN) lies in ensuring the security of health-related sensitive data and diagnostic information, preventing unauthorized access by malicious users. Given that information exchange takes place between the WBAN client and the Application Provider (AP), there is a critical need for thorough attention to mutual authentication and secure key generation. Many of the available research works lack the addressing of essential security features such as strong anonymity, key confidentiality, and key-escrow resilience. The primary focus of this research work is to develop a certificateless anonymous mutual authentication scheme that will be computationally efficient and memory-optimized, while maintaining uncompromising security features. Our scheme excels over other schemes due to its utilization of a hybrid approach, which integrates cryptographic operations related to the Discrete Logarithm Problem (DLP), Elliptic Curve Discrete Logarithm Problem (ECDLP), and bi-linear pairings. This approach maintains strong security features and also enhances the performance of the system. The proposed scheme improves computational cost, storage cost, and communication cost by at least 15%, 41%, and 10%, respectively, compared to the best available schemes. We have also verified our protocol using formal and informal approaches. Formal logic analysis and simulation of our scheme ensure its potential to significantly enhance user privacy and strengthen mutual authentication in Smart healthcare systems.

The most crucial smart service suitable for any country is a smart and robust policing system. According to law, for any offense, cognizable or non-cognizable, an FIR has to be lodged with the police station for any further action, exceptional only in some cases. The ratio of cops to people has a sizable gap. The unavailability of police stations nearby, and political influence, among others, cause hindrances to the judicial system. Investigation case file tampering and bribery demands add to the problem list. These issues cause the basic system involved in this, is continuing in the interest of ‘Trust’. Our objective is to build a decentralized application/tool which can be used by the existing police system to deal with the problems aforesaid. Common people and police officers will be treated as equal part-takers in terms of the authority to add information to the blockchain. The FIR details are encrypted, and hash is stored in IPFS, but the catch here is the encryption will be done in a way that necessary details will be revealed for distinguishing complaint A from B, but the complainant or defendant identity is not revealed either to the police officials or to anybody having visibility in the blockchain before FIR lodging. Further, this research work helps to identify real users from spammers following an exhaustive verification check discussed further.

Tactile Internet, a fast and low-latency communication network, plays a crucial role in IoD applications for providing various features like precision control and realistic telepresence. The Internet of Drones (IoD) is a rapidly evolving concept that envisions a network of collaborating and communicating interconnected drones. Drones have diverse applications, including traffic monitoring, medicine, battlefield surveillance, logistics, and agriculture. However, the widespread deployment of drones raises significant security and privacy concerns. In this paper we have proposed secure data delivery authentication protocol for tactile Internet enabled IoD system (D3 APTS). Also, using blockchain along with IoD for storing data will provide additional characteristics like data immutability. To secure communication among user, ground station server, and drone D3APTS employs one-way hash function and ECC cryptosystem. It resists various attacks like impersonation attacks, capturing attacks, session-key disclosure attacks, especially desynchronisation attacks which is important in case of IoD scenario. D3APTS also provides anonymity and unlinkability features. It is formally verified using the scyther security tool and ROR model. The performance analysis and comparison shows that D3APTS is better in terms of computation, communication overheads, security and functionality features.

Advancements in technology and the adoption of innovative developments have significantly simplified our lives. One notable innovation in the networking domain is Software Defined Networking (SDN), which revolutionizes the network layer by enabling centralized network administration and re-programmability. SDN technology finds application in diverse fields such as Vehicular Ad-hoc Networks (VANETs), Wireless Sensor Networks (WSNs), Internet of Things (IoT) communications, and cloud-fog computing. The integration of SDN technology into VANET systems has notably improved network performance but has also raised security concerns. To tackle this issue, this paper focuses on devising an authentication mechanism to facilitate secure communication across various VANET levels by establishing a shared session key. Moreover, the research proposes a method to mitigate the challenge of single points of failure, a typically difficult issue to address. To ensure the security of all confidential information during protocol execution, simulations are conducted using the Scyther tool. Additionally, an informal security analysis is performed, demonstrating the robustness of the proposed protocol. The proposed protocol also performs outstanding in terms of performance results

The growing reliance on wireless communication in Internet-of-Things (IoT) devices highlights the critical need for secure and efficient communication protocols, especially in environments vulnerable to cyber threats. Existing IoT protocols often lack sufficient security, creating a need for robust authentication and key exchange mechanisms that can resist attacks while maintaining low computational overhead. In this paper, we propose a fog-enabled network architecture integrated with IoT devices (Intra and Inter IoT device) and develop the DEAC-IoT scheme using Elliptic Curve Cryptography (ECC) for secure authentication and key agreement. Our protocol is designed to protect device-to-device communication from security threats in resource-constrained IoT environments. We validate DEAC-IoT's security through both informal analysis and formal verification using the Real-Or-Random (RoR) model, demonstrating its resistance to major attacks. Simulation via the Scyther tool confirms that private parameters remain secure throughout the protocol's execution. For practical feasibility, we implement DEAC-IoT on a Field Programmable Gate Array (FPGA) and conduct performance evaluations. The results show that our protocol surpasses existing protocols in both computational and communication efficiency, making it highly suitable for real-world IoT applications.

Drones also called Unmanned Aerial Vehicles (UAVs) have become more prominent in several applications such as package delivery, real-time object detection, tracking, traffic monitoring, security surveillance systems, and many others. As a key member of IoT, the group of Radio Frequency IDentification (RFID) technologies is referred to as Automatic Identification and Data Capturing (AIDC). In particular, RFID technology is becoming a contactless and wireless technique used to automatically identify and track the tagged objects via radio frequency signals. It also has drawn a lot of attention among researchers, scientists, industries, and practitioners due to its broad range of real-world applications in various fields. However, RFID systems face two key concerns related to security and privacy, where an adversary performs eavesdropping, tampering, modification, and even interception of the secret information of the RFID tags, which may cause forgery and privacy problems. In contrast to security and privacy, RFID tags have very limited computational power capability. To deal with these issues, this paper puts forward an RFID-based Lightweight and Provably Secure Authentication Protocol (LPSAP) for Unmanned Aerial Vehicle Systems. The proposed protocol uses secure Physically Unclonable Functions (PUFs), Elliptic-Curve Cryptography (ECC), secure one-way hash, bitwise XOR, and concatenation operations. We use Ouafi and Phan's formal security model for analyzing security and privacy features such as traceability and mutual authentication. The rigorous informal analysis is carried out which ensures that our proposed protocol achieves various security and privacy features as well as resists various known security attacks. The performance analysis demonstrates that our proposed protocol outperforms other existing protocols. In addition, Scyther and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool simulation results demonstrates that there is no security attack possible within bounds. Therefore, our proposed LPSAP protocol achieves an acceptable high level of security with the least computational, communication, and storage costs on passive RFID tags.

The Internet of Vehicles (IoV) is a fast developing field that seeks to use cutting-edge technologies to enhance the sustainability, efficiency, and safety of transportation networks. The IoV can gain greatly from integrating blockchain in terms of security, trust, decentralization, smart contracts, and data management. This paper presents the weakness of a blockchain based lightweight authentication and key agreement scheme for internet of vehicles(BLAIV) proposed by Zheng et al. [1]. By performing thorough security analysis we have observed that the BLAIV scheme is vulnerable to various security attacks. The main cause for the security attacks is the BLAIV scheme stores the security parameters in the Onboard unit(OBU) of vehicle, due to which the BLAIV scheme is vulnerable to various attacks like vehicle or OBU capture attacks, session key computation attacks, and impersonation attacks. The paper also suggests possible changes to improve the BLAIV scheme.

Very recently, ESEAP mutual authentication protocol was designed to avoid the drawbacks of Wang et al. protocol and highlights that the protocol is protecting all kind of security threats using informal analysis. This work investigates the ESEAP protocol in security point of view and notices that the scheme is not fully protected against stolen verifier attack and does not provide user anonymity. Furthermore, the same protocol has user identity issues, i.e., the server cannot figure out the user identity during the authentication phase. Later we discuss the inconsistencies in the security analysis of ESEAP presented by RESEAP.

Internet of Medical Things (IoMT) has facilitated the healthcare industry by providing ease of communication among doctors and patients living in remote areas for accomplishing diagnosis, real-time monitoring, and treatment procedure efficiently. The patient's health-related data must be secured from various attacks of adversary since the data is sensitive and highly prone to attacks. This paper proposes an architecture that suits both localized and emergency scenarios. This architecture utilizes cloud server and edge computing technology. Provably secured lightweight authenticated key agreement protocol for modern health industry (PSLA2P) provides a lightweight authentication and key agreement protocol that can be deployed in the proposed network architecture. It protects the privacy of the patient's health-related data by providing anonymity and untraceability. Real-Or-Random (ROR) model is used for the formal analysis of PSLA2P. We have verified the security weaknesses of PSLA2P using the Scyther simulator. Moreover, the informal analysis ensures high-level mitigation against known possible attacks. PSLA2P achieves better performance in terms of computation and communication overhead.

According to state-of-the-art, several multiple base station-based authentication and key agreement protocols exist. Still, most of the protocols are computationally inefficient and suffer from several potential attacks. In this research work, we consider WSN architecture, where multiple base stations are located in a distributed way. After that, we proposed a blockchain-based authentication and key agreement protocol for establishing secure communication. This protocol utilizes a smart contract facility during the registration of the sensor node. Our work also stores records of the sensor node in blockchain network. Most importantly, we have verified the proposed protocol using FPGA implementation, which further confirms the correctness of the generated session keys. BSAPM is demonstrated in terms of security threats using the Scyther tool, and we have also shown formal security analysis using the Real-or-Random(ROR) model. The informal security analysis demonstrates the protection against security threats. BSAPM is better in terms of communication, computation overheads, and functionality features when compared to the related other competitive schemes.

In recent times, sensor node or smart camera can be embedded in the drones for the collection of important data with the help of Internet Technology. Several security threats/vulnerabilities may hamper the system while collecting data. Hence, strong protection against security attacks is essential in drone based data collection system. In this work, we have considered a drone based cloud enable architecture for collecting and sharing information. The aim of this paper is to design a lightweight security protocol which will provide secure communication and mutual authentication among the entities. The proposed protocol establishes temporary session key for each session in order to make the complete system security attacks free. We have simulated the proposed protocol for measuring security strength using Scyther simulation whose results show all the claimed parameters are private during protocol run. It also ensures the correctness of mutual authentication. The informal analysis confirms strong protection on all security threats related to proposed architecture. The performance analysis has also made which shows that the protocol is lightweight and achieves better efficiency in comparison with related published works.

Due to the massive increase in the Internet of Things (IoT) devices in various applications requiring an IoT–cloud environment, the network latency is high since all the IoT devices have to be authenticated by the cloud servers. Fog nodes can be used as an intercessor between IoT devices and the cloud, thereby reducing the latency of the network since the burden of authenticating the devices can be offloaded from the cloud. This paper proposes a lightweight secure mutual authentication scheme based on physically unclonable function that best addresses the current issues. Since the fog nodes are constrained, a lightweight authentication scheme will be the best solution. The formal security analysis of the scheme LASSI is done using real-or-random model. We used the widely accepted tool Scyther for formal security verification, and the results show that the scheme LASSI is resilient against various attacks. The performance evaluation of the scheme and the comparison with related other schemes show that our scheme is better in terms of communication and computation costs.