Raman Singh

University of the West of Scotland | UWS · School of Computing

In the modern world of technology, location-based services are widely used in various applications, such as smartphones, smart vehicles, and smart cities. When requesting a point of interest from location-based or third-party services, these services require users to enable location services. The primary purpose of this study is to identify researc...

Given the rise in demand for cloud computing in the modern era, the effectiveness of resource utilization is eminent to decrease energy footprint and achieve economic services. With the emerging machine learning and artificial intelligence techniques to model and predict, it is essential to explore a principal method that provides the best solution...

The emergence of Industry 5.0 has highlighted the significance of information usage, processing, and data analysis when maintaining physical assets. This has enabled the creation of the Digital Twin (DT). Information about an asset is generated and consumed during its entire life cycle. The main goal of DT is to connect and represent physical asset...

One of the major factors creating advance prospects in the aerial imaging classification solutions market is the recently published drone policies by Government of India and availability of artificial intelligence-based technologies. The images in low-altitude aerial datasets are inherently different from standard datasets in terms of the appearanc...

Location privacy (LP) plays an important role in location-based services (LBS) offered by different service providers. Many applications request users to enable the location services in their smart devices and access geodata from their smartphones which becomes a security threat. To enhance the individual’s privacy while accessing LBS systems, this...

Citation: Singh, R.; Pervez, Z.; Tewari, H. Blockchain-Enabled NextGen Service Architecture for Mobile Internet Offload. Future Internet 2023, 15, 173. https:// Abstract: The amalgamation of heterogeneous generations of mobile cellular networks around the globe has resulted in diverse data speed experiences for end users. At present, there are no d...

The utilization of Internet of Things (IoT) devices in various smart city and industrial applications is growing rapidly. Within a trusted authority (TA), such as an industry or smart city, all IoT devices are closely monitored in a controlled infrastructure. However, in cases where an IoT device from one TA needs to communicate with another IoT de...

Advancement in the Internet of Things (IoT) and cloud computing has escalated the number of connected edge devices in a smart city environment. Having billions more devices has contributed to security concerns, and an attack-proof authentication mechanism is the need of the hour to sustain the IoT environment. Securing all devices could be a huge t...

In this paper, we have addressed the problem of data and location privacy in smart devices over vehicular cloud computing (VCC). We proposed a framework to identify and register the smart GPS devices over VCC service and allow the users to monitor the smart GPS device in real-time. The proposed framework divides into three parts: First, data anonym...

Nowadays, Cloud services are gaining importance among users due to their cost-effectiveness and highly scalable resources. To meet the user’s demands, several data centres are built across the globe, which has severe environmental as well as economical concerns. Energy consumption is one of the most significant issue faced by cloud service provider...

This paper compares the classification performance of machine learning classifiers vs. deep learning-based handcrafted models and various pretrained deep networks. The proposed study performs a comprehensive analysis of object classification techniques implemented on low-altitude UAV datasets using various machine and deep learning models. Multiple...

The Internet of Things (IoT) introduces an active connection between smart devices for revolutionizing our modern lives in this world. But, IoT devices often exhibit several security issues, so transmission between the nodes should be protected using cryptographic approaches. However, the complexity of conventional cryptographic approaches is very...

As the number and characteristics of smart devices change, the concept of the Internet of Things (IoT) emerges. The IoT provides the connected devices with a variety of resources that enable effective communication. At this point, several security issues arise to get the sensitive information behind every communication in the IoT. To provide users...

The understanding and implementation of object detection and classification algorithms help in deploying diverse applications of UAVs. There is a need for a simulated UAV dataset to incorporate a pipeline for various algorithms. To reduce human efforts, multiple simulators have been utilized to mimic the real-time behavior of drones. Our work inspi...

Great extent of modernization in intelligent device automation and wireless sensor network have encouraged the augmentation of IoTs to interconnect millions of actual devices to the Internet with the help of sensors, actuators and communication technologies. IoT devices with the potential of pervasive sensing and quantifying ability, it becomes an...

In this era of ubiquitous social media and messaging applications, users are becoming increasingly aware of the data privacy issues associated with such apps. Major messaging applications are moving towards end-to-end encryption (E2EE) to give their users the privacy they are demanding. However the current security mechanisms employed by different...

The use of low-cost sensors in IoT over high-cost devices has been considered less expensive. However, these low-cost sensors have their own limitations such as the accuracy, quality, and reliability of the data collected. Fog computing offers solutions to those limitations; nevertheless, owning to its intrinsic distributed architecture, it faces c...

The paper can be found at my profile page: https://research-portal.uws.ac.uk/en/publications/comparative-analysis-of-simulators-for-iot-applications-in-fogclo

The low-altitude aerial objects are hard to detect by existing deep learning-based object detectors because of the scale variance, small size, and occlusion-related problems. Deep learning-based detectors do not consider contextual information about the scale information of small-sized objects in low-altitude aerial images. This paper proposes a ne...

This paper proposes a high-performance framework for accurate multi-stage object detection in low-altitude based UAV images. The proposed system employs a cascade style architecture with increasing thresholds for achieving accurate detection. The framework makes use of highly efficient Feature Pyramid Networks (FPNs) to detect objects of small size...

With the increasing prevalence of different mobile apps, many applications require users to enable the location service on their devices. For example, the geofence service can be defined as establishing virtual geographical boundaries. Enabling this service triggers entering and exiting the boundary area and notifies the users and trusted third par...

The leakage of sensitive data of users and global positioning system location trajectories from different cloud computation sources have increased in daily lives. This critical problem can influence users' lives because attackers try to misuse the leaked information. In this study, we addressed the critical problem pertaining to the privacy of pers...

In general, the Internet of Things (IoT) is used for many applications and plays an essential role in the digital communications of smart city applications. However, securing the sensor-based IoT communication is difficult because it is highly vulnerable to malicious actions like Denial of Service (DOS), ransomware, and node impersonation. In the p...

The Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not poss...

In the popular field of cloud computing, millions of job requests arrive at the data centre for execution. The job of the data centre is to optimally allocate virtual machines (VMs) to these job requests in order to use resources efficiently. In the future smart cities, huge amount of job requests and data will be generated by the Internet of Thing...

The amalgamation of different generations of mobile cellular networks around the globe has resulted in diverse data speed experiences for end users. At present there are no defined mechanisms in place for a subscriber of one mobile network operator (MNO) to use the services of a WiFi provider. Cellular and Data Service providers also have no standa...

In the era of social media and messaging applications, people are becoming increasingly aware of data privacy issues associated with such apps. Major messaging applications are moving towards end-to-end encryption (E2EE) to give their users the privacy they are demanding. However the current security mechanisms employed by different service provide...

Over the past decade, we have witnessed the Internet becoming increasingly centralized in the hands of a small number of giant technology firms, that control many of the most popular applications and the content they host on their platforms. In addition, in the majority of instances today, access to the Internet is usually provided through local in...

Deep learning-based object detection solutions emerged from computer vision has captivated full attention in recent years. The growing UAV market trends and interest in potential applications such as surveillance, visual navigation, object detection, and sensors-based obstacle avoidance planning have been holding good promises in the area of deep l...

Slide Presentation

Over the past decade, we have witnessed the Internet becoming increasingly centralized in the hands of a small number of giant technology firms, that control many of the most popular applications and the content they host on their platforms. In addition, in the majority of instances today, access to the Internet is usually provided through local in...

Dear Professor, Greetings of the day!!! Its my pleasure to inform you that we are serving as the Guest Editors ☺️ for Computers and Electrical Engineering journal on a special issue "Load Balancing of Sensory Data for IoT Deep Learning Applications with Edge/Fog Computing". This is a Q1 journal with Impact Factor of 2.663 and CiteScore of 5.3 ind...

The Internet of Things (IoT) represents the physical world of devices and objects connected over the network using wireless sensors. This chapter gives detailed study about the different applications of IoT with the integration of WSN (wireless sensor networks) with Internet connectivity. This allows applications to communicate among themselves and...

Unmanned Aerial Vehicle (UAV) has received wide interest in recent years because of their promising potentials for several applications that include border surveillance, intrusion, detection, emergent item delivery, wildlife monitoring, rescue operations etc. The growing number of entrances of drones into airspace has emerged a significant interest...

Security is the major concern in the world of Internet. Traditionally, encryption, firewall, and other security countermeasures are used to secure the data. However, in the modern era of technology, the Intrusion Detection System (IDS) plays a major role in the field of security to detect the attack type. IDS are tuned in such a way that it learns...

This research pertains to classification of the heart sound using digital Phonocardiogram (PCG) signals targeted to screen for heart ailments. In this study, an existing variant of the decision tree, i.e. XgBoost has been used with unsegmented heart sound signal. The dataset provided by PhysioNet Computing in Cardiology (CinC) Challenge 2016 has be...

A dedicated key server cannot be instituted to manage keys for MANETs since they are dynamic and unstable. The Lagrange's polynomial and curve fitting are being used to implement hierarchical key management for Mobile Ad hoc Networks (MANETs). The polynomial interpolation by Lagrange and curve fitting requires high computational efforts for higher...

Purpose The paper addresses various cyber threats and their effects on the internet. A review of the literature on intrusion detection systems (IDSs) as a means of mitigating internet attacks is presented, and gaps in the research are identified. The purpose of this paper is to identify the limitations of the current research and presents future di...

Intrusion Detection System (IDS) can be used to detect malware by its network activities or behavioral profiles. Common challenges for IDS are large amount of data to process, low detection rate and high rate of false alarms. Online Sequential Extreme Learning Machine (OS-ELM) based IDS with network traffic profiling is tested on Panjab University...

Anomaly based Intrusion Detection Systems (IDS) learn normal and anomalous behavior by analyzing network traffic in various benchmark datasets. Common challenges for IDSs are large amounts of data to process, low detection rates and high rates of false alarms. In this paper, a technique based on the Online Sequential Extreme Learning Machine (OS-EL...

The network traffic dataset is a crucial part of anomaly based intrusion detection systems (IDSs). These IDSs train themselves to learn normal and anomalous activities. Properly labeled dataset is used for the training purpose. For the activities based IDSs, proper network traffic activity labeled dataset is the first requirement, however non-avail...

Time taken by Intrusion Detection System (IDS) in order to detect malwares is very crucial factor. Network traffic dataset have many features and all may not contribute in detection of threats. Rejecting irrelevant features may increase performance of IDS by reducing computational time. In this paper, feature selection techniques based on Gain rati...

In sampling of huge network traffic dataset, some packets are chosen out of total packets. Leftover packets may have effect on statistical characteristics of the data. In this paper effect of sampling on statistical characteristics is discussed. A well-known benchmarked NSL KDD network traffic dataset is used. Three sampling techniques namely - ran...

Intrusion detection systems (IDS) have to process millions of packets with many features, which delay the detection of anomalies. Sampling and feature selection may be used to reduce computation time and hence minimizing intrusion detection time. This paper aims to suggest some feature selection algorithm on the basis of The Technique for Order of...

Network traffic data is huge, varying and imbalanced because various classes are not equally distributed. Machine learning (ML) algorithms for traffic analysis uses the samples from this data to recommend the actions to be taken by the network administrators as well as training. Due to imbalances in dataset, it is difficult to train machine learnin...

Network traffic data is huge, varying and imbalanced because various classes are not equally distributed. Machine learning (ML) algorithms for traffic analysis uses the samples from this data to recommend the actions to be taken by the network administrators. Due to imbalances in dataset, machine learning algorithms may give biased or false results...

Monitoring of network traffic flow is very important for network management. Classifying network traffic can detect hidden patterns of possible threat. Classification is a tool of network administrator to find out hidden threats to network. In this paper we have analysed network traffic which is captured on Panjab University campus network. This tr...

Distributed denial-of-service (DDoS) attacks are a major threat to the Internet. A lot of research is going on to detect, prevent and trace back DDoS attacks. Most of researchers are busy in post attack forensics which comes after the attack has been occurred but nobody is talking about how to design a system which can tolerate such attacks. In thi...

Bandwidth is very crucial and limited resource available, so it should be properly utilized. Network congestion occurs when a link or node is carrying large amount of data in case of flood attack and quality of service deteriorates. Effects of flood attack include queuing delay, packet loss or the blocking of new connections. As a consequence incre...

Monitoring of network traffic flow is very important for network management. Classifying network traffic can detect hidden patterns of possible threat. Classification is a tool of network administrator to find out hidden threats to network. In this paper we have analysed network traffic which is captured on Panjab University campus network. This tr...

Soft computing techniques are widely used in malware detection in these days. These techniques have the ability of learning from the past incidences and can categories normal and abnormal behaviour. In this paper we have reviewed various soft computing techniques. A review of application of these soft-computing techniques in malware detection has a...