Vishal Sharma

Rushil Gupta, Vishal Sharma, Yash Jain et al.

We focus on the task of future frame prediction in video governed by underlying physical dynamics. We work with models which are object-centric, i.e., explicitly work with object representations, and propagate a loss in the latent space. Specifically, our research builds on recent work by Kipf et al. \cite{kipf&al20}, which predicts the next state via contrastive learning of object interactions in a latent space using a Graph Neural Network. We argue that injecting explicit inductive bias in the model, in form of general physical laws, can help not only make the model more interpretable, but also improve the overall prediction of model. As a natural by-product, our model can learn feature maps which closely resemble actual object positions in the image, without having any explicit supervision about the object positions at the training time. In comparison with earlier works \cite{jaques&al20}, which assume a complete knowledge of the dynamics governing the motion in the form of a physics engine, we rely only on the knowledge of general physical laws, such as, world consists of objects, which have position and velocity. We propose an additional decoder based loss in the pixel space, imposed in a curriculum manner, to further refine the latent space predictions. Experiments in multiple different settings demonstrate that while Kipf et al. model is effective at capturing object interactions, our model can be significantly more effective at localising objects, resulting in improved performance in 3 out of 4 domains that we experiment with. Additionally, our model can learn highly intrepretable feature maps, resembling actual object positions.

Gaurav Choudhary, Vishal Sharma

The 5G networks have the capability to provide high compatibility for the new applications, industries, and business models. These networks can tremendously improve the quality of life by enabling various use cases that require high data-rate, low latency, and continuous connectivity for applications pertaining to eHealth, automatic vehicles, smart cities, smart grid, and the Internet of Things (IoT). However, these applications need secure servicing as well as resource policing for effective network formations. There have been a lot of studies, which emphasized the security aspects of 5G networks while focusing only on the adaptability features of these networks. However, there is a gap in the literature which particularly needs to follow recent computing paradigms as alternative mechanisms for the enhancement of security. To cover this, a detailed description of the security for the 5G networks is presented in this article along with the discussions on the evolution of osmotic and catalytic computing-based security modules. The taxonomy on the basis of security requirements is presented, which also includes the comparison of the existing state-of-the-art solutions. This article also provides a security model, "CATMOSIS", which idealizes the incorporation of security features on the basis of catalytic and osmotic computing in the 5G networks. Finally, various security challenges and open issues are discussed to emphasize the works to follow in this direction of research.

Gaurav Choudhary, Jiyoon Kim, Vishal Sharma

The rapid involution of the mobile generation with incipient data networking capabilities and utilization has exponentially increased the data traffic volumes. Such traffic drains various key issues in 5G mobile backhaul networks. Security of mobile backhaul is of utmost importance; however, there are a limited number of articles, which have explored such a requirement. This paper discusses the potential design issues and key challenges of the secure 5G mobile backhaul architecture. The comparisons of the existing state-of-the-art solutions for secure mobile backhaul, together with their major contributions have been explored. Furthermore, the paper discussed various key issues related to Quality of Service (QoS), routing and scheduling, resource management, capacity enhancement, latency, security-management, and handovers using mechanisms like Software Defined Networking and millimeter Wave technologies. Moreover, the trails of research challenges and future directions are additionally presented.

Vishal Sharma

The blockchain is a safe, reliable and innovative mechanism for managing numerous vehicles seeking connectivity. However, following the principles of the blockchain, the number of transactions required to update ledgers pose serious issues for vehicles as these may consume the maximum available energy. To resolve this, an efficient model is presented in this letter which is capable of handling the energy demands of the blockchain-enabled Internet of Vehicles (IoV) by optimally controlling the number of transactions through distributed clustering. Numerical results suggest that the proposed approach is 40.16% better in terms of energy conservation and 82.06% better in terms of the number of transactions required to share the entire blockchain-data compared with the traditional blockchain.

Gaurav Choudhary, Vishal Sharma, Ilsun You et al.

Unmanned Aerial Vehicles (UAV)-based civilian or military applications become more critical to serving civilian and/or military missions. The significantly increased attention on UAV applications also has led to security concerns particularly in the context of networked UAVs. Networked UAVs are vulnerable to malicious attacks over open-air radio space and accordingly, intrusion detection systems (IDSs) have been naturally derived to deal with the vulnerabilities and/or attacks. In this paper, we briefly survey the state-of-the-art IDS mechanisms that deal with vulnerabilities and attacks under networked UAV environments. In particular, we classify the existing IDS mechanisms according to information gathering sources, deployment strategies, detection methods, detection states, IDS acknowledgment, and intrusion types. We conclude this paper with research challenges, insights, and future research directions to propose a networked UAV-IDS system which meets required standards of effectiveness and efficiency in terms of the goals of both security and performance.

Takshi Gupta, Gaurav Choudhary, Vishal Sharma

Pervasive Online Social Networks (POSNs) are the extensions of Online Social Networks (OSNs) which facilitate connectivity irrespective of the domain and properties of users. POSNs have been accumulated with the convergence of a plethora of social networking platforms with a motivation of bridging their gap. Over the last decade, OSNs have visually perceived an altogether tremendous amount of advancement in terms of the number of users as well as technology enablers. A single OSN is the property of an organization, which ascertains smooth functioning of its accommodations for providing a quality experience to their users. However, with POSNs, multiple OSNs have coalesced through communities, circles, or only properties, which make service-provisioning tedious and arduous to sustain. Especially, challenges become rigorous when the focus is on the security perspective of cross-platform OSNs, which are an integral part of POSNs. Thus, it is of utmost paramountcy to highlight such a requirement and understand the current situation while discussing the available state-of-the-art. With the modernization of OSNs and convergence towards POSNs, it is compulsory to understand the impact and reach of current solutions for enhancing the security of users as well as associated services. This survey understands this requisite and fixates on different sets of studies presented over the last few years and surveys them for their applicability to POSNs...

Vishal Sharma, Jiyoon Kim, Soonhyun Kwon et al.

Internet of Things (IoT) aims at providing connectivity between every computing entity. However, this facilitation is also leading to more cyber threats which may exploit the presence of a vulnerability of a period of time. One such vulnerability is the zero-day threat that may lead to zero-day attacks which are detrimental to an enterprise as well as the network security. In this article, a study is presented on the zero-day threats for IoT networks and a context graph-based framework is presented to provide a strategy for mitigating these attacks. The proposed approach uses a distributed diagnosis system for classifying the context at the central service provider as well as at the local user site. Once a potential zero-day attack is identified, a critical data sharing protocol is used to transmit alert messages and reestablish the trust between the network entities and the IoT devices. The results show that the distributed approach is capable of mitigating the zero-day threats efficiently with 33% and 21% improvements in terms of cost of operation and communication overheads, respectively, in comparison with the centralized diagnosis system.