ASHISH SAINI
@quantumeducation.in
Assistant Professor
Quantum University, Roorkee
EDUCATION
Ph.D, MCA, B.Sc.
RESEARCH INTERESTS
Software Product Line, Cloud Computing, Artificial Intelligence, Internet of Things, Machine Learning
Scopus Publications
Scopus Publications
Amit Kumar, Sanjeev Kumar, Vivek Kumar, Amrita Kumari, Ashish Saini, and Sarthak Gupta
IEEE
The Internet of Things is getting connected with the edge computing network day by day. These devices generate large amounts of confidential data that is stored and processed on edge computing. There is a need to protect such data and edge computing networks from new types of attacks. Therefore, intrusion detection system (IDS) is an effective defense to secure edge computing network. In this study, an IDS based on machine learning is designed and developed. This article elaborates the technique of Recursive Feature Elimination (RFE) using the Random Forest algorithm (RF). The contribution of this paper is to select a relevant and efficient feature set using the recently developed Python library PyCaret. This paper proposes a novel approach for detecting new types of attacks in network traffic. The recently released dataset CICIDS2017 has been used to evaluate the proposed method, which includes state-of-the-art attacks. In this paper, two classification techniques are also used to build the IDS model. The first is a binary classification technique using the recently developed PyCaret library, and the second is a multiclass classification technique using RFE.
Amrita Kumari, Ashish Saini, Amit Kumar, Vivek Kumar, and Mukesh Kumar
IEEE
Junctionless (JL) devices represent a new generation technological development. Several studies have been conducted with an emphasis on various JL device topologies with and without incorporating strain. In this paper, an attempt has been done to provide a succinct overview of strained-JL (S-JL) devices. Moreover, a review of modelling techniques has also been provided. The need for JL architecture has also been explored for unstrained devices. To examine the improvement in device performance, simulations have been performed by several research groups. According to the study, ultra-short channel devices are in need of this technology since additional scaling to increase transistor density and device functionality has already approached its maximum limit. The ultra-abrupt junctions need not to be constructed in JL devices. A study on the benefits of strain in JL MOSFETs has also been performed. In such strained devices, improvements in ON current of up to 30-40% have been characterized. Improvements in leakage currents and threshold voltage were also seen in strained devices.
Ashish Saini, Sanjeev Kumar, Amrita Kumari, Satender Kumar, Amit Kumar, and Amit Kumar
IEEE
Flying ad hoc networks (FANETs), have a wide range of applications in both civilian and military settings. Although, prevailing routing protocols are effective in well-connected networks, they struggle in sparse networks. To address this issue in FANETs, a new geographic routing method, utilizing a delay-tolerant routing protocol, is proposed in this paper. The proposed method combines position routing and delay tolerant network (DTN) to minimize routing errors. Here, beacons are transmitted by unmanned aerial vehicles (UA Vs) acting as ferries to inform about their succeeding anchor position to other nodes. The node receiving the beacon determines the closest ferry node and base station to the destination. Using the store-carry and forward approach, each node in the network handles sparse networks. Here, we focused to achieve low latency and have developed a novel communication protocol with two options to emphasize the need for lower latency and routing overhead when delivering data. Data collected by searching UAVs is sent to the base station using the ferry. The proposed model is validated using simulated scenarios, which show improved packet delivery, decreased end-to-end delay, and decreased overhead. The study highlights the importance of using communication methods that have lower latency and routing overhead to deliver data efficiently.
Ashish Saini, Raj Kumar, Amrita Kumari, Satendra Kumar, and Mukesh Kumar
IEEE
Quality is very important in any software product, so that the customer trusts the efficiency of the product. The quality or validity of a product is measured by its testing. The test measures the quality of a product as well as shows the validity of the product. For example, testing and measuring the validity of a product in a single software system is not easy. Similarly, the software product line, which produces many different products of the same family at once, makes it even more difficult to check their validity and quality. Several techniques and models have been proposed to test the validity of the software line products and to ascertain the quality. In the same direction, we also propose a method for testing the products of software product line. The proposed method isbased on the distance between the features of the product (Desired and Original). We have used the proposed technique on product line with less features and found that the method presented gives fast and better results than traditional methods.
Akshay Kumar, Pooja Joshi, Ashish Saini, Amrita Kumari, Chetna Chaudhary, and Kapil Joshi
Springer Nature Singapore
Ashish Saini, Rajkumar, Amrita Kumari, and Satender Kumar
IEEE
Software product line includes a series of software products which share common feature’s set. Since the number of features may grow exponentially, it is not possible to test individual products of the entire product line. Since the time budget for testing is limited or even unknown a priori, the sequence of testing products is critical for effective product line testing. Regression testing is the way to test a product after making some changes in the product (for example, after a new version or product is developed). Due to the lack of resources, only a a subset of test cases is executed for testing a specific product. This leads to problems with important test cases regarding testing. Therefore, to lead the test cases, minimization and prioritization of test cases is initiated by the regression testing technique. Existing techniques usually require source code which is time-consuming and complex to execute. However, testing of complex applications often restricts access to source code. Therefore, complex applications can be tested by black-box testing. In this paper, a machine learning- based technique has been proposed to test the software product line. Fuzzy C-Means clustering has been applied to minimize the test cases and Ranked Support Vector Machine to prioritize the rest of the test cases.
Aditya Lama, Vibhor Kumar Vishnoi, Krishan Kumar, Brajesh Kumar, and Ashish Saini
IEEE
Electronic waste or e-waste is a rapidly growing serious threat to the environment. The whole process of managing the e-waste which includes collection, transportation, storage, and recycling or treatment is yet to be well controlled. E-waste disposal has become an emerging issue for public health and the global environment. The convoluted chemicals produced during the e-waste recovery and hazardous by- products raise panic situations for the industry workers and labourers. Generally, the e-waste industry workers are untrained and belong to the informal sector. These people are generally not aware of the necessary precautionary actions to be taken before handling or recovering the e-waste. The inappropriate components, which can’t be reused, are either dumped or burnt outside openly. The toxic gases or hazardous chemicals pollute the environment or can be released directly into water sources. Thus, proper recycling of e-waste in a controlled way is very necessary and ecologically desirable. By promoting the reuse of non-degradable products their extraction rate can be minimized. A formalization of rules for e- waste management and their amendments can potentially offer benefits to this industry and the workers by reducing uncontrolled extraction and providing them employment security. This paper highlights the burden of e-waste, the impact of e-waste on health, the current status of e-waste management concerning the Moradabad region, initiatives for e-waste management including legislation, and current research aspects of e-waste management.
Harshit Sharma, Richa Saxena, Satendra Kumar, Ashish Saini, Mohammad Saad, and Mohammad Faraz
IEEE
In computer system keyboard is the most prominent input medium of all time. But lately, human community is living in an era of global pandemic being afraid of suffering from Coronavirus (Covid-19) and hence each and every person avoids touching anything. This is because of the fear of contracting this contagious virus and their mutants. So, to mitigate this issue, we present a method "webcam based virtual keyboard interface" to interact with a computer system. The code of this method is written using pre- built modules like OpenCV, MediaPipe, PyVDA, Win32API, etc. and Python 3.9. This approach uses matching the index finger and middle finger on the specific key. After that the virtual desktop switching mechanism is done by PyVDA. The PyttSX3 library plays the sound whenever any key is pressed or when a desktop switch is initiated, corresponding to the key pressed or the desktop switched. In this approach no additional hardware device other than the webcam, that is already available in the system, is required. This approach is also useful for those persons who wants the access the system, even when their hands are dirty.
Reshoo Devi, Amit Kumar, Vivek Kumar, Ashish Saini, Amrita Kumari, and Vipin Kumar
IEEE
The main intention of edge computing is to improve network performance by storing and computing data at the edge of the network near the end user. However, its rapid development largely ignores security threats in large-scale computing platforms and their capable applications. Therefore, Security and privacy are crucial need for edge computing and edge computing based environment. Security vulnerabilities in edge computing systems lead to security threats affecting edge computing networks. Therefore, there is a basic need for an intrusion detection system (IDS) designed for edge computing to mitigate security attacks. Due to recent attacks, traditional algorithms may not be possibility for edge computing. This article outlines the latest IDS designed for edge computing and focuses on the corresponding methods, functions and mechanisms. This review also provides deep understanding of emerging security attacks in edge computing. This article proves that although the design and implementation of edge computing IDS have been studied previously, the development of efficient, reliable and powerful IDS for edge computing systems is still a crucial task. At the end of the review, the IDS developed will be introduced as a future prospect.
Amrita Kumari, Ashish Saini, Aditya Lama, and Amit Kumar
IEEE
Junctionless (JL) devices are new generation technology advancement. Numerous research works have been done with focus on several different architectures of strained and unstrained JL devices. In this paper, an effort has been made to give a brief review of strained-JL (S-JL) devices. A review of modeling techniques in such S-JL devices has also been outlined. Unstrained devices have also been reviewed highlighting the need for JL architecture. Simulations have been performed to analyze the enhancement in device performance. The review indicates that this technology is very much required in ultra-short channel devices, where further scaling to improve the transistor density and device functionality have been stretched to their maximum limit. JL devices help to eliminate the need for constructing ultra-abrupt junctions. Advantages of strain in JL MOSFETs are also reviewed. Enhancements of up to 30-40% in ON current has been characterized in such devices. Strained devices also showed improvement in threshold voltage and leakage currents.
Amit Kumar, Vivek Kumar, Ashish Saini, Amrita Kumari, and Vipin Kumar
IEEE
In the digital age, the mass adoption of edge devices or Internet of Things (IoT) devices pose serious challenges to cybersecurity. Today, various new types of attacks including minority attacks are increasing due to the presence of intruders in the network. Furthermore, due to the complex behavior in network or IoT networks, these attacks cannot be detected by traditional algorithms. Therefore, this paper proposes an effective intrusion detection system to detect these attacks in network or IoT networks. Machine learning algorithms Decision Trees, Extra Trees, Gradient Boosted Trees, k-Nearest Neighbors and Random Forest classifiers are used to estimate the benchmark dataset CICIDS2017. Furthermore, the RFE (recursive feature elimination technique) is utilized to select the most suitable or optimal set of features for detecting minority attack.
Ashish Saini, Raj Kumar, Gaurav Kumar, Satendra Kumar, and Mohit Mittal
Inderscience Publishers
Ashish Saini, Rajkumar, and Satendra Kumar
Springer Nature Singapore
Ashish Saini, Raj Kumar, Satendra Kumar, and Mohit Mittal
Inderscience Publishers