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Survey on Malicious URL Detection Techniques
Crimes in the cyberspace are increasing day by day. Recent cyber threat defense reports states that 80.7% of the systems are compromised at least once in 2020. Cyber criminals taking the pandemic situation as an opportunity for the mass attack through malicious URL circulated by email or text messages in social media. Performing cyber-attacks through malicious URLs is the handy method for the cyber criminals. Protecting from such attacks requires proper awareness and solid defense system. Some of the common approaches followed by the cybercriminals to deceive the victims are 1. Phishing URLs which is very similar to the legitimate URLs. 2. Redirecting URLs 3. Using JavaScript, redirects to the phishing URL when user interacts with webpage 4. Social engineering etc. As soon as the novice internet users clicks on the malicious URL link, cyber criminals can easily steal personal information or install malware on their device to get additional access. Recently malicious URLs are generated algorithmically and uses URL shortening service to evade the existing security setup such as firewall and web filters. In literature, the researchers have proposed several ways to detect the malicious URLs but, new attack vectors that are introduced by the cyber criminals can easily bypass the security system. The purpose of this paper is to provide an overview of various malicious URL detection techniques which includes blacklist based, rules based, machine learning and deep learning-based techniques. Most importantly, the paper discusses the common features used by the detection system from webpages to classify the URL as malicious or benign and various performance metrics. This will encourage the new researchers to bring out the innovative solutions. 2022 IEEE. -
Prominent label identification and multi-label classification for cancer prognosis prediction
Cancer prognosis prediction improves the quality of treatment and increases the survivability of the patients. Conventional methods of cancer prediction deal with single class by limiting the prognosis prediction to one response variable. The SEER Public Use cancer database has more prominent variables that support better prediction approach. The objective of this paper is to find the prominent labels from cancer databases and use them in a multi-class environment. The implementation consist of three phases namely, pre-processing, prominent label identification and multi-label classification. Breast, Colorectal and Respiratory Cancer Data sets have been used for the experimentation. Also random samples from all three data sets are generated to form a mixed cancer data. Patient survival, number of primaries and age at diagnosis are the prominent labels identified from others using the Decision tree, Nae Bayes and KNN algorithms. The three prominent labels have been tested using multi-label RAkEL algorithm to find the relations between them. The results of the empirical study are comparatively better than the traditional way of cancer prediction. 2012 IEEE. -
A Framework for Integrating the Distributed Hash Table (DHT) with an Enhanced Blooms Filter in MANET
MANET, a self-organizing, infrastructure-less, wireless network is a fast-growing technology in day-to-day life. There is a rapid growth in the area of mobile computing due to the extent of economical and huge availability of wireless devices which leads to the extensive analysis of the mobile ad-hoc network. It consists of the collection of wireless dynamic nodes. Due to this dynamic nature, the routing of packets in the MANET is a complex one. The integration of distributed hash table (DHT) in MANET is performed to enhance the overlay of routing. The node status updating in the centralized hash table creates the storage overhead. The bloom filter is a data structure that is a space-effective randomized one but it allows the false-positive rates. However, this can be able to compensate for the issue of storage overhead in DHT (Distributed hash table). Hence, to overcome the storage overhead occurring in DHT, and reduce the false positives, the Bloom's filter is integrated with the DHT initially. Furthermore, the link stability is measured by the distance among mobile nodes. The optimal node selection should be done for the transmission of packets which is the lacking factor. If it fails to select the optimal path then the removal of malicious nodes may lead to the unwanted entry of nodes into the other clustering groups. Therefore, to solve this problem, the bloom's filter is modified for enhancing the link stability. The novelty of this proposed work is the integration of Bloom's filter with the Distributed Hash Table which provides good security on transmission data by removing false-positive errors and storage overhead 2022,International Journal of Advanced Computer Science and Applications.All Rights Reserved -
Link stability - based optimal routing path for efficient data communication in MANET
The paper delves into the complexities of Mobile Ad hoc Networks (MANETs), which consist of a diverse array of wireless nodes. In such networks, routing packets poses a significant challenge due to their dynamic nature. Despite the variety of techniques available for optimizing routing in MANETs, persistent issues like packet loss, routing overhead, and End-to-End Delay (EED) remain prevalent. In response to these challenges, the paper proposes a novel approach for efficient Data Communication (DC) by introducing a Link Stability (LS)-based optimal routing path. This approach leverages several advanced techniques, including Pearson Correlation Coefficient SWIFFT (PCC-SWIFFT), Galois-based Digital Signature Algorithm (G-DSA), and Entropy-based Gannet Optimization Algorithm (E-GOA). The proposed methodology involves a systematic process. Initially, the nodes in the MANET are initialized to establish the network infrastructure. Subsequently, the Canberra-based K Means (C-K Means) algorithm is employed to identify Neighboring Nodes (NNs), which are pivotal for creating communication links within the network. To ensure secure communication, secret keys (SK) are generated for both the Sender Node (SN) and the Receiver Node (RN) using Galois Theory. Following this, PCC-SWIFFT methodologies are utilized to generate hash codes, serving as unique identifiers for data packets or routing information. Signatures are created and verified at the SN and RN using the G-DSA. Verified nodes are subsequently added to the routing entry table, facilitating the establishment of multiple paths within the network. The Optimal Path (OP) is selected using the E-GOA, considering factors such as link stability and network congestion. Finally, Data Communication (DC) is initiated, continuously monitoring LS to ensure optimal routing performance. Comparative analysis with existing methodologies demonstrates the superior performance of the proposed model. In summary, the proposed approach offers a comprehensive solution to enhance routing efficiency in MANETs by addressing critical issues and leveraging advanced algorithms for key generation, signature verification, and path optimization. 2024, Universitas Ahmad Dahlan. All rights reserved. -
A Spatio-temporal Model for the Analysis and Classification of Soil Using the IoT
The Internet of Things (IoT) is an evolving trend in the field of computer applications where various hardware and software are connected together to address a specific problem. With the help of the IoT, the world has become smart and enabled itself to connect various objects (e.g., cars, computers, mobile phones, and smart appliances) with distinctive Internet protocol addresses, which allows them to interact with one another, thus accomplishing various procedures. Applications of the IoT include but are not restricted to smart cities, healthcare, industry, and robotics. Amongst a huge list of applications furnished by the IoT, agricultural IoT is the theme of this chapter. The IoT in agriculture transforms entities such as crops, soils, and livestock in a smart way by utilizing underlying technologies such as embedded systems, pervasive computing, sensor networks, ubiquitous computing, ad hoc networks, various wireless communication technologies, Internet protocols and other advanced technologies. The research here focuses on the most important agriculture entity soil. It is the soil that determines the yield of a crop. The more fertile the soil, more qualitative is the yield. The main idea behind the research is to identify the soil most suitable for agriculture. Using a spatio-temporal model, the soil samples collected from various parts of the country are classified into agricultural soil and non-agricultural soil. This classification is done by the aid of features such as the pH of the soil, and its humidity, moisture, and temperature collected from IoT sensors. The chapter begins with an introduction to the usage of IoT technology in different areas of agriculture followed by an account of the proposed state-of-the-art model, and its results, analysis, and a conclusion. 2022 selection and editorial matter, Vikram Bali, Vishal Bhatnagar, Deepti Aggarwal, Shivani Bali, and Mario JosDiv; individual chapters, the contributors. -
Revolutionizing Road Traffic Management and Enforcement: Harnessing AI, ML, and Geospatial Techniques
This study investigates the synergistic application of Artificial Intelligence (AI), Machine Learning (ML), and Geospatial Technologies in optimizing traffic management systems. Through a mixed-methods research design, it evaluates the potential of these technologies to enhance urban traffic flow and reduce congestion. The research emphasizes the critical importance of data quality, ethical considerations, and the selection of appropriate technological solutions based on specific urban traffic scenarios. Findings highlight the significant role of integrated AI and geospatial analyses in improving traffic predictions and operational efficiency. Future work will focus on developing more sophisticated models that ensure privacy, equity, and adaptability to new transportation trends. 2024 IEEE. -
Enhancing Traffic Incident Management and Regulatory Compliance Using IoT and Itms: A Mumbai Traffic Police Case Study
In the rapidly urbanizing landscape of Mumbai, a megacity confronted with significant traffic management and law enforcement challenges, the deployment of an advanced city surveillance system represents a transformative approach to urban governance. This paper examines the integration of over 11,000 CCTV cameras into the Mumbai Traffic Police's operational framework, covering an area of 438 square kilometers encompassing 41 traffic divisions and 94 police stations. Since its inception in 2016, the system has been pivotal in enhancing safety, order, and mobility within the city, especially amid obstacles such as ongoing infrastructure projects, traffic congestion, accidents, and natural disasters. Central to this study is the analysis of the Mumbai City Surveillance System Project (MCSP), which leverages CCTV technology to generate and classify Incident Reports (IR) based on severity, ranging from minor disruptions to significant emergencies. The period from October 2021 to 2023 saw a marked increase in IR generation, from 742 reports in 2021 to 10,392 in 2022 and 9,639 in 2023, indicating the system's growing efficacy in real-time traffic management and incident response.This paper further explores the cutting-edge integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies within the MCSP framework, highlighting the role of computational intelligence in enhancing the capabilities of Intelligent Transportation Systems (ITS). By employing AI-driven predictive analytics, the system effectively anticipates traffic conditions based on diverse variables such as traffic flow, vehicle speed, and weather, thereby optimizing traffic management strategies.The findings underscore the significant impact of AI and IoT technologies in redefining urban transportation networks, demonstrating improved efficiency, safety, and resilience in the face of Mumbai's complex transportation challenges. This study contributes to the discourse on smart city initiatives, offering insights into the role of advanced computational technologies in facilitating intelligent transportation solutions and shaping the future of urban living. 2024 IEEE. -
Impact of human resource practice on work engagement and turnover intention in information technology companies
Orientation: The information technology (IT) sector, a global economic driver, faces high employee turnover because of low work engagement. This study examines the relationship between human resource management (HRM) practices and their impact on work engagement and turnover intention (TI) in IT companies. Research purpose: The primary purpose of this research article is to investigate how HRM practices influence employee work engagement and TI in the IT sector. Motivation for the study: This study is motivated by the need to address this critical issue by exploring the role of HRM practices in shaping employee engagement and TI. Research approach/design and method: The research data came from 10 IT organisations in Pune IT parks. Non-probability convenience sampling was used to collect data. Data were analysed using Structural Equation Modelling (SEM), Statistical Package for Social Science (SPSS) and Moment Structure Analysis to evaluate the hypotheses. Main findings: The study found that HRM practices such as effective communication (EC), training satisfaction (TS), performance appraisal satisfaction (PAS), pay satisfaction (PS) and opportunities for development (OFD) positively influence work engagement among IT employees. Addressing these HRM practices can enhance employee retention and engagement in the IT sector. Practical/managerial implications: Implementing these strategies can lead to a more committed and productive workforce, improving overall organisational performance and retention. Contribution/value-add: This research offers actionable recommendations for IT companies to improve employee retention and engagement, filling a gap in existing literature by focussing exclusively on the unique challenges and dynamics of the IT industry. 2024. The Authors. -
Analyzing Job Satisfaction, Job Performance, and Attrition in International Business Machines Corporation through Python
Since workers significantly impact the firm's operation, businesses invest heavily in them. They must deliver better and more excellent performance to compete with the increasing competition. Employee performance is becoming more and more important for business success and staying ahead of the competition, so companies are putting more money into things like training, growth centers, and careers. The target audience was the employees working in International Business Machines Corporation. The data was analyzed through the process of Exploratory Data Analysis using Python. There is a 0.002297 link between Job Satisfaction and Performance Rating, and a 0.002572 correlation between Work Life Balance and Performance Rating. The relationship between work-life balance and job involvement is -0.01462, indicating a negative impact on work-life balance for people who are heavily interested in their occupations. The study would help Human Resources Managers formulate their policies and understand the employees better in the current environment. Here, Job Satisfaction and Performance Rating served as mediators, and the findings show that their influence on Attrition is minimal at this firm. 2024 IEEE. -
Women in higher education institutions: Challenges faced by women in HEI and emerging opportunities
A multitasking Queen plays a heterogeneous role in each and everyone 's tremendous journey of life right from the beginning until the end. As a wife, mother, sister, daughter, mentor, philosopher, friend, lover, and most importantly, 'first teacher', her contributions are noteworthy. Nobody can even dream up life without a woman. Women are capable enough in learning, teaching, and sustenance throughout their life. The art of learning and teaching encompasses the art of living. As a teacher, she is a source of inspiration, knowledge, and reason for the future. The first smile, step, voice, and any word are being routed by the first teacher called mother cum woman. This chapter explores women in higher education institutions. 2022, IGI Global. All rights reserved. -
HydroIoT: An IoT and Edge Computing based Multi-Level Hydroponics System
The depleting area of cultivable lands is increasing demands for implementing improved techniques that could use less space and produce more than traditional farming. This situation is common in all the developing and under developed countries. With a motivation to contribute towards providing solution to this growing problem of food scarcity, a Multi-Level Hydroponics System is proposed. The proposed system combines best of all trending technologies like IoT, Edge Computing and Computer Vision and applies it to Hydroponics. A cultivation estimation system based on image processing is implemented and accuracy of the same is tested with actual produce. The crop used for the proposed system is corn as it serves as best fodder for cattle. It was observed that with proposed system up to 95% accuracy in estimating fodder produce was achieved. 2021 IEEE. -
Source-load-variable voltage regulated cascaded DC/DC converter for a DC microgrid system
Solar energy is available abundantly, the utilization of solar energy is developing rapidly and the photovoltaic based direct current (DC) microgrid system design is under demand but the stability of the DC voltage is of most important issue, as the variation of the output DC voltage is a common problem when the load or source voltage varies, hence a regulated DC output voltage converter is proposed. This paper presents source-load-variable (SLV) voltage regulated cascaded DC/DC converter which is used to obtain regulated output voltage of 203.1 V DC at 0.4 duty ratio with 2% voltage fluctuations for the variation in the input source voltage and 1.5% voltage fluctuations for the variation in load resistance of the nominal value with lower output voltage ripple and without use of sub circuits. A simulation model of SLV voltage regulated cascaded DC/DC converter in LTspice XVII software environment for the assessment of converter performance at different input source voltages and load resistances are verified. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
A Review of Comprehension and Operation of DC/DC Converters Precisely Voltage Multiplier and Voltage Lift Converters
Converters in power electronics play a significant part in the power conversion of distributed generation and grid-connected systems. This paper gives comprehension analysis and operation of various non-isolated step-up DC/DC converters for renewable energy applications using voltage multiplier or/and voltage lift techniques to attain higher voltage gain. An isolated converter structure mainly comprises a transformer which is associated with high cost, complexity, leakage inductance, losses and EMI problems with the decrease in the efficiency of the converter, hence the operation of several DC/DC converters precisely voltage multiplier and voltage lift converters are discussed with relative simulation results obtained. 2022 Seventh Sense Research Group. -
Navigating real estate purchase decisions: an interplay of influential factors
Purpose: The purpose of this study is to investigate the relationship between social trends, peer influence, personal attitudes regarding real estate purchase decisions, perception of long-term property value and the mediating effect of hedging in influencing property and real estate purchases. Design/methodology/approach: Using a combination of quantitative surveys, this study aims to provide a comprehensive knowledge of the factors influencing real estate buying decisions. Data were obtained from 399 young consumers in four Indian cities. Using structural equation modeling, the suggested conceptual framework is examined. Findings: The studys findings suggest that attitude plays an important role in influencing real estate purchase decisions. Young adults also tend to look for long-term gains or value when purchasing a home. Developing durable products for the customers is the best way to grow business, according to the results. Originality/value: To the best of the authors knowledge, this is the first paper that examines the role of sentimental, personal and financial factors in real estate purchase decisions. The study provides insights into how these factors interact and affect the decisions of consumers in real estate. The authors hope that the findings will be useful for real estate professionals to better tailor their services to meet the needs of their customers. 2024, Emerald Publishing Limited. -
Counseling and psychotherapy in india: Professionalism amidst changing times
India is a melting pot of diversity in castes, communities, geographical regions, languages, religions, and practices, within a geographical area of 32,87,263 kilometers, with 28 states and seven union territories. Although the notions of counseling and psychotherapy are Western, the process of mentoring and assisting individuals through their developmental issues was already present in ancient models of care in India, such as the Guru Shishya System,1 the Joint Family Network,2 and traditional healing. Counseling and psychotherapy do not exist as completely distinct disciplines in India. Although counseling grew out of a strong guidance format and led to a proliferation of trained and lay counselors and psychotherapy arose from a strong theoretical clinical psychology background, these differences are blurred in society. As Arulmani (2007) points out: all that is termed as counseling today was embedded within a complex support system of social relationships (p. 70). Although these fields progressed, difficulties with accreditation exist. The Indian Association of Clinical Psychologists (IACP), along with other bodies such as the Counseling Association of India, offer discussions of matters related to psychotherapy counseling and clinical psychology, and provide the code of conduct in India (IACP, 1993). Varma (1982) highlighted seven distinct features of the Indian population that strongly infiuence how counseling and psychotherapy are practiced and received by clients: Mutual interdependence, lack of psychological sophistication involving introspective and verbal abilities, social distance between the doctor and the patient due to class hierarchies, religious belief in rebirth and fatalism and related accountability, guilt attributed to misdeeds in past life and social approval-related shame, and lower emphasis on confidentiality as society can be therapeutic allies. India is a collectivistic society wherein the self is relational (Roland, 2005), though recent socio-economic changes have resulted in a contradictory mix of traditional and modern elements in families (Murthy, 2003). Shah and Isaac (2005) note that relationship problems dominate themes in clinical interviews and in the process of individual, couple and family therapy sessions in India. 2013 by Taylor & Francis Group, LLC. -
The Eff ect of Music and Editing Style on Subjective Perception of Time When Watching Videos An Eye-tracking Study
Arousal, editing style, and eye movements have been implicated in time perception when watching videos. However, little multimodal research has explored how manipulating both the auditory and visual properties of videos aff ects temporal processing. This study investigated how editing density and music-induced arousal aff ect viewers time perception. Thirty-nine participants watched six videos varying in editing density and music while their eye movements were recorded. They estimated the videos duration and reported their subjective experience of time passage and emotional involvement. Fast-paced editing was associated with the feeling of time passing faster, a relationship mediated by fi xation durations. Higharousal background music was also associated with the feeling of time passing faster. The consequences of this study in terms of a possible auditory driving eff ect are explored. The Author/s -
Assessing the Effectiveness of Implied Volatility in Predicting Realised Return Volatility for Informative Decision-Making: Insights from the Nifty Bank Index
Implied volatility (IV) is crucial in option pricing models and serves as an essential tool for volatility traders to make informed decisions. However, its effectiveness in predicting realized return volatility is still debated. This study investigates the efficiency of implied volatility in forecasting realized return volatility in the Indian financial markets, specifically using Bank Nifty index options and also assesses the predictive capability of implied volatility against the realised volatility estimator. Utilizing data spanning five years, from January 2018 to December 2022. Finding of this study reveal that implied volatility significantly forecasts realized volatility, highlighting its efficacy as a forecasting tool. Moreover, historical volatility fails to enhance predictive power when combined with implied volatility. Nonetheless, caution should be exercised in generalizing these results to other markets or time periods, as further research is warranted. The study contributes to the ongoing discourse on implied volatility efficiency, offering practical insights for options traders and adding to the body of knowledge in financial economics. 2024, Iquz Galaxy Publisher. All rights reserved. -
Design techniques in carry select adder using parallel prefix adder for improved switching energy
A new architecture of Carry select adder has been proposed with improved switching energy using parallel prefix adder. The conventional Carry select adder is the use of two Ripple Carry Adder (RCA) and a multiplexer. The findings in this work are the replacement of one RCA block by Brent Kung adder and the other RCA block by excess-1 converter. Simulation results show that the proposed Carry select adder is proved to have improved switching energy when compared with the other adders in 45nm CMOS process. 2021 Wydawnictwo SIGMA-NOT. All rights reserved. -
Organizing data using lists: A sequential data structure
Computer programming aims to organize and process data to get the desired result. Software developer chooses a programming language for application development based on the data processing capabilities of the language. The list is one of the sequential data structures in Python. A list is limited to a particular data type, such as numbers or strings. Occasionally, a list may include data of mixed types, including numbers and strings. Elements in the list can be accessed by using the index. Usually, a list's elements are enclosed within square brackets and divided using commas. The list may be referred to as a dynamic-sized array, which denotes that its size increases as additional data is added and that its size is not predefined. List data structure allows repetition; hence, a single data item may appear several times in a list. The list assists us in solving several real-world problems. This chapter deals with the list's creation and manipulation, the complexity of processing the list, sorting, stack, and queue operations. 2023, IGI Global. All rights reserved. -
An Investigation into the Role of AI-Based Innovation in Supporting the Next Generation of Startup Entrepreneurs
The advent of Artificial Intelligence (AI) has revolutionized various industries, offering unprecedented opportunities for innovation and entrepreneurship. This investigation delves into the pivotal role of AI-based innovation in nurturing and empowering the next generation of startup entrepreneurs.AI technologies, including machine learning, natural language processing, and computer vision, have significantly augmented the capabilities of startups across diverse sectors. This study aims to elucidate the multifaceted ways in which AI fosters entrepreneurial endeavors, from ideation to market penetration.AI algorithms enable startups to analyze vast datasets swiftly, extracting valuable insights that inform strategic decision-making and product development. Through predictive analytics and trend forecasting, entrepreneurs can anticipate market demands, optimize resource allocation, and mitigate risks, thereby enhancing the viability and competitiveness of their ventures.AI facilitates personalized customer experiences, driving customer engagement and retention for startups. By leveraging AI algorithms to analyze user behavior and preferences, entrepreneurs can deliver tailored products, services, and marketing campaigns, fostering brand loyalty and customer satisfaction.The integration of AI into startup ecosystems also presents various challenges, including ethical considerations, data privacy concerns, and regulatory complexities. Therefore, this investigation also explores the ethical implications and regulatory frameworks surrounding AI-based entrepreneurship, advocating for responsible innovation practices and stakeholder collaboration. 2024, Collegium Basilea. All rights reserved.