RETRACTED ARTICLE: Comparative analysis of time series model and machine testing systems for crime forecasting

S Jha, E Yang, AO Almagrabi, AK Bashir… - Neural Computing and …, 2021 - Springer
Crime forecasting has been one of the most complex challenges in law enforcement today,
especially when an analysis tends to evaluate inferable and expanded crime rates, although …

Smo-dnn: Spider monkey optimization and deep neural network hybrid classifier model for intrusion detection

N Khare, P Devan, CL Chowdhary, S Bhattacharya… - Electronics, 2020 - mdpi.com
The enormous growth in internet usage has led to the development of different malicious
software posing serious threats to computer security. The various computational activities …

Cost-effective ensemble models selection using deep reinforcement learning

Y Birman, S Hindi, G Katz, A Shabtai - Information Fusion, 2022 - Elsevier
Ensemble learning–the application of multiple learning models on the same task–is a
common technique in multiple domains. While employing multiple models enables reaching …

Trends in cybersecurity management issues related to human behaviour and machine learning

J Scott, M Kyobe - 2021 International Conference on Electrical …, 2021 - ieeexplore.ieee.org
The number of organisational cybersecurity threats continues to increase every year as
technology advances. All too often, organisations assume that implementing systems …

An efficient mixed attribute outlier detection method for identifying network intrusions

JR Beulah, DS Punithavathani - International Journal of Information …, 2020 - igi-global.com
Intrusion detection systems (IDS) play a vital role in protecting information systems from
intruders. Anomaly-based IDS has established its effectiveness in identifying new and …

Enhancing detection of R2L attacks by multistage clustering based outlier detection

JR Beulah, M Nalini, DS Irene… - Wireless Personal …, 2022 - Springer
The modern society is greatly benefited by the advancement of Internet. The contemporary
humanity is significantly profited by the Internet. The ease of access to the Internet have …

Author classification using transfer learning and predicting stars in co‐author networks

R Abbasi, A Kashif Bashir, J Chen… - Software: Practice …, 2021 - Wiley Online Library
The vast amount of data is key challenge to mine a new scholar that is plausible to be star in
the upcoming period. The enormous amount of unstructured data raise every year is …

Designing a dynamic framework for people counting using YOLO-PC

K Duraipandian, BR Padmanabhan… - AIP Conference …, 2024 - pubs.aip.org
Determining the count of individuals in a public space is helpful for video surveillance and
security applications. The existing system which uses the Wi-Fi CSI method to count the …

Role of deep learning algorithms in securing Internet of Things applications

R Arul, S Basheer, A Abbas… - Deep Learning for Internet …, 2021 - taylorfrancis.com
The Internet of Things (IoT) has become the biggest sector for commercialization as well as
industrialization in this era. Automation in the machinery, machine-to-machine …

An Efficient Methodology for Resolving Uncertain Spatial References in Text Documents

K Raja, VR Kanagavalli, NB PK… - International Journal of …, 2020 - igi-global.com
In recent decades, all the documents maintained by the industries are getting transformed
into soft copies in either structured documents or as an e-copies. In text document …