Rakesh Kumar

16 papers Journal 14Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Deep learning approaches to address cold start and long tail challenges in recommendation systems: a systematic review.
Multim. Tools Appl.
Manisha Jangid, Rakesh Kumar
2025 J jnl
Dual attention-based CNN-LSTM framework for session-based recommendations.
Evol. Syst.
Manisha Jangid, Rakesh Kumar
2025 J jnl
Energy Efficient Resource Sharing in Trustworthy Federated Cloud Environment: A Bayesian Game and Double Auction Based Approach.
IEEE Trans. Serv. Comput.
Sandeep Singh Sikarwar, Rakesh Kumar, Benay Kumar Ray
2025 J jnl
Enhancing user experience: a content-based recommendation approach for addressing cold start in music recommendation.
J. Intell. Inf. Syst.
Manisha Jangid, Rakesh Kumar
2025 J jnl
Multi-attribute based double auction for virtual machine trading in federated cloud environment.
Clust. Comput.
Sandeep Singh Sikarwar, Rakesh Kumar, Benay Kumar Ray
2023 J jnl
EVACON-Rainsnow Computing: An Amalgamation of Cloud and Its Inherited Computing to Encourage End User for Both Localized and Globalized Remote Computing.
Wirel. Pers. Commun.
Santosh Kumar Yadav, Rakesh Kumar
2022 J jnl
Data dissemination approach using machine learning techniques for WBANs.
Concurr. Comput. Pract. Exp.
Roopali Punj, Rakesh Kumar
2022 J jnl
Scalable Profit Optimized Incentive Mechanism for Resources in Cloudlet Based Mobile Edge Computing Framework.
Wirel. Pers. Commun.
Santosh Kumar Yadav, Rakesh Kumar
2021 J jnl
A survey on analysis and detection of Android ransomware.
Concurr. Comput. Pract. Exp.
Shweta Sharma, Rakesh Kumar, C. Rama Krishna
2021 J jnl
An ensemble-based supervised machine learning framework for android ransomware detection.
Int. Arab J. Inf. Technol.
Shweta Sharma, Rama Krishna Challa, Rakesh Kumar
2021 J jnl
RansomDroid: Forensic analysis and detection of Android Ransomware using unsupervised machine learning technique.
Digit. Investig.
Shweta Sharma, C. Rama Krishna, Rakesh Kumar
2020 — conf
Android Ransomware Detection using Machine Learning Techniques: A Comparative Analysis on GPU and CPU.
ACIT
Shweta Sharma, C. Rama Krishna, Rakesh Kumar
2020 J jnl
Energy Efficient Dynamic Cluster Head and Routing Path Selection Strategy for WBANs.
Wirel. Pers. Commun.
Roopali Punj, Rakesh Kumar
2020 J jnl
The Paradox of Choice: Investigating Selection Strategies for Android Malware Datasets Using a Machine-learning Approach.
Commun. Assoc. Inf. Syst.
Shweta Sharma, Naveen Kumar, Rakesh Kumar, C. Rama Krishna
2019 J jnl
Technological aspects of WBANs for health monitoring: a comprehensive review.
Wirel. Networks
Roopali Punj, Rakesh Kumar
2017 — conf
CHS-GA: An Approach for Cluster Head Selection Using Genetic Algorithm for WBANs.
REV
Roopali Punj, Rakesh Kumar
redb/extractors/decompiler/apk/__init__.py
← Index redb/extractors/decompiler/apk/__init__.py python 
"""APK code analysis module — androguard + JADX + apktool integration."""

from redb.extractors.decompiler.apk.analyzer import APKCodeAnalyzer
from redb.extractors.decompiler.apk.library_filter import LibraryFilter
from redb.extractors.decompiler.apk.smali_parser import SmaliParser
from redb.extractors.decompiler.apk.jadx_wrapper import JADXDecompiler
from redb.extractors.decompiler.apk.apktool_wrapper import ApktoolDisassembler

__all__ = [
    "APKCodeAnalyzer",
    "LibraryFilter",
    "SmaliParser",
    "JADXDecompiler",
    "ApktoolDisassembler",
]