Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Cluster Computing
Published in: Cluster Computing 3/2019

07-12-2017

Analysis of the structure of hive files and the implementation of pivotal operations for distributed computing environment

Authors: Qing Su, Yihao Tang, Zhanyi Li, Kai Liu, Tianyi Cheng

Published in: Cluster Computing | Special Issue 3/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This paper provides a thorough analysis of the storage structure of hive files and then proposes a new method for processing hive files independently of the Windows registry API and for achieving direct access. The method has the advantages of high priority and of preserving the computing environment. In particular, it is suitable for occasions when the hive files of the target operating system cannot be copied or directly loaded. This paper also presents a set of algorithms for key operations associated with hive files such as access, deletion, creation, and expansion. These operations are designed to be independent of the Windows API. Third-party developers can develop other specialized applications on the basis of this set of algorithms. A complete hivedit program to carry out the operations described above has been implemented. This program can be executed before loading the operating system with the assistance of the ECM-XDP3 emulator, and the correctness of all the algorithms has been verified.
previous article An improved LLE-based cluster security approach for nonlinear system fault diagnosis
next article The computation on -connectedness index of uncertain graph

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Mbatha, M.P.: Windows registry forensic artifacts. University of Nairobi, School of Computing and Informatics, Shellbags for Computer Security. College of Biological and Physical Sciences (2016)
2.
Kaur, R., Chadha, R.: Comparative analysis of various file formats in HIVE. Int. J. Technol. Comput. 3(6), 135–139 (2017)
3.
Ramani, A., Dewangan, S.K.: Digital forensic identification, collection, examination and decoding of windows registry keys for discovering user activities patterns. Int. J. Comput. Trends Technol. 17(2), 101–111 (2014)CrossRef
4.
Ravi, C., Manoharan, R.: Malware detection using windows API sequence and machine learning. Int. J. Comput. Appl. 43(17), 12–16 (2012)
5.
Luttgens, J.T., Pepe, M., Mandia, K.: Incident Response & Computer Forensics. McGraw-Hill Education Group, New York (2014)
6.
Russinovich, M.E., Solomom, D.A., Ionescu, A.: Windows Internals, 7th edn. Microsoft Press, Redmond (2017)
7.
8.
Dolan-Gavitt, B.: Forensic analysis of the Windows registry in memory. Digit. Investig. 5, S26–S32 (2008)CrossRef
9.
Raghavan, S.: Digital forensic research: current state of the art. CSI Trans. ICT 1(1), 91–114 (2013)CrossRef
10.
Thomassen, Jolanta: Forensic Analysis of Unallocated Space in Windows Registry Hive Files. The University of Liverpool, Liverpool (2008)
11.
Khanuja, H.K., Adane, D.S.: Forensic Analysis for Monitoring Database Transactions. In: Proceedings of International Symposium on Security in Computing and Communication. Springer, Berlin, pp. 201–210 (2014)
12.
Khalidi Y.A., Smith, F.J. IV, Talluri, M.: Merging registry keys, U.S. Patent 8 245 035 B2. Aug 14 (2012)
13.
14.
Ramani, A., Dewangan, S.K.: Auditing Windows 7 Registry Keys to track the traces left out in copying files from system to external USB Device. Int. J. Comput. Sci. Inf. Technol. 5(2), 1045–1052 (2014)
15.
Patil, D.N., Meshram, B.B.: RegForensicTool: evidence collection and analysis of windows registry. Int. J. Cyber Secur. Digit. Forensics 2, 94–105 (2016)CrossRef
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
Alghafli, K.A., Jones, A., Martin, T.A.: Forensic analysis of the Windows 7 Registry. J. Digit. Forensics Secur. Law 5(4), 5–30 (2010)
27.
Bose, R.P.J.C., Srinivasan, S.H.: mRegistry: a registry representation for fault diagnosis. In: Proceedings of International Conference on Intelligent Systems Design and Applications 2005. Isda ’05. Proceedings of the IEEE, pp. 37–42 (2005)
28.
Morgan, T.D.: Recovering deleted data from the Windows registry. Digit. Investig. 5(Suppl. 1), S33–S41 (2008)CrossRef
29.
Tabarno, S.M., Sharma, A.K., Verma, N.: A futuristic digital forensic software framework for analyzing the registry of windows based systems. Softw. Eng. Technol. 5(8), 282–286 (2013)
30.
31.
Cui, B., Wang, C., Dong, G., Ma, J.: A program behavior recognition algorithm based on assembly instruction sequence similarity. In: Proceedings of International Conference on Broadband and Wireless Computing, Communication and Applications, pp. 13–20 (2017)
32.
Zhou, Q., Luo, J.: Artificial neural network based grid computing of E-government scheduling for emergency management. Comput. Syst. Sci. Eng. 30(5), 327–335 (2015)
33.
34.
Roy, T., Jain, A.: Windows registry forensics: an imperative step in tracking data theft via USB devices. Int. J. Comput. Sci. Inf. Technol. 3(3), 4427–4433 (2012)
Metadata
Title
Analysis of the structure of hive files and the implementation of pivotal operations for distributed computing environment
Authors
Qing Su
Yihao Tang
Zhanyi Li
Kai Liu
Tianyi Cheng
Publication date
07-12-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1468-1

Other articles of this Special Issue 3/2019

Cluster Computing 3/2019 Go to the issue

OriginalPaper

Multi-base multi-UAV cooperative reconnaissance path planning with genetic algorithm

OriginalPaper

A matching model for plant growth environment based on weighted multi-dimensional tree designed for big data

OriginalPaper

Self-healing reconfiguration scheme for distribution network with distributed generations based on multi-agent systems

OriginalPaper

Collective behavior simulation based on agent with artificial emotion

OriginalPaper

The simulation model on delay time of road accessibility based on intelligent traffic control system

OriginalPaper

A dynamic clustering based method in community detection

Premium Partner

    Image Credits