The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
Physical and Cyber Crime Detection using Digital Forensic Approach: A Complet...IJARIIT
Criminalization may be a general development that has significantly extended in previous few years. In
order, to create the activity of the work businesses easy, use of technology is important. Crime investigation analysis
is a section records in data mining plays a crucial role in terms of predicting and learning the criminals. In our
paper, we've got planned an incorporated version for physical crime as well as cybercrime analysis. Our approach
uses data mining techniques for crime detection and criminal identity for physical crimes and digitized forensic tools
(DFT) for evaluating cybercrimes. The presented tool named as Comparative Digital Forensic Process tool
(CDFPT) is entirely based on digital forensic model and its stages named as Comparative Digital Forensic Process
Model (CDFPM). The primary step includes accepting the case details, categorizing the crime case as physical crime
or cybercrime and sooner or later storing the data in particular databases. For physical crime analysis we've used kmeans
approach cluster set of rules to make crime clusters. The k-means method effects are a lot advantageous by the
utilization of GMAPI generation. This provides advanced and consumer-friendly visual-aid to k-means approach for
tracing the region of the crime. we have applied KNN for criminal identification with the
help of observing beyond crimes and finding similar ones that suit this crime, if no past document is discovered then
the new crime sample are introduced to the crime data-set. With the advancements of web, the network form has
become much more complicated and attacking methods are further more than that as well. For crime analysis
we're detecting the attacks executed on host system through an outsider the usage of
assorted digitized forensic tools to produce information security with the help of generating reports for an
event which could need any investigation. Our digitized technique aids the development of the society
by helping the investigation businesses to follow a custom-built investigative technique in crime analysis and criminal
identification as opposed to manually looking the database to analyze criminal activities, and as a
result facilitate them in combating crimes.
Enhancements in the world of digital forensicsIAESIJAI
Currently, the rapid advancement of computer systems and mobile phones has resulted in their utilization in unlawful acts. Ensuring adequate and effective security measures poses a difficult task due to the intricate nature of these devices, thereby exacerbating the challenges associated with investigating crimes involving them. Digital forensics, which involves investigating cyber crimes, plays a crucial role in this realm. Extensive research has been conducted in this field to aid forensic investigations in addressing contemporary obstacles. This paper aims to explore the progress made in the applications of digital forensics and security, encompassing various aspects, and provide insights into the evolution of digital forensics over the past five years.
Crime and violence are inherent in our political and social system. With the moving pace of technology, the
popularity of internet grows continuously, with not only changing our views of life, but also changing the
way crime takes place all over the world. We need a technology that can be used to bring justice to those
who are responsible for conducting attacks on computer systems across the globe. In this paper, we present
various measures being taken in order to control and deal with the crime related to digital devices. This
paper gives an insight of Digital Forensics and current situation of India in handling such type of crimes.
Review on effectiveness of deep learning approach in digital forensicsIJECEIAES
Cyber forensics is use of scientific methods for definite description of cybercrime activities. It deals with collecting, processing and interpreting digital evidence for cybercrime analysis. Cyber forensic analysis plays very important role in criminal investigations. Although lot of research has been done in cyber forensics, it is still expected to face new challenges in near future. Analysis of digital media specifically photographic images, audio and video recordings are very crucial in forensics This paper specifically focus on digital forensics. There are several methods for digital forensic analysis. Currently deep learning (DL), mainly convolutional neural network (CNN) has proved very promising in classification of digital images and sound analysis techniques. This paper presents a compendious study of recent research and methods in forensic areas based on CNN, with a view to guide the researchers working in this area. We first, defined and explained preliminary models of DL. In the next section, out of several DL models we have focused on CNN and its usage in areas of digital forensic. Finally, conclusion and future work are discussed. The review shows that CNN has proved good in most of the forensic domains and still promise to be better.
A Proactive Approach in Network Forensic Investigation ProcessEditor IJCATR
nformation Assurance and Security (IAS) is a crucial component in the corporate environment to ensure that the secrecy of
sensitive data is protected, the integrity of important data is not violated, and the availability of critical systems is guaranteed. The
advancement of Information communication and technology into a new era and domain such as mobility and Internet of Things,
its ever growing user’s base and sophisticated cyber-attacks forces the organizations to deploy automated and robust defense
mechanism to manage resultant digital security incidences in real time. Digital forensic is a scientific process that facilitates
detection of illegal activities and in-appropriate behaviors using scientific tools, techniques and investigation frameworks. This
research aims at identifying processes that facilitate and improves digital forensic investigation process. Existing digital forensic
framework will be reviewed and the analysis will be compiled toderive a network forensic investigation framework that include
evidence collection, preservation and analysis at a sensor level and in real time. It is aimed to discover complete relationship with
optimal performance among known and unseen/new alerts generated by multiple network sensors in order to improve the quality
of alert and recognize attack strategy
A SYSTEMATIC REVIEW ON MACHINE LEARNING INSIDER THREAT DETECTION MODELS, DATA...IJNSA Journal
Computers are crucial instruments providing a competitive edge to organizations that have adopted them. Their pervasive presence has presented a novel challenge to information security, specifically threats emanating from privileged employees. Various solutions have been tried to address the vice, but no exhaustive solution has been found. Due to their elusive nature, proactive strategies have been proposed of which detection using Machine Learning models has been favoured. The choice of algorithm, datasets and metrics are cornerstones of model performance and hence, need to be addressed. Although multiple studies on ML for insider threat detection have been done, none has provided a comprehensive analysis of algorithms, datasets and metrics for development of Insider Threat Detection models. This study conducts a comprehensive systematic literature review using reputable databases to answer the research questions posed. Search strings, inclusion and exclusion criteria were set for eligibility of articles published in the last decade.
Combating Cybersecurity Challenges with Advanced AnalyticsCognizant
Using an AI-powered analytics platform, IT organizations can shift from a reactive approach to security breaches, to proactively identifying increasingly sophisticated threat vectors and quickly resolving exploitable vulnerabilities.
Physical and Cyber Crime Detection using Digital Forensic Approach: A Complet...IJARIIT
Criminalization may be a general development that has significantly extended in previous few years. In
order, to create the activity of the work businesses easy, use of technology is important. Crime investigation analysis
is a section records in data mining plays a crucial role in terms of predicting and learning the criminals. In our
paper, we've got planned an incorporated version for physical crime as well as cybercrime analysis. Our approach
uses data mining techniques for crime detection and criminal identity for physical crimes and digitized forensic tools
(DFT) for evaluating cybercrimes. The presented tool named as Comparative Digital Forensic Process tool
(CDFPT) is entirely based on digital forensic model and its stages named as Comparative Digital Forensic Process
Model (CDFPM). The primary step includes accepting the case details, categorizing the crime case as physical crime
or cybercrime and sooner or later storing the data in particular databases. For physical crime analysis we've used kmeans
approach cluster set of rules to make crime clusters. The k-means method effects are a lot advantageous by the
utilization of GMAPI generation. This provides advanced and consumer-friendly visual-aid to k-means approach for
tracing the region of the crime. we have applied KNN for criminal identification with the
help of observing beyond crimes and finding similar ones that suit this crime, if no past document is discovered then
the new crime sample are introduced to the crime data-set. With the advancements of web, the network form has
become much more complicated and attacking methods are further more than that as well. For crime analysis
we're detecting the attacks executed on host system through an outsider the usage of
assorted digitized forensic tools to produce information security with the help of generating reports for an
event which could need any investigation. Our digitized technique aids the development of the society
by helping the investigation businesses to follow a custom-built investigative technique in crime analysis and criminal
identification as opposed to manually looking the database to analyze criminal activities, and as a
result facilitate them in combating crimes.
Enhancements in the world of digital forensicsIAESIJAI
Currently, the rapid advancement of computer systems and mobile phones has resulted in their utilization in unlawful acts. Ensuring adequate and effective security measures poses a difficult task due to the intricate nature of these devices, thereby exacerbating the challenges associated with investigating crimes involving them. Digital forensics, which involves investigating cyber crimes, plays a crucial role in this realm. Extensive research has been conducted in this field to aid forensic investigations in addressing contemporary obstacles. This paper aims to explore the progress made in the applications of digital forensics and security, encompassing various aspects, and provide insights into the evolution of digital forensics over the past five years.
Crime and violence are inherent in our political and social system. With the moving pace of technology, the
popularity of internet grows continuously, with not only changing our views of life, but also changing the
way crime takes place all over the world. We need a technology that can be used to bring justice to those
who are responsible for conducting attacks on computer systems across the globe. In this paper, we present
various measures being taken in order to control and deal with the crime related to digital devices. This
paper gives an insight of Digital Forensics and current situation of India in handling such type of crimes.
Review on effectiveness of deep learning approach in digital forensicsIJECEIAES
Cyber forensics is use of scientific methods for definite description of cybercrime activities. It deals with collecting, processing and interpreting digital evidence for cybercrime analysis. Cyber forensic analysis plays very important role in criminal investigations. Although lot of research has been done in cyber forensics, it is still expected to face new challenges in near future. Analysis of digital media specifically photographic images, audio and video recordings are very crucial in forensics This paper specifically focus on digital forensics. There are several methods for digital forensic analysis. Currently deep learning (DL), mainly convolutional neural network (CNN) has proved very promising in classification of digital images and sound analysis techniques. This paper presents a compendious study of recent research and methods in forensic areas based on CNN, with a view to guide the researchers working in this area. We first, defined and explained preliminary models of DL. In the next section, out of several DL models we have focused on CNN and its usage in areas of digital forensic. Finally, conclusion and future work are discussed. The review shows that CNN has proved good in most of the forensic domains and still promise to be better.
A Proactive Approach in Network Forensic Investigation ProcessEditor IJCATR
nformation Assurance and Security (IAS) is a crucial component in the corporate environment to ensure that the secrecy of
sensitive data is protected, the integrity of important data is not violated, and the availability of critical systems is guaranteed. The
advancement of Information communication and technology into a new era and domain such as mobility and Internet of Things,
its ever growing user’s base and sophisticated cyber-attacks forces the organizations to deploy automated and robust defense
mechanism to manage resultant digital security incidences in real time. Digital forensic is a scientific process that facilitates
detection of illegal activities and in-appropriate behaviors using scientific tools, techniques and investigation frameworks. This
research aims at identifying processes that facilitate and improves digital forensic investigation process. Existing digital forensic
framework will be reviewed and the analysis will be compiled toderive a network forensic investigation framework that include
evidence collection, preservation and analysis at a sensor level and in real time. It is aimed to discover complete relationship with
optimal performance among known and unseen/new alerts generated by multiple network sensors in order to improve the quality
of alert and recognize attack strategy
A SYSTEMATIC REVIEW ON MACHINE LEARNING INSIDER THREAT DETECTION MODELS, DATA...IJNSA Journal
Computers are crucial instruments providing a competitive edge to organizations that have adopted them. Their pervasive presence has presented a novel challenge to information security, specifically threats emanating from privileged employees. Various solutions have been tried to address the vice, but no exhaustive solution has been found. Due to their elusive nature, proactive strategies have been proposed of which detection using Machine Learning models has been favoured. The choice of algorithm, datasets and metrics are cornerstones of model performance and hence, need to be addressed. Although multiple studies on ML for insider threat detection have been done, none has provided a comprehensive analysis of algorithms, datasets and metrics for development of Insider Threat Detection models. This study conducts a comprehensive systematic literature review using reputable databases to answer the research questions posed. Search strings, inclusion and exclusion criteria were set for eligibility of articles published in the last decade.
Combating Cybersecurity Challenges with Advanced AnalyticsCognizant
Using an AI-powered analytics platform, IT organizations can shift from a reactive approach to security breaches, to proactively identifying increasingly sophisticated threat vectors and quickly resolving exploitable vulnerabilities.
Digital Footprints_ Investigating Digital Evidence in Online Crime Cases.pptxwebb00704
Have you ever stopped to consider the trail of breadcrumbs you leave behind every time you browse the internet? From social media posts to online purchases, your digital footprint is expanding with each click. But what if I told you that this seemingly harmless virtual path holds immense significance in solving online crime cases? In an era where cybercriminals are growing more sophisticated by the day, understanding the importance of digital footprints has become crucial for law enforcement agencies and individuals alike. Get ready to dive into a world where every keystroke could be a potential clue in unraveling complex web-based crimes.
Kathryn E. ScarboroughEastern Kentucky UniversityMarc Ro.docxtawnyataylor528
Kathryn E. Scarborough
Eastern Kentucky University
Marc Rogers
Purdue University
Kelli Frakes
Eastern Kentucky University
Cristina San Martin
Purdue University
KKaatthhrryynn EE.. SSccaarrbboorroouugghh, PPhh..DD.., professor at the Department of Safety, Security, and Emergency
Management at Eastern Kentucky University, earned her Ph.D. in criminal justice from Sam Houston State
University. She also has an MA in applied sociology with a certificate in women’s studies from Old
Dominion and Norfolk State Universities, and a BS in criminal justice from the University of Southern
Mississippi. Prior to her teaching at Eastern Kentucky University, she was a police officer in Portsmouth,
Virginia, a United States Navy Hospital Corpsman/Emergency Medical Technician, and a chemical depen-
dency technician. In addition to her faculty role, Dr. Scarborough is Director for Research, Evaluation and
Testing for the Justice and Safety Center. Her current teaching and research interests include criminal
investigation, law enforcement technology, cyber crime and security, and police administration.
In her role as director for research, testing and evaluation, she has oversight of more than
70 projects funded by the Department of Homeland Security, the National Institute of Justice/Office of
Science and Technology, the State of Kentucky, and the Department of Defense. She also serves as project
director or codirector of the following projects: National Study on Criminal Investigation, the Digital
Evidence Assessment of Local and State Law Enforcement Organizations, the Rural Cyber Crime
Response and Prevention Team project, Cyber PAAL, and the ASIS International Security Trends project.
MMaarrcc RRooggeerrss,, PPhh..DD.., CISSP, CCCI, is the Chair of the Cyber Forensics Program in the Department of
Computer and Information Technology at Purdue University. He is an associate professor and also a
research faculty member at the Center for Education and Research in Information Assurance and
Security (CERIAS). Dr. Rogers was a senior instructor for (ISC)2, the international body that certifies
information system security professionals (CISSP), is a member of the quality assurance board for
(ISC)2’s SCCP designation, and is Chair of the Law, Compliance and Investigation Domain of interna-
tional Common Body of Knowledge (CBK) committee. He is a former police detective who worked in
the area of fraud and computer crime investigations. Dr. Rogers sits on the editorial board for several
professional journals and is a member of various national and international committees focusing on dig-
ital forensic science and digital evidence. He is the author of numerous book chapters, and journal pub-
lications in the field of digital forensics and applied psychological analysis. His research interests
include applied cyber forensics, psychological digital crime scene analysis, and cyber terrorism.
Chapter 24
Digital Evidence
477
M24_SCHM8860_01_SE_C24.QXD 2/4/08 ...
Use of network forensic mechanisms to formulate network securityIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel interested in obtaining knowledge in securing communication devices/infrastructure. This research provides a framework that can be used in an organization to eliminate digital anomalies through network forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
USE OF NETWORK FORENSIC MECHANISMS TO FORMULATE NETWORK SECURITYIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel
interested in obtaining knowledge in securing communication devices/infrastructure. This research
provides a framework that can be used in an organization to eliminate digital anomalies through network
forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also
enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
National framework for digital forensics bangladesh context Bank Alfalah Limited
Bangladesh is a young and rapidly growing population is 160 million. According to BASIS 2012 survey the ICT industry is consistently growing 20% to 30% per year. Most of our IT investment focused on Financial, Telecomm and Government sector. Now a day we cannot think a day without Information Technology as we are living on Information Age. We are very quickly accustomed to keeping and using digital information. While we are keeping our processed data on different digital media, security is one of the key issues in contemporary computing and is relevant to a wide range of activities, including software development, networking and system. Some people will then take the advantages of these loosely coupled securities and involved in different crime. Our object in this project is to make a Digital Forensics Framework which will cover Policy, Standard and give a future Guideline for investigation and presentation to law and enforcement agency.
Contemporary Cyber Security Social Engineering Solutions, Measures, Policies,...CSCJournals
Social engineering is a major threat to organizations as more and more companies digitize operations and increase connectivity through the internet. After defining social engineering and the problems it presents, this study offers a critical review of existing protection measures, tools, and policies for organizations to combat cyber security social engineering. Through a systematic review of recent studies published on the subject, our analysis identifies the need to provide training for employees to ensure they understand the risks of social engineering and how best to avoid becoming a victim. Protection measures include awareness programs, training of non-technical staff members, new security networks, software usage, and security protocols to address social engineering threats.
Applications of artificial intelligence techniques to combating cyber crimes ...ijaia
With the advances in information technology (IT) criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be an effective tool for detection and prevention of cyber attacks, as well as to give the scope for future work.
Optimised malware detection in digital forensicsIJNSA Journal
On the Internet, malware is one of the most serious threats to system security. Most complex issues and
problems on any systems are caused by malware and spam. Networks and systems can be accessed and
compromised by malware known as botnets, which compromise other systems through a coordinated
attack. Such malware uses anti-forensic techniques to avoid detection and investigation. To prevent systems
from the malicious activity of this malware, a new framework is required that aims to develop an optimised
technique for malware detection. Hence, this paper demonstrates new approaches to perform malware
analysis in forensic investigations and discusses how such a framework may be developed.
DOES DIGITAL NATIVE STATUS IMPACT END-USER ANTIVIRUS USAGE?IJCNCJournal
Due to the increasingly online nature of business (e-commerce), it is essential to understand how end-users can be protected from malicious online activities such as malware. Several factors have been examined in the research on this topic. Digital native status was identified as a factor that has not been investigated thoroughly. This study examined how the security decision-making process is impacted by digital native status by looking at Protection Motivation Theory. Digital Native Status was investigated as a mediating factor in the PMT model. Intent to use antivirus was utilized as the protective measure. The findings indicate that digital native status does not mediate Fear. However, other factors, such as Fear, selfefficacy, and response efficacy, play a part in the intent to use antivirus. Conversely, the other constructs in the model, response-costs and maladaptive rewards, did not have a relationship with antivirus usage. Practically speaking, employers and eCommerce businesses could use these findings to identify factors that play into their end-user behaviors. These findings can be utilized to help guide training programs and professionals researching end-user behavior. These findings also suggest that future research should focus on factors other than age.
Digital Forensics Market, Size, Global Forecast 2023-2028Renub Research
Global Digital Forensics Market is forecasted to hit US$ 13.93 Billion by 2028, according to Renub Research. The modern world has witnessed an increased dependence on the latest digital technology. With the widespread adoption of the internet, smartphones, social media platforms like Facebook, Internet of Things (IoT), GPS, fitness trackers, and even smart cars, it has become increasingly difficult for digital forensics investigators to retrieve digital data.
SQL Vulnerability Prevention in Cybercrime using Dynamic Evaluation of Shell and Remote File Injection Attacks R. Ravi,
Department of Computer Science & Engineering,
Francis Xavier Engineering College, Tamil Nadu, India
Dr. Beulah Shekhar,
Department of Criminology,
Manonmanium Sundaranar University, Tamil Nadu, India
Running head: CRIME ANALYSIS 1
CRIME ANALYSIS TECHNOLOGY 2
Crime analysis is a function that usually involves the systemic analysis in identifying as well as analyzing the crime patterns and trends. Crime analysis is very important for law enforcement agencies as it helps law enforcers effectively deploy the available resources in a better and effective manner, which enables them to identify and apprehend suspects. Crime analysis is also very significant when it comes to arriving at solutions devised to come up with the right solution to solve the current crime problem and issues as well as coming up with the right prevention strategies. Since the year 2014, crime rates in the USA have increased steadily as per a study done by USAFacts, which is a non-partisan initiative (Osborne & Wernicke, 2013). With this increase in crime rates, which has majorly resulted in massive growth in technology, it is essential to come up with better means and ways of dealing with the increased crime rates. With the current advancement in technology, better law enforcement tools developed, which has enabled better crime deterrence in better and efficient ways. All this has been facilitated by the efforts of crime analysts who have come up with better tools and thus enabling the law enforcers to better deal with the crimes (Osborne & Wernicke, 2013). In this paper, I will consider the application of crime analysis technology and techniques in fighting crimes. Application of crime analysis technology and techniques used to make crime analysis more accurate and efficient.
Currently, the two technological tools that are used in predictive policing software have enabled security agencies to effectively use predictive policing ("Crime Analysis: Fighting Crime with Data," 2017). Application of this software has enabled better crime prevention as with data obtained in the previous crimes have been used to predict possible future severe crimes in a specific area.
Through the adoption and use of crime analysis, law enforcement agencies have been able to fight against crimes as when compared with the past effectively. The use of crime analysis comes at the right time, where there has been an increase in crime rates in the current digital error. In a survey done by Wynyard group in 2015, the study revealed that for every 10 law enforcement officials 9 of them believe that the use of current technology in crime analysis has had positive effects in helping the agencies in solving crimes as they can identify essential links and trends in crimes ("Crime Analysis: Fighting Crime with Data," 2017). In the same way, other sectors have benefited from data analysis with spreadsheets, databases, and mapping, law enforcers have been able to use data analysis to come up with a better decision. Crime analysis ha ...
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
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Digital Footprints_ Investigating Digital Evidence in Online Crime Cases.pptxwebb00704
Have you ever stopped to consider the trail of breadcrumbs you leave behind every time you browse the internet? From social media posts to online purchases, your digital footprint is expanding with each click. But what if I told you that this seemingly harmless virtual path holds immense significance in solving online crime cases? In an era where cybercriminals are growing more sophisticated by the day, understanding the importance of digital footprints has become crucial for law enforcement agencies and individuals alike. Get ready to dive into a world where every keystroke could be a potential clue in unraveling complex web-based crimes.
Kathryn E. ScarboroughEastern Kentucky UniversityMarc Ro.docxtawnyataylor528
Kathryn E. Scarborough
Eastern Kentucky University
Marc Rogers
Purdue University
Kelli Frakes
Eastern Kentucky University
Cristina San Martin
Purdue University
KKaatthhrryynn EE.. SSccaarrbboorroouugghh, PPhh..DD.., professor at the Department of Safety, Security, and Emergency
Management at Eastern Kentucky University, earned her Ph.D. in criminal justice from Sam Houston State
University. She also has an MA in applied sociology with a certificate in women’s studies from Old
Dominion and Norfolk State Universities, and a BS in criminal justice from the University of Southern
Mississippi. Prior to her teaching at Eastern Kentucky University, she was a police officer in Portsmouth,
Virginia, a United States Navy Hospital Corpsman/Emergency Medical Technician, and a chemical depen-
dency technician. In addition to her faculty role, Dr. Scarborough is Director for Research, Evaluation and
Testing for the Justice and Safety Center. Her current teaching and research interests include criminal
investigation, law enforcement technology, cyber crime and security, and police administration.
In her role as director for research, testing and evaluation, she has oversight of more than
70 projects funded by the Department of Homeland Security, the National Institute of Justice/Office of
Science and Technology, the State of Kentucky, and the Department of Defense. She also serves as project
director or codirector of the following projects: National Study on Criminal Investigation, the Digital
Evidence Assessment of Local and State Law Enforcement Organizations, the Rural Cyber Crime
Response and Prevention Team project, Cyber PAAL, and the ASIS International Security Trends project.
MMaarrcc RRooggeerrss,, PPhh..DD.., CISSP, CCCI, is the Chair of the Cyber Forensics Program in the Department of
Computer and Information Technology at Purdue University. He is an associate professor and also a
research faculty member at the Center for Education and Research in Information Assurance and
Security (CERIAS). Dr. Rogers was a senior instructor for (ISC)2, the international body that certifies
information system security professionals (CISSP), is a member of the quality assurance board for
(ISC)2’s SCCP designation, and is Chair of the Law, Compliance and Investigation Domain of interna-
tional Common Body of Knowledge (CBK) committee. He is a former police detective who worked in
the area of fraud and computer crime investigations. Dr. Rogers sits on the editorial board for several
professional journals and is a member of various national and international committees focusing on dig-
ital forensic science and digital evidence. He is the author of numerous book chapters, and journal pub-
lications in the field of digital forensics and applied psychological analysis. His research interests
include applied cyber forensics, psychological digital crime scene analysis, and cyber terrorism.
Chapter 24
Digital Evidence
477
M24_SCHM8860_01_SE_C24.QXD 2/4/08 ...
Use of network forensic mechanisms to formulate network securityIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel interested in obtaining knowledge in securing communication devices/infrastructure. This research provides a framework that can be used in an organization to eliminate digital anomalies through network forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
USE OF NETWORK FORENSIC MECHANISMS TO FORMULATE NETWORK SECURITYIJMIT JOURNAL
Network Forensics is fairly a new area of research which would be used after an intrusion in various
organizations ranging from small, mid-size private companies and government corporations to the defence
secretariat of a country. At the point of an investigation valuable information may be mishandled which
leads to difficulties in the examination and time wastage. Additionally the intruder could obliterate tracks
such as intrusion entry, vulnerabilities used in an entry, destruction caused, and most importantly the
identity of the intruder. The aim of this research was to map the correlation between network security and
network forensic mechanisms. There are three sub research questions that had been studied. Those have
identified Network Security issues, Network Forensic investigations used in an incident, and the use of
network forensics mechanisms to eliminate network security issues. Literature review has been the
research strategy used in order study the sub research questions discussed. Literature such as research
papers published in Journals, PhD Theses, ISO standards, and other official research papers have been
evaluated and have been the base of this research. The deliverables or the output of this research was
produced as a report on how network forensics has assisted in aligning network security in case of an
intrusion. This research has not been specific to an organization but has given a general overview about
the industry. Embedding Digital Forensics Framework, Network Forensic Development Life Cycle, and
Enhanced Network Forensic Cycle could be used to develop a secure network. Through the mentioned
framework, and cycles the author has recommended implementing the 4R Strategy (Resistance,
Recognition, Recovery, Redress) with the assistance of a number of tools. This research would be of
interest to Network Administrators, Network Managers, Network Security personnel, and other personnel
interested in obtaining knowledge in securing communication devices/infrastructure. This research
provides a framework that can be used in an organization to eliminate digital anomalies through network
forensics, helps the above mentioned persons to prepare infrastructure readiness for threats and also
enables further research to be carried on in the fields of computer, database, mobile, video, and audio.
National framework for digital forensics bangladesh context Bank Alfalah Limited
Bangladesh is a young and rapidly growing population is 160 million. According to BASIS 2012 survey the ICT industry is consistently growing 20% to 30% per year. Most of our IT investment focused on Financial, Telecomm and Government sector. Now a day we cannot think a day without Information Technology as we are living on Information Age. We are very quickly accustomed to keeping and using digital information. While we are keeping our processed data on different digital media, security is one of the key issues in contemporary computing and is relevant to a wide range of activities, including software development, networking and system. Some people will then take the advantages of these loosely coupled securities and involved in different crime. Our object in this project is to make a Digital Forensics Framework which will cover Policy, Standard and give a future Guideline for investigation and presentation to law and enforcement agency.
Contemporary Cyber Security Social Engineering Solutions, Measures, Policies,...CSCJournals
Social engineering is a major threat to organizations as more and more companies digitize operations and increase connectivity through the internet. After defining social engineering and the problems it presents, this study offers a critical review of existing protection measures, tools, and policies for organizations to combat cyber security social engineering. Through a systematic review of recent studies published on the subject, our analysis identifies the need to provide training for employees to ensure they understand the risks of social engineering and how best to avoid becoming a victim. Protection measures include awareness programs, training of non-technical staff members, new security networks, software usage, and security protocols to address social engineering threats.
Applications of artificial intelligence techniques to combating cyber crimes ...ijaia
With the advances in information technology (IT) criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be an effective tool for detection and prevention of cyber attacks, as well as to give the scope for future work.
Optimised malware detection in digital forensicsIJNSA Journal
On the Internet, malware is one of the most serious threats to system security. Most complex issues and
problems on any systems are caused by malware and spam. Networks and systems can be accessed and
compromised by malware known as botnets, which compromise other systems through a coordinated
attack. Such malware uses anti-forensic techniques to avoid detection and investigation. To prevent systems
from the malicious activity of this malware, a new framework is required that aims to develop an optimised
technique for malware detection. Hence, this paper demonstrates new approaches to perform malware
analysis in forensic investigations and discusses how such a framework may be developed.
DOES DIGITAL NATIVE STATUS IMPACT END-USER ANTIVIRUS USAGE?IJCNCJournal
Due to the increasingly online nature of business (e-commerce), it is essential to understand how end-users can be protected from malicious online activities such as malware. Several factors have been examined in the research on this topic. Digital native status was identified as a factor that has not been investigated thoroughly. This study examined how the security decision-making process is impacted by digital native status by looking at Protection Motivation Theory. Digital Native Status was investigated as a mediating factor in the PMT model. Intent to use antivirus was utilized as the protective measure. The findings indicate that digital native status does not mediate Fear. However, other factors, such as Fear, selfefficacy, and response efficacy, play a part in the intent to use antivirus. Conversely, the other constructs in the model, response-costs and maladaptive rewards, did not have a relationship with antivirus usage. Practically speaking, employers and eCommerce businesses could use these findings to identify factors that play into their end-user behaviors. These findings can be utilized to help guide training programs and professionals researching end-user behavior. These findings also suggest that future research should focus on factors other than age.
Digital Forensics Market, Size, Global Forecast 2023-2028Renub Research
Global Digital Forensics Market is forecasted to hit US$ 13.93 Billion by 2028, according to Renub Research. The modern world has witnessed an increased dependence on the latest digital technology. With the widespread adoption of the internet, smartphones, social media platforms like Facebook, Internet of Things (IoT), GPS, fitness trackers, and even smart cars, it has become increasingly difficult for digital forensics investigators to retrieve digital data.
SQL Vulnerability Prevention in Cybercrime using Dynamic Evaluation of Shell and Remote File Injection Attacks R. Ravi,
Department of Computer Science & Engineering,
Francis Xavier Engineering College, Tamil Nadu, India
Dr. Beulah Shekhar,
Department of Criminology,
Manonmanium Sundaranar University, Tamil Nadu, India
Running head: CRIME ANALYSIS 1
CRIME ANALYSIS TECHNOLOGY 2
Crime analysis is a function that usually involves the systemic analysis in identifying as well as analyzing the crime patterns and trends. Crime analysis is very important for law enforcement agencies as it helps law enforcers effectively deploy the available resources in a better and effective manner, which enables them to identify and apprehend suspects. Crime analysis is also very significant when it comes to arriving at solutions devised to come up with the right solution to solve the current crime problem and issues as well as coming up with the right prevention strategies. Since the year 2014, crime rates in the USA have increased steadily as per a study done by USAFacts, which is a non-partisan initiative (Osborne & Wernicke, 2013). With this increase in crime rates, which has majorly resulted in massive growth in technology, it is essential to come up with better means and ways of dealing with the increased crime rates. With the current advancement in technology, better law enforcement tools developed, which has enabled better crime deterrence in better and efficient ways. All this has been facilitated by the efforts of crime analysts who have come up with better tools and thus enabling the law enforcers to better deal with the crimes (Osborne & Wernicke, 2013). In this paper, I will consider the application of crime analysis technology and techniques in fighting crimes. Application of crime analysis technology and techniques used to make crime analysis more accurate and efficient.
Currently, the two technological tools that are used in predictive policing software have enabled security agencies to effectively use predictive policing ("Crime Analysis: Fighting Crime with Data," 2017). Application of this software has enabled better crime prevention as with data obtained in the previous crimes have been used to predict possible future severe crimes in a specific area.
Through the adoption and use of crime analysis, law enforcement agencies have been able to fight against crimes as when compared with the past effectively. The use of crime analysis comes at the right time, where there has been an increase in crime rates in the current digital error. In a survey done by Wynyard group in 2015, the study revealed that for every 10 law enforcement officials 9 of them believe that the use of current technology in crime analysis has had positive effects in helping the agencies in solving crimes as they can identify essential links and trends in crimes ("Crime Analysis: Fighting Crime with Data," 2017). In the same way, other sectors have benefited from data analysis with spreadsheets, databases, and mapping, law enforcers have been able to use data analysis to come up with a better decision. Crime analysis ha ...
Similar to Behavioural Analytics in Cyber Security for Digital Forensics Application (20)
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Welcome to AIRCC's International Journal of Computer Science and Information Technology (IJCSIT), your gateway to the latest advancements in the dynamic fields of Computer Science and Information Systems.
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the
context of text understanding. We begin by describing the architecture and training process of GPT-3, and
provide an overview of its impressive performance across a wide range of natural language processing
tasks, such as language translation, question-answering, and text completion. Throughout this research
project, a summarizing tool was also created to help us retrieve content from any types of document,
specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the
summarizing, as well as question-answering capabilities of GPT-3 (0) via long text
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This paper describes the outcome of an attempt to implement the same transitive closure (TC) algorithm
for Apache MapReduce running on different Apache Hadoop distributions. Apache MapReduce is a
software framework used with Apache Hadoop, which has become the de facto standard platform for
processing and storing large amounts of data in a distributed computing environment. The research
presented here focuses on the variations observed among the results of an efficient iterative transitive
closure algorithm when run against different distributed environments. The results from these comparisons
were validated against the benchmark results from OYSTER, an open source Entity Resolution system. The
experiment results highlighted the inconsistencies that can occur when using the same codebase with
different implementations of Map Reduce.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Behavioural Analytics in Cyber Security for Digital Forensics Application
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 15, No 1, February 2023
DOI: 10.5121/ijcsit.2023.15106 83
BEHAVIOURAL ANALYTICS IN CYBER SECURITY
FOR DIGITAL FORENSICS APPLICATION
Martin Luther Bwangah
School of Science, Engineering & Technology, Kabarak University, Nakuru, Kenya
ABSTRACT
The paper emphasizes the human aspects of cyber incidents concerning protecting information and
technology assets by addressing behavioral analytics in cybersecurity for digital forensics applications.
The paper demonstrates the human vulnerabilities associated with information systems technologies and
components. This assessment is based on past literature assessments done in this area. This study also
includes analyses of various frameworks that have led to the adoption of behavioral analysis in digital
forensics. The study's findings indicate that behavioral evidence analysis should be included as part of the
digital forensics examination. The provision of standardized investigation methods and the inclusion of
human factors such as motives and behavioral tendencies are some of the factors attached to the use of
behavioral digital forensic frameworks. However, the study also appreciates the need for a more
generalizable digital forensic method.
KEYWORDS
Digital Forensics, Human Vulnerabilities, Social Engineering, Criminal Profiling, Behavioral Analytics
1. INTRODUCTION
Data and information are among the most vital assets in any modern organization. Human,
organizational, and technological aspects play a central consolidative role in information security
and digital forensics in safeguarding these important assets. However, the security and integrity
of such assets is increasingly threatened by malicious cyberspace users. Even with the adoption
of proactive stop-gap measures, the rise in cybercrime has led to significant losses. An
assessment of the 2020 Information Systems Audit and Control Association’s (ISACA) annual
report on the state of cyber security provided an insight into the increasing threat of cybercrime
[1]. This report used insight from 2,000 information security experts across seventeen industries,
to investigate the cybersecurity landscape. The report concluded that cyberattacks have been on
the increase year over year since 2010 [1]. The report also revealed that the threat actors were
divided as follows, external cybercriminals (22%,) malicious insiders at (11%,) non-malicious
insiders at (10 %) followed by state actors (9 %) then hacktivists at 8%. In the report, the most
prevalent attack techniques used were social engineering which stood at 15%, followed by
advanced persistent threat at 10%, and subsequently ransomware and unpatched systems at 9%
each [1].
The Finance Online Research Center 2022/2023, which reported on 10 cyber security predictions,
recognized that cybercrime was the fastest-growing crime globally. Notably, the financial losses
suffered by organizations outnumber overall income in the international illegal drug trade [2].
Unfortunately, these attacks also target small enterprises that lack sufficient cyber security
capacity to protect themselves. This report also identified the common cyber-attack method
facing companies based in the United States. The threats included phishing at 38%, network
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 15, No 1, February 2023
84
intrusion at 32%, inadvertent disclosure at 12%, theft and loss of devices and records at 8%, and
system misconfiguration at 5% [2].
Based on the two reports, it is apparent that social engineering attacks based on phishing are a
growing threat. The threat involves system intruders targeting employees who connect to their
employer’s network remotely from home or away from the office. The hackers use manipulation
that exploits human error to gain private information, access, or valuables with the intent to use
such information against the employee. Such attacks have resulted in huge losses which have
shifted focus towards identifying criminal behaviors instead of simply focusing on physical and
device security alone.
The study of behavioral tendencies is informed by the fact that most cybercriminal activities are
grounded on certain patterns, especially social engineering. This paper proposes the combined
use of digital forensics and behavioral analytics to create a digital forensic profiling framework
for analyzing evidence. The framework should provide a definitive criminal profile to identify
cybercriminals and stop them before they commit further crimes.
1.1. Problem Statement
Specialists in digital forensics have been experiencing unforeseen difficulties because
cybercriminals are increasingly using innovative and sophisticated techniques to commit crimes.
In many cases, such as social engineering attacks, the evidence is often not enough to minimize
the list of possible suspects. These challenges can be solved with a combination of digital
forensic processes that include focusing on the criminal's behavior in addition to the conventional
analysis process. However, even the addition of human behavior as a factor requires a proper
framework that can be used uniformly and effectively.
1.2. Background to the Study
The increased use of digital services across almost all social, economic, and regulatory speeches
has made computers a predominant part of human life. However, the same increased use of
digital devices has resulted in increased cases of cybercrime activities. As a result, law
enforcement and judicial authorities are facing increasing pressure to adopt proactive means of
including digital ways of collecting and analyzing evidence in both the physical and cyber
spheres. This study acknowledges the shortcomings of past digital forensic and evidence-
collection mechanisms. Most of the digital frameworks identified so far failed to acknowledge
the strengths of previous frameworks. As such, it has been hard to have a unified digital forensic
methodology that would draw consensus among architects of previous frameworks. This
assessment sought to collate a comprehensive review of digital forensic framework proposals that
are available to the public. It also sought to delineate between those frameworks that have a
behavioral evidence analysis aspect and those that lack the same.
1.3. Study Objectives
This study sought to: (i) explore the application of behavioral analytics in digital forensics; (ii)
explore the existing behavioral evidence analysis framework to establish their strengths and
weaknesses.
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2. LITERATURE REVIEW
This section provides an assessment of the literature relating to the primary objectives outlined in
the introduction section of this research paper. The literature review also covers the concepts of
behavioral analytics, cyber security challenges, digital transformation, and the adoption of digital
forensics as a solution to emergent cybersecurity challenges. Finally, the assessed literature also
addresses the use of digital forensic frameworks for investigations and as a barrier to cybercrime.
2.1. Cybersecurity Challenges in Digitally Dynamic Organizations
Cybersecurity is a growing global concern for personal digital device users, businesses, and state
agencies. The cybercrime space has been evolving fast, with the adoption of new digital
technologies and practices such as the internet of things and remote work. In a world where most
aspects of life are becoming digitalized, one of the greatest difficulties in the field of
cybersecurity is guaranteeing the safety of data [3]. However, the aspect of human beings as
Information Technology system operators has remained constant. Social engineering, which
provides an actual link between criminals and their targets, has also become a prevalent problem
due to the operational position held by legitimate system users. Spear phishing and spoofing often
serve as the initial vector for intrusive attacks against organizations and individual victims of
cybercrime.
2.2. Digital Forensics
In most cases, cybercrime scenes tend to be online or have a digital dimension that requires
expert analysis leading to the need for digital forensic analysis. Notably, digital forensics assists
authorities in forensically and methodically determining when an event happened, when it
occurred, where it transpired, why it ended up happening, and, ideally, who is responsible. Such
data is required to certify that the evidence discovered is adequate to indict a person for the
unlawful offense perpetrated [4]. All this information is needed to guarantee that there is enough
evidence to prosecute and convict a cybercriminal. Digital forensics (DF) is a sub-field of
forensic science that focuses on the study of the digital environment. DF, like any other forensic
investigation, employs scientific procedures to discover evidence. The primary purpose of DF is
to ensure evidence gathered in the investigation is credible and admissible before the court of
law[5].
2.3. Behavioral Analytics
Behavioral analytics is a concept that employs principles such as motive, mode of operation,
signature behavioral patterns, offender schemas, and victim personas to better probe criminal
activity [6]. It is worth stating that hard data is the bedrock of behavioral analytics. Behavioral
analytics is a subfield of data analytics concerned with gaining insight into the activities of
individuals [6]. Initially oriented towards violent offenders, behavioral analytics has been
expanded to cover other aspects of criminology. This field utilizes vast amounts of raw data
collected from various platforms and devices including social media, gaming apps, retail
websites, and apps [7]. The information is gathered, processed, and then utilized as the basis for
making choices, such as how to predict future criminal trends. Behavioral analytics may support
a variety of assumptions. The assumptions make iterative testing and assessment a key
component of this field.
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2.4. The Relationship between Digital Forensics, Criminal Profiling, and Behavioral
Analytics
In the field of digital forensics, behavioral analytics involves the logical investigation method that
looks at evidentiary material from a particular event and focuses on specific personality and
behavioral patterns to figure out what the probable offender is like. Notably, Behavioral evidence
analytics (BEA) practice includes four sets of assessments (Figure 1) including equivocal
forensic analysis [8], forensic victimology [9], identification of crime scene characteristics (10],
and determination of criminal tendencies [8], [11]. These four categories are used to arrive at a
comprehensive methodology for investigating crime.
Figure 1. Digital forensic assessment areas
Criminal profiling involves figuring out what kind of an individual or a group of suspects are by
using the actions they take while committing a crime(s) [11]. Cybercriminals often have unique
goals and motivating factors that form a pattern just like criminals in the physical world. Profiling
in digital forensics can be used to identify such patterns, and more investigators are choosing to
adopt the same [12]. Furthermore, the overall set of crime investigation processes is often similar
to those used in a traditional crime investigation, such as what drove the criminal or why they
chose an individual target.
3. DIGITAL FRAMEWORKS
One of the earliest digital forensics frameworks was the US Department of Justice’s Digital
Forensics Investigation Process Model [13]. This model was a fours stage model consisting of
securing and analyzing the incident, recording the incident, collecting evidence, as well as
packing, transporting, and organizing digital evidence. A 2002 article introduced a new
framework to standardize the DF process, but the seven processes proved too general for proper
use [14]. An Integrated Digital Investigation Process consisting of (1) preparation, (2)
distribution, (3) physical crime scene examination, (4) digital crime event investigation, and (5)
appraisal; was introduced by [15].
Subsequently, a two-tiered model was created to cover primary crime and physical crime scenes
distinctly in 2004 [16]. A six-step framework that was aimed at incorporating specificity and
practicality in the investigative process followed the 2004 model [17]. The six-step model was
woven around preparation, incident response, data collection, analysis, presentation of findings,
and incident closure. A minor adjustment that sought to address the legal challenge in the digital
evidence analysis process by adding attribution and reconstruction was incorporated into a 2010
model [18]. A 2010 research article proposed the systematic digital forensic investigation model
that included eleven phases. The eleven phases included scene preparation, scene lockdown,
survey and identification, scene recording, communication blocking, evidence collecting,
preservation, inspection, analysis, presentation, and outcome [19].
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A 12-step harmonized model that covered both traditional and digital forensic concepts was
proposed in 2012 [20]. The steps within this assessment included the identification of incidents,
initial response, planning, preparedness, documenting of the event location, and identification of
possible evidence. It also involved the gathering of prospective evidence, conveyance of potential
evidence, storage of potential evidence, examination of potential evidence, presenting, and result
cataloging. While noting that previous frameworks failed to incorporate the practical needs of
digital forensic investigators, several researchers proposed the use of an eight-step process that
incorporated preparation, identification, incident response, evidence gathering, evaluation,
analysis, presentation of information, and closure [21].
All of the frameworks above lacked the inclusion of behavioral aspects in the forensic analysis
process. A consequent analysis of previous structures developed a framework tailored toward
cyberstalking cases that included aspects of behavioral evidence analysis [22]. This model was
broken down into detection and complaint, examination and evaluation. A 2015 assessment
provided an alternative BA-focused approach of dealing with sexual crimes that involved six
steps beginning with the categorization of cases, contextual analysis, collecting of data, statistical
evaluation, chronological analysis, and visualization, as well as decision-making and expert
opinion [23]. A more comprehensive analysis [8] combined the concept in [22] with [23] to
develop a four-step process consisting of review, recognition and gathering, examination and
analysis as well as assessment and presentation. Table 1 below provides a tabulated breakdown of
the digital forensic frameworks.
Table 1. Digital forensic framework proposals through the years.
Author(s) Year Constituent variables
Federal Bureau of
Investigation [13]
2001 (1) Securing and analyzing the incident, (2) recording the
incident, (3) collecting evidence, (4) secure packing and
transporting of evidence, (5) organizing digital evidence
Reith, Carr, andGunsch
[15]
2002 (1) Preparation of evidence, (2) distribution, (3) physical
crime scene examination, (4) digital crime event
investigation, and (5) appraisal.
Baryamureeba and
Tushabe [16]
2004 (1) Preparation, (2) incident response, (3) data collection,
(4) analysis, (5) presentation of findings, (6) incident
closure.
Beebe and Clark [17] 2010 (1) Crime scene preparation, (2) scene lockdown, (3)
survey and identification, (4) scene recording, (5)
communication blocking, (6) evidence collecting, (7)
preservation, (8) inspection, (9) analysis, (10)
presentation, (11) outcome.
Valjarevic and Venter
[20]
2012 (1) Identification of incidents, (2) initial response, (3)
planning, (4) preparedness, (5) documenting of the event
location, (6) identification of possible evidence (7)
gathering of prospective evidence, (8) conveyance of
potential evidence, (9) storage of potential evidence, (10)
examination of potential evidence, (11) presenting, (12)
result cataloguing
Silde and Angelopoulou
[21]
2014 (1) Detection and complaint, (2) examination and
evaluation
Montasari, Peltola and
Evans [22]
2015 (1) Preparation, (2) identification, (3) incident response,
(4)evidence gathering, (5)evaluation, (6) analysis, (7)
presentation of information, (8) closure
Rogers and Seigfried [23] 2016 (1) Categorization of cases, (2) contextual analysis, (3)
collecting of data, (4) statistical evaluation, (4)
chronological analysis, (5) visualization
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4. RESEARCH METHODOLOGY
This qualitative content analysis study looked at academic peer-reviewed scholarly academic
journals, theses, and doctoral dissertations authored or presented between 2001 and 2021 that
addressed digital forensics and behavioral analytics. Content analysis has been defined as the
impartial, methodical, qualitative research of a document's features [24]. The sources were TW
Universal academic database as well as ProQuest Dissertation. TW Universal and ProQuest were
used because they provided access to comprehensive academic directories with a large range of
full-text academic journals, dissertations, and theses.
5. FINDINGS
Up until 2014, none of the existing frameworks were tested in practical situations. The theories
and methods that went into making them were not tested in the real world. Models that
outlined the steps used did so with made-up examples and scant information that lacked clarity
over how the steps were used. Also, the models that explained these different phases concentrated
on what needed to be done during each phase, but they did not give enough information about
how to carry out the inquiry. Until 2014, the frameworks didn't take into consideration the
individuals engaged in the DF investigation. They also did not consider the behavioral,
motivational, or social aspects of criminal behavior that could help find possible evidence during
investigations. Critically, each framework is built upon the failures of the preceding frameworks.
Based on the assessment of the various frameworks it was clear that the use of BA in digital
crimes may help the investigative process in a variety of ways. Specifically, the use of BA offers
a methodical strategy for directing investigators to possible sources of forensic evidence in the
analyzed devices. It also gives information on individual offender traits and behaviors, which
may help with risk assessment. A key benefit of BA inclusion into the analysis process was the
adoption of methodologies that could and were applied in the field. Additionally, the frameworks
covered from 2014 onwards had a sense of standardization and were much simpler in comparison
to those used before them. The disadvantage of behavioral digital forensic frameworks is their
specificity to crime categories. For instance, while [23] and [8] dealt with sexual crimes, the
framework in [22] was constrained to cyberstalking.
6. RECOMMENDATION
This research has provided a review of the major digital frameworks provided thus far. The paper
has also shown how the inclusion of behavioral evidence analysis has revolutionized the
composition of digital forensic frameworks. However, most of the frameworks have remained
untested beyond the proposal. Future researchers on the subject should focus on proving the
efficacy of some of the frameworks, even if such an assessment will begin in the post-behavioral
analysis age.
7. CONCLUSION
The growing complexity and power of digital technologies have made it vital to keep an eye on
how cyber techniques are used to deter exploitation. The methodologies used to deal with online
crimes must also change to keep up with the adoption of new digital skills. Because of this,
digital forensics has needed improvement. When Behavioral Evidence Analysis is added to the
digital forensic processes, it makes it easier to solve digitally facilitated crimes and provide future
preventive as well as detective mechanisms in behavioral evidence. The suggested BEA model,
on the other hand, aims to create a standardized approach that can be employed in all criminal
cases. This paper details how well BEA works and spells out how to use it in the digital forensic
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process. By tracing the development of current digital investigation frameworks, this paper
establishes the importance of behavioral analytics in the digital investigation process.
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AUTHOR
Martin Luther Bwangah is a cybersecurity specialist and scholar with over 20 years
of experience in cybercrime investigations. He holds a BSc. In Information,
Technology, and Communication from Maseno University and an MSc. in Data
Communication (Computer Networks and Emerging Technologies) from KCA
University. He is currently pursuing a doctorate in IT Security and Audit at Kabarak
University. Mr. Bwangah works at the Kenya Anti-Counterfeit Authority as a regional
head in charge of online intelligence and investigations. He also teaches cybercrime
and computer forensics at the United States International University (Kenya) and KCA University. He
previously worked in the cyber Crime division of the Kenya National Police service, which he headed for
three years.