Mobile Forensics: Advances, Challenges, and Research Opportunities

Chernyshev, Maxim; Zeadally, Sherali; Baig, Zubair A.; Woodward, Andrew

doi:10.1109/msp.2017.4251107

Cited by 35 publications

(42 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, the nature of smartphones consists of aspects that are not available on typical computing systems, such as desktop and laptop computers. The heterogeneity of smartphones in use from various vendors with a diverse set of hardware and software configurations make the development of forensic tools a challenging task [5]. In such dynamic environments, the application of artificial intelligence (AI) facilitates the resilience to adapt to rapidly changing requirements.…”

Section: Discussionmentioning

confidence: 99%

“…However, modern smartphones use strong user authentication mechanisms such as PIN codes, log-in patterns, and biometrics, such as fingerprint and facial recognition. Furthermore, the sheer diversity of makes and models currently in the smartphone market causes difficulty in following a unified approach to perform live analysis on smartphones in investigations [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Forensic Insights From Smartphones Through Electromagnetic Side-Channel Analysis

Sayakkara

Le-Khac

2021

IEEE Access

View full text Add to dashboard Cite

The increasing use of smartphones has increased their presence in legal and corporate investigations. Unlike desktop and laptop computers, forensic analysis of smartphones is a challenging task due to their limited interfaces to retrieve information of forensic value. Electromagnetic side-channel analysis (EM-SCA) has been recently proposed as an alternative window to acquire forensic insights from computers, in particularly from Internet of Things devices. Along this line, this work experimentally evaluates the potential of extracting information of forensic value from smartphones through their EM radiation. Initially, a group of smartphones representing a diverse set of system-on-chip (SoC) processors were used to acquire EM radiation traces. Later, deep learning models were trained to detect various internal software behaviours running on the SoCs. The results of this work indicates that a wide variety of insights can be extracted from smartphones through EM side-channel, increasing the potential opportunities for digital forensic investigators.INDEX TERMS Digital forensics, smartphone forensics, electromagnetic side-channel, software behaviour detection, deep learning model.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Forensic Insights From Smartphones Through Electromagnetic Side-Channel Analysis

Sayakkara

Le-Khac

2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Data from mobile devices must be extracted during investigations. There are five levels of data extraction: manual, logical, hex dumps, chip-offs, and micro reads [5]. Each of these options allow investigators to gather different information from different areas of the device with varying levels of complexity.…”

Section: Data Extractionmentioning

confidence: 99%

Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions

Horan

Saiedian

2021

JCP

View full text Add to dashboard Cite

As technology has become pivotal a part of life, it has also become a part of criminal life. Criminals use new technology developments to commit crimes, and investigators must adapt to these changes. Many people have, and will become, victims of cybercrime, making it even more important for investigators to understand current methods used in cyber investigations. The two general categories of cyber investigations are digital forensics and open-source intelligence. Cyber investigations are affecting more than just the investigators. They must determine what tools they need to use based on the information that the tools provide and how effectively the tools and methods work. Tools are any application or device used by investigators, while methods are the process or technique of using a tool. This survey compares the most common methods available to investigators to determine what kind of evidence the methods provide, and which of them are the most effective. To accomplish this, the survey establishes criteria for comparison and conducts an analysis of the tools in both mobile digital forensic and open-source intelligence investigations. We found that there is no single tool or method that can gather all the evidence that investigators require. Many of the tools must be combined to be most effective. However, there are some tools that are more useful than others. Out of all the methods used in mobile digital forensics, logical extraction and hex dumps are the most effective and least likely to cause damage to the data. Among those tools used in open-source intelligence, natural language processing has more applications and uses than any of the other options.

show abstract

“…In the network score‐based algorithm, 29 various network factors are considered for the best network selection of the MN during handover. Finally, the cybercriminal activities of mobile devices and secure data utilization in Internet of things (IoT) left an important research issues 30,31 in future communication. The overall comparison of existing vertical handover algorithms is summarized in Table 2.…”

Section: Literature Surveymentioning

confidence: 99%

Optimized seamless handover scheme with information and decision server‐assisted partially distributed mobility management in heterogeneous 5th generation wireless networks

Parasuraman

Rajaraman

2021

Int J Communication

View full text Add to dashboard Cite

Summary Existing mobile network architectures are flatter and employ a centralized mobility management (CMM) scheme, where the entire intelligence is focused on the single‐end, which leads to low scalability, lack of dynamic mobility support, suboptimal routing, and insufficiency to support large volumes of data. The fifth‐generation (5G) networks demand high‐speed seamless connections to the best‐connected network irrespective of user position and connectivity. Further, seamless handover has to be carried out between wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), universal mobile telecommunication system (UMTS), and long‐term evolution (LTE). This paper aims to propose a distributed mobility management (DMM) solution in order to bring the mobility anchor point nearer to the mobile node (MN) to support the acceptable quality of service (QoS) and quality of experience (QoE) provision to end users. An information and decision server (IDS)‐based partial DMM scheme (IDS‐PDMM) is suggested to support optimized handover in internet protocol (IP)‐based heterogeneous architecture. The IDS estimates the nearest candidate network for MN during handover and thus provides a seamless connection for delay‐sensitive applications. The performance of the presented approach is compared with the existing CMM scheme and the simulation results prove that the IDS‐PDMM efficiently minimizes the handover delay and packet loss rate with guaranteed QoS provision.

show abstract

Mobile Forensics: Advances, Challenges, and Research Opportunities

Cited by 35 publications

References 14 publications

Forensic Insights From Smartphones Through Electromagnetic Side-Channel Analysis

Forensic Insights From Smartphones Through Electromagnetic Side-Channel Analysis

Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions

Optimized seamless handover scheme with information and decision server‐assisted partially distributed mobility management in heterogeneous 5th generation wireless networks

Contact Info

Product

Resources

About