Security, Privacy, Forensics Analysis for Smartphones

Security, Privacy, Forensics Analysis for Smartphones

Monika Arora (The NorthCap University, India) and Yogita Gigras (The Northcap University, India)
DOI: 10.4018/978-1-5225-9554-0.ch001
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The number of mobile phone users has increased exponentially in the past decade. In India itself, it has crossed to over 1.2 billion mobile phone users, with at least 45% being the smartphone users, and this number is growing by the day. Almost 75% of internet traffic is generated by Smartphone users, traffic growth is irrespective of the demography of users. In this chapter, the focus is on two main categories of users (i.e., adolescents and senior citizens), who are not very tech-savvy. It discusses the threat they face even in normal usage of smartphones, and how digital forensics shall provide a secure environment without compromising much on ease of usage. Android apps are prone to attacks by hackers as basic information shared by a user on social media turns out to be very lucrative information for intruders. This chapter discusses some of the methods adopted by digital forensic experts to deal with such cybercrimes, the software/hardware tools present in a smartphone, and what preventive steps shall be taken by users to safeguard themselves against cybercrimes.
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Smartphone has entirely changed the way a person deals with society. The smartphone is equipped with a different application, i.e. Healthcare tracker, location tracker, food habits, diets, and the daily routine etc. Due to the sensitivity of data stored in the phone, here privacy and security require an essential consideration. In recent years Android (Banuri, Alam, Khan, Manzoor, & Ali, 2012) and iPhone (Damopoulos, Kambourakis, Anagnostopoulos, Gritzalis & Park, 2013) are dominating the market. Every smartphone is equipped with sensors and vulnerabilities that lead to leakage of sensitive information which should be patched regularly to maintain privacy.

Some smartphones (Loaded with Previous Versions of Android as Nougat and Earlier) are installed with zero permission sensors, which can be activated without the knowledge of the user and inside have an exploit or malware that leads to a security breach. Also, there are certain games as Pokémon Go etc. which works on WI-FI and keeps track of a geographical area where the person is moving. It can be a threat to personal security and privacy as it receives user behavioral information, usage time, and geographical area (geolocation). Shrivastava & Kumar, (2017), in their previous work, discusses that the cyber forensics is concrete to see computerized media with a point of difference, security, investigation and display of the realities about advanced data.

Sharma & Gupta, (2018) discusses the increased usage of smartphone devices connected via WIFI, thereby vulnerable to frequent attacks. Different Smartphone vulnerabilities and different security challenges are discussed with the usage of the internet and ways to deal against Distributed Denial of Service (DDoS) attack.

Sharma, & Gupta, (2016) discuss in their research about designing a three-tier security model for detecting, defending against different malware attacks in the Accessing point and network traffic. The model is considering the system to grant permission for WI-FI access. Shrivastava et al., (2016) have proposed different forensics analysis tools on Networks, which enhances security by recording all the evidence and documenting evidence. Intrusion can be detected using the Honeypot tool has been discussed. (Singh, & Sharma, 2016) discusses the proposed tools and architecture to increase network security.

Sharma & Gupta, (2018) discuss the poor access control policies of the Android operating system. The clear picture of the access control policies and their vulnerabilities are highlighted. The mentioned paper also discusses the defending measures against similar attacks. This paper illustrates various incidents about Denial of Service attacks and Distributed Denial of Service attacks in a distributed system with the measures to defend against various attacks. Sharma & Gupta, (2019) highlights the key points of the Android-based smartphone, like the fact that access to download applications is not monitored. In this article, authors have used Machine Learning technology to identify malware activities and various exploits.

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