International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 05 | May -2017
p-ISSN: 2395-0072
www.irjet.net
Review of Malware Data Classification and Detection in Smart Devices Sandeep Sharma
Shrish Dixit
Babita Pathik
Dept. of CS & Engineering LNCTE, Bhopal (M.P.) ssharma1886@gmail.com
Dept. of CS & Engineering Dept. of CS & Engineering LNCTE, Bhopal (M.P.) LNCTE, Bhopal (M.P.) shrilnct@gmail.com babitapathik@gmail.com
Dr. Shiv K. Sahu Dept. of CS & Engineering LNCTE, Bhopal (M.P.) shivksahu@rediffmail.com
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The increasing rate of popularity of android
space, while the OS run in kernel space. Those applications requiring access to protected libraries must be signed using a certificate issued by Symbian, while all others can be selfsigned. Protection at the market level is inexistent or very low. BLACKBERRY security model is based on a coarsegrained permission protection model. Applications have very limited access to the device resources and, as in the case of BLACKBERRY OS, they must be signed by the manufacturer (RIM) to be able to access resources such as, for example, the user’s personal information. Additionally, applications must get user authorization to access resources such as the network. However, once the user grants access to an application to use the network, the application can both send SMSs and connect to Internet. Although applications are not executed in a sandbox, some basic process and memory protection is offered. For instance, a process cannot kill other processes nor access memory outside the app bounds. Google’s ANDROID OS security model relies on platform protection mechanism rather than on market protection, as users are free to download applications from any market. Applications declare the permissions they request at installation time through the so-called manifest. If the user accepts them, the operating system will be in charge of enforcing them at running time. Apples IOS security model relies on market protection mechanisms rather than enforcing complex per-mission polices on the device at installation time. Apple’s App Store is a walled-garden market with a rigorous review process [7]. Those processes are essential for preventing malware from entering the device, as runtime security mechanisms are limited to sandboxing and user supervision. IOS isolates each thirdparty application in a sandbox. However, most of the device’s resources are accesible1 and misuse of a few of such as GPS, SMS, and phone calls can only be detected by the user after installation. Furthermore, IOS sandboxing model is weaker than ANDROID OS’s, as Apple only uses one sandbox to run all applications, whereas Google separates each application in a sandbox. Microsoft’s market protection model for WINDOWS MOBILE systems is based on application review. Developers are also validated prior to application’s approval. Platform protection in WINDOWS MOBILE is similar to ANDROID OS. It uses a trusted boot component and code signing to protect the integrity of the operating system. It also provides signed drivers and applications through the Windows Phone Store online market. Malware software that
based smart phone is day to day. The uses of smart phone compromise with various malware and infected virus. The malware and infected software degraded the performance of smart phone and android based system. The process of malware in smart device also theft the secured information and data over the third party. In this paper present the review of malware detection and classification based on different feature extraction and classification technique. The feature extractions play an important role in malware detection and classification. For the extraction of features used various data oriented features extractor. Keywords: Smart classification
devices,
malware,
android,
1. INTRODUCTION Smart devices are rapidly emerging as popular appliances with increasingly powerful computing, networking and sensing capabilities. Perhaps the most successful examples of such devices so far are smart phones and tablets, which in their current generation are far more powerful than early personal computers (PCs). The key difference between such smart devices and traditional “non-smart” appliances is that they offer the possibility to easily incorporate third-party applications through online markets. The popularity of smart devices –intimately related to the rise of cloud-computing paradigms giving complementary storage and computing services is backed by recent commercial surveys, showing that they will very soon outsell the number of PCs worldwide. For example, the number of smart phone users has rapidly increased over the past few years. Smart devices present greater security and privacy issues to users than traditional PCs. For instance, many of such devices incorporate numerous sensors that could leak highly sensitive information about users’ location, gestures, moves and other physical activities, as well as recording audio, pictures and video from their surroundings. Furthermore, users are increasingly embedding authentication credentials into their devices, as well as making use of on-platform micropayment technologies such as NFC. SYMBIAN OS security model is based on a basic permission system. Phone resources are controlled by the OS using a set of permissions called capabilities [4]. Furthermore, applications run in user
© 2017, IRJET
|
Impact Factor value: 5.181
|
ISO 9001:2008 Certified Journal
|
Page 202