Mobile computing devices
Mobile computing devices, such as smart phones and tables, can cause harm to individuals and organizations since they are far less secure compared to laptops and desktops. As the number of people using or owing mobile devices increases, mobile security concerns increase, as well. There are different detection techniques that expose vulnerabilities and threats in mobile devices. These detection techniques are categorized into three types, namely; dynamic, static, and permission-based analysis. Static analysis detects malware in downloaded applications by checking its source code and software properties. However, encryption and obfuscation techniques in software makes this technique difficult. Droid Mat is a static feature-based approach that detects and distinguishes android malware (Dua & Bansal, 2017). This mechanism considers the static data including intents and permissions components that characterize android malware.
Dynamic analysis executes application in isolated areas and track its execution behavior. It discloses the malware’s natural behavior as the executed code gets analyzed. Apps-playground framework involves automatic dynamic analysis for all android applications. This approach analyzes malicious applications and applications that lack private data without the user’s consent. TaintDroid is also a dynamic tool that analyzes android systems by tracking sensitive information flow through other applications. It integrates various granularities and monitors how the sensitive information is used by applications and labels the taints. Permission-based analysis uses manifest.sml to detect malicious behavior in applications. The permissions can limit application behavior by controlling privacy and reducing vulnerabilities and bugs.
We are now able to carry our world with us due to technological advancements. Since information is freely accessible, personal information can be easily accessed by other people. Hence, mobile technology can put our personal or private information at a great risk. Privacy demands that confidential or sensitive information remains in the control and possession of an individual or b=organization it belongs to. Legitimate applications and mobile operating systems access and share information regarding the user to perform their rightful tasks. However, there are strict privacy measures that have been established in the mobile devices to enhance confidentiality.
Mobile phones and apps developers have installed settings that enable mobile device owners to set up security to block unauthorized parties from taking user’s phone and accessing everything in it. Users are encouraged to use strong alphanumeric passwords to secure their devices, but it is not completely convenient. Most people consider a fingerprint as a best balance between convenience and security. One can also restrict apps from asking for permissions that they do not need unless they are collecting information on users and selling it.
Privacy is also enhanced through installation of anti-virus apps. Anti-virus software is a major component that protects the mobile device’s security. The programs scan the device’s operating system, identify risks, and removes them. These programs run in the device’s background seamlessly on a pre-set schedule to assure the users that their devices are secure. Mobile devices’ privacy can be enhanced by encrypting the phone’s data (“Mobile Privacy”, 2020). This is a good way of ensuring mobile security if the mobile device is stolen and the use can hardly block it remotely. Data encryption essentially changes electronic information and data into unreadable state through ciphers or algorithms. The use of VPN software is also an excellent way of enhancing the mobile device’s privacy without affecting its speed. When the mobile device is connected to SaferVPN, one can browse via a bank-level encrypted tunnel and enjoy a secure connection that keeps private data protected from snoopers and hackers.
References
Dua, L., & Bansal, D. (2017). Review on Mobile Threats and Detection Techniques. Retrieved 26 August 2020, from https://www.academia.edu/8177884/Review_on_Mobile_Threats_and_Detection_Techniques
Mobile Privacy. (2020). Retrieved 26 August 2020, from https://smallbusiness.theprivatebank.com/en/about-us/mobile-privacy.html