Biblio

In today’s digital world, Mobile SMS (short message service) communication has almost become a part of every human life. Meanwhile each mobile user suffers from the harass of Spam SMS. These Spam SMS constitute veritable nuisance to mobile subscribers. Though hackers or spammers try to intrude in mobile computing devices, SMS support for mobile devices become more vulnerable as attacker tries to intrude into the system by sending unsolicited messages. An attacker can gain remote access over mobile devices. We propose a novel approach that can analyze message content and find features using the TF-IDF techniques to efficiently detect Spam Messages and Ham messages using different Machine Learning Classifiers. The Classifiers going to use in proposed work can be measured with the help of metrics such as Accuracy, Precision and Recall. In our proposed approach accuracy rate will be increased by using the Voting Classifier.

Nowadays, peoples are very concerned about their data privacy. Hence, all the current security methods should be improved to stay relevant in this fast-growing technology world. Visual Cryptography (VC) is a cryptographic technique that using the image processing method. The implementation of VC can be varying and flexible to be applied to the system that requires an extra security precaution as it is one of the effective solutions in securing the data exchange between two or more parties. The main purpose of the development of V-CRYPT System is to improve the current VC technique and make it more complex in the encryption and decryption process. V-CRYPT system will let the user enter the key, then select the image that they want to encrypt, and the system will split the image into four shares: share0, share1, share2, share3. Each pixel of the image will be splatted into a smaller block of subpixels in each of the four shares and encrypted as two subpixels in each of the shares. The decryption will work only when the user selects all the shares, and the correct text key is entered. The system will superimpose all the shares and producing one perfect image. If the incorrect key is entered, the resulted image will be unidentified. The results show that V- CRYPT is a valuable alternative to existing methods where its security level is higher in terms of adding a secure key and complexity.

Mobile wearable health devices have expanded prevalent usage and become very popular because of the valuable health monitor system. These devices provide general health tips and monitoring human health parameters as well as generally assisting the user to take better health of themselves. However, these devices are associated with security and privacy risk among the consumers because these devices deal with sensitive data information such as users sleeping arrangements, dieting formula such as eating constraint, pulse rate and so on. In this paper, we analyze the significant security and privacy features of three very popular health tracker devices: Fitbit, Jawbone and Google Glass. We very carefully analyze the devices' strength and how the devices communicate and its Bluetooth pairing process with mobile devices. We explore the possible malicious attack through Bluetooth networking by hacker. The outcomes of this analysis show how these devices allow third parties to gain sensitive information from the device exact location that causes the potential privacy breach for users. We analyze the reasons of user data security and privacy are gained by unauthorized people on wearable devices and the possible challenge to secure user data as well as the comparison of three wearable devices (Fitbit, Jawbone and Google Glass) security vulnerability and attack type.

SQL injection attack (SQLIA) pose a serious security threat to the database driven web applications. This kind of attack gives attackers easily access to the application's underlying database and to the potentially sensitive information these databases contain. A hacker through specifically designed input, can access content of the database that cannot otherwise be able to do so. This is usually done by altering SQL statements that are used within web applications. Due to importance of security of web applications, researchers have studied SQLIA detection and prevention extensively and have developed various methods. In this research, after reviewing the existing research in this field, we present a new hybrid method to reduce the vulnerability of the web applications. Our method is specifically designed to detect and prevent SQLIA. Our proposed method is consists of three phases namely, the database design, implementation, and at the common gateway interface (CGI). Details of our approach along with its pros and cons are discussed in detail.

Hackers create different types of Malware such as Trojans which they use to steal user-confidential information (e.g. credit card details) with a few simple commands, recent malware however has been created intelligently and in an uncontrolled size, which puts malware analysis as one of the top important subjects of information security. This paper proposes an efficient dynamic malware-detection method based on API similarity. This proposed method outperform the traditional signature-based detection method. The experiment evaluated 197 malware samples and the proposed method showed promising results of correctly identified malware.

The rise of malware attack and data leakage is putting the Internet at a higher risk. Digital forensic examiners responsible for cyber security incident need to continually update their processes, knowledge and tools due to changing technology. These attack activities can be investigated by means of Digital Triage Forensics (DTF) methodologies. DTF is a procedural model for the crime scene investigation of digital forensic applications. It takes place as a way of gathering quick intelligence, and presents methods of conducting pre/post-blast investigations. A DTF framework of Window malware forensic toolkit is further proposed. It is also based on ISO/IEC 27037: 2012 - guidelines for specific activities in the handling of digital evidence. The argument is made for a careful use of digital forensic investigations to improve the overall quality of expert examiners. This solution may improve the speed and quality of pre/post-blast investigations. By considering how triage solutions are being implemented into digital investigations, this study presents a critical analysis of malware forensics. The analysis serves as feedback for integrating digital forensic considerations, and specifies directions for further standardization efforts.

Cloud computing is an emerging paradigm shifting the shape of computing models from being a technology to a utility. However, security, privacy and trust are amongst the issues that can subvert the benefits and hence wide deployment of cloud computing. With the introduction of omnipresent mobile-based clients, the ubiquity of the model increases, suggesting a still higher integration in life. Nonetheless, the security issues rise to a higher degree as well. The constrained input methods for credentials and the vulnerable wireless communication links are among factors giving rise to serious security issues. To strengthen the access control of cloud resources, organizations now commonly acquire Identity Management Systems (IdM). This paper presents that the most popular IdM, namely OAuth, working in scope of Mobile Cloud Computing has many weaknesses in authorization architecture. In particular, authors find two major issues in current IdM. First, if the IdM System is compromised through malicious code, it allows a hacker to get authorization of all the protected resources hosted on a cloud. Second, all the communication links among client, cloud and IdM carries complete authorization token, that can allow hacker, through traffic interception at any communication link, an illegitimate access of protected resources. We also suggest a solution to the reported problems, and justify our arguments with experimentation and mathematical modeling.