Raad S. Al-Qassas

A Secure Cloud Computing Model based on Data Classification.

Abstract In cloud computing systems, the data is stored on remote servers accessed through the internet. The increasing volume of personal and vital data, brings up more focus on storing the data securely. Data can include financial transactions, important documents, and multimedia contents. Implementing cloud computing services may reduce local storage reliance in addition to reducing operational and maintenance costs. However, users still have major security and privacy concerns about their outsourced data because of possible unauthorized access within the service providers. The existing solutions encrypt all data using the same key size without taking into consideration the confidentiality level of data which in turn will increase the cost and processing time. In this research, we propose a secure cloud computing model based on data classification. The proposed cloud model minimizes the overhead and processing time needed to secure data through using different security mechanisms with variable key sizes to provide the appropriate confidentiality level required for the data. The proposed model was tested with different encryption algorithms, and the simulation results showed the reliability and efficiency of the proposed framework.

Secure and Efficient Cloud Computing Framework

Cloud computing is a very useful solution to many individual users and organizations. It can provide many services based on different needs and requirements. However, there are many issues related to the user data that need to be addressed when using cloud computing. Among the most important issues are: data ownership, data privacy, and storage. The users might be satisfied by the services provided by the cloud computing service providers, since they need not worry about the maintenance and storage of their data. On the other hand, they might be worried about unauthorized access to their private data. Some solutions to these issues were proposed in the literature, but they mainly increase the cost and processing time since they depend on encrypting the whole data. In this paper, we are introducing a cloud computing framework that classifies the data based on their importance. In other words, more important data will be encrypted with more secure encryption algorithm and larger key sizes, while less important data might even not be encrypted. This approach is very helpful in reducing the processing cost and complexity of data storage and manipulation since we do not need to apply the same sophisticated encryption techniques to the entire users data. The results of applying the proposed framework show improvement and efficiency over other existing frameworks.

Routing and the Impact of Group Mobility Model in VANETs

Group vehicular applications could play a vital role in our life, whether these applications are safety-oriented or convenience-oriented applications. The group concept has also been used in support of many solutions in VANETs. Reference Point Group Mobility model (RPGM) is a popular group mobility model and has been used heavily in the literature. In order to study the impact of this mobility model on routing in VANETs, two well-known protocols are considered, namely AODV and AOMDV, as representatives of single-path and multipath routing, respectively. These protocols have shown performance merits over other routing protocols and they have a vital role in other wireless networks including MANETs and Wireless Mesh Networks. This paper provides a thorough evaluation of these protocols, by examining them under various potential realistic scenarios, under the RPGM mobility model. To the best of knowledge, this is the first study that examines the behaviour of the two protocols under the RPGM mobility model. The results from extensive simulations have shown that both protocols have comparable performance merits when the number of communicating nodes is low. However, increasing the number of communicating nodes has demonstrated a performance advantage for AOMDV, in the majority of the performance metrics used in the paper.

A fingerprint featured data encryption algorithm

In this paper, we propose a new DES variant named Hashed Data Encryption Standard (or HDES for short), with an objective to enhance the limitation of static S-boxes arrangement in DES. The proposed HDES combines several techniques and components into one new algorithm to enhance the original DES. The HDES uses a hash function at the beginning of each block encryption process to produce a fingerprint for the plaintext, which will be used later to produce a seed that will coordinate the generation of the S-boxes during the sixteen rounds of the encryption process. The performance of the HDES has been evaluated and compared against DES and DESX. The evaluation has been conducted using the cipher data randomness and the encryption time.

Software randomness analysis and evaluation of lightweight ciphers: the prospective for IoT security

In the past few years, various lightweight cryptographic algorithms have been proposed to balance the trade-offs between the requirements of resource constrained IoT devices and the need to securely transmit and protect data. However, it is critical to analyze and evaluate these algorithms to examine their capabilities. This paper provides a thorough investigation of the randomness of ciphertext obtained from Simeck, Kasumi, DES and AES. The design of our randomness analysis is based on five metrics implemented following the guidance of the NIST statistical test suite for cryptographic applications. This analysis also provides performance and power consumption evaluations for the selected cryptographic algorithms using different platforms and measures. Results from the evaluation reveal that lightweight algorithms have competitive randomness levels, lower processing time and lower power consumption when compared to conventional algorithms.

Randomness Analysis of DES Ciphers Produced with Various Dynamic Arrangements

Over the past few years, researchers have devoted efforts to enhance the original DES encryption algorithm. These enhancements focus on improving multiple perspectives of the algorithm through enhancing its internal components to deliver a robust DES variant against different kinds of typical attacks such as linear and differential crypto analysis, in addition to the newly evolved attacks such as differential power analysis attacks. In fact the output of existing solutions have enhanced the ciphertext randomness. This paper introduces two encryption algorithms that enhance the original DES named DDES and HDES. DDES is mainly based on a secure selection of both S-boxes and P-box arrangements during each encryption round, it has also extended the key length by adding two more keys beside the original one to the encryption process. HDES, on the other hand, uses a hash function to generate a random fingerprint for each plaintext block. This fingerprint is used to generate the seed to produce round seeds that are used to select secure S-boxes only for each round in the encryption process. These two variants meet with certain demands that are imposed by the user applications context. DDES provides a higher ciphertext randomness with some added processing time, while HDES provides a relatively secure variant with lower processing time. These two variants can provide alternatives depending on the targeted applications that require different levels of security and processing time. DDES and HDES have been evaluated and compared against DES, DESX and 3DES, using a number of metrics including chi-square test, cipher data difference, hamming distance and processing time.

A Group Leader Location Hiding Technique for VANETs

Vehicular ad hoc network (VANET) is one of the most promising and emerging communication technologies that could definitely lead to significant improvements in the traffic management and safety. Location privacy is a critical requirement in VANET, since location information may be shared between vehicles to support the VANET applications. Therefore, it is crucial to protect the location of users. In this paper, we propose a location privacy protection technique that utilises the shadow concept and takes into consideration the reliability in protecting the group leader location, which would basically provide the needed anonymity and protection for the location information targeted by global adversaries. The performance of the proposed technique has been investigated through simulation and compared against the well-known AOSA technique. The results from extensive simulations have shown that the proposed technique enhances the anonymity of the group leader vehicle by reducing the time that the global adversaries can use in collecting location information.