Dynamic addressing in wireless sensor networks without location awareness

Sensor Networks have applications in diverse fields. They can be deployed for habitat modeling, temperature monitoring and industrial sensing. They also find applications in battlefield awareness and emergency (first) response situations. While unique addressing is not a requirement of many data collecting applications of wireless sensor networks, it is vital for the success of applications such as emergency response. Data that cannot be associated with a specific node becomes useless in such situations. In this work we propose a novel dynamic addressing mechanism for wireless sensor networks that are not location-aware. The scheme enables successful reuse of addresses in event-driven wireless sensor networks introducing minimal latencies and efficiently addressing packet loss. It also eliminates the need for network-wide Duplicate Address Detection (DAD) to ensure uniqueness of network level addresses.

Faster CRT-RSA Decryption towards RFID applications

In this paper we present a strategy to design the RSA parameters in such a manner so that the CRT-RSA decryption becomes more efficient than the existing methods. We achieve around 21% improvement in speed over the currently best known implementation strategy for CRT-RSA decryption with our properly chosen parameters that also helps in terms of less memory requirement. Moreover, we argue in detail the cryptographic security regarding our choice of the secret parameters.

Enhanced RFID mutual authentication scheme based on shared secret information

RFID is a revolutionary remote technology which has many useful implications. Large scale implementation of RFID is seeking 100% information privacy and untraceability, for users and organizations, which is suitable for low cost RFID tag (Class1). To protect users and organization we are proposing an enhanced RFID mutual authentication scheme. In this protocol we use authentication based on shared unique parameters as a method to protect privacy. This protocol will be capable of handling forward and backward security, rouge reader better than existing protocols. In our new scheme we involved RFID reader’s hardware ID in addition to other shared secret information which uses hash to protect users and industries privacy. Moreover, we used LAMED as our PRNG (Pseudorandom Number Generator) which is faster and take less computational power.

Mutual authentication with malware protection for a RFID system

Radio Frequency Identification (RFID) system is a remote identification technology which is taking the place of barcodes to become electronic tags of an object. However, its radio transmission nature is making it vulnerable in terms of security. Recently, research proposed that an RFID tag can contain malicious code which might spread viruses, worms and other exploits to middleware and back-end systems. This paper is proposing a framework which will provide protection from malware and ensure the data privacy of a tag. The framework will use a sanitization technique with a mutual authentication in the reader level. This will ensure that any malicious code in the tag is identified. If the tag is infected by malicious code it will stop execution of the code in the RFIF system. Here shared unique parameters are used for authentication. It will be capable of protecting an RFID system from denial of service (DOS) attack, forward security and rogue reader better than existing protocols. The framework is introducing a layer concept on a smart reader to reduce coupling between different tasks. Using this framework, the RFID system will be protected from malware and also the privacy of the tag will be ensured.

Secure connectivity model in wireless sensor networks (WSN) using first order Reed-Muller codes

In this paper, we suggest the idea of separately treating the connectivity and communication model of a Wireless Sensor Network (WSN). We then propose a novel connectivity model for a WSN using first order Reed-Muller Codes. While the model has a hierarchical structure, we have shown that it works equally well for a Distributed WSN. Though one can use any communication model, we prefer to use the communication model suggested by Ruj and Roy [1] for all computations and results in our work. Two suitable secure (symmetric) cryptosystems can then be applied for the two different models, connectivity and communication respectively. By doing so we have shown how resiliency and scalability are appreciably improved as compared to Ruj and Roy [1].

Security of RFID systems - a hybrid approach

The use of RFID (Radio Frequency Identification) technology can be employed for tracking and detecting each container, pallet, case, and product uniquely in the supply chain. It connects the supply chain stakeholders (i.e.; suppliers, manufacturers, wholesalers/distributors, retailers and customers) and allows them to exchange data and product information. Despite these potential benefits, security issues are the key factor in the deployment of a RFID-enabled system in the global supply chain. This paper proposes a hybrid approach to secure RFID transmission in Supply Chain Management (SCM) systems using modified Wired Equivalent Encryption (WEP) and Rivest, Shamir and Adleman (RSA) cryptosystem. The proposed system also addresses the common loop hole of WEP key algorithm and makes it more secure compare to the existing modified WEP key process.

Smart RFID reader protocol for malware detection

Radio frequency identification (RFID) is a remote identification technique promises to revolutionize the way a specific object use to identify in our industry. However, large scale implementation of RFID sought for protection, against Malware threat, information privacy and un-traceability, for low cost RFID tag. In this paper, we propose a framework to provide privacy for tag data and to provide protection for RFID system from malware. In the proposed framework, malware infected tag is detected by analysing individual component of the RFID tag. It uses sanitization technique for analysing individual component. Here authentication based shared unique parameters is used as a method to protect privacy. This authentication protocol will be capable of handling forward and backward security and identifying rogue reader better than existing protocols. Using this framework, the RFID system will be protected from malware and the privacy of the tag will be ensured as well.

A framework for elearning with social media using DRM

This paper provides a proposal for personal e-learning system (PELS) architecture in the context of social network environment. The main objective of PELS is to develop individual skills on a specific subject and share resources with peers. Our system architecture defines organization and management of personal learning environment that aids in creating, verifying and sharing learning artifacts and making money at the same time. We also focus on in our research one of the most interesting arenas in digital content or document management called Digital Right Management (DRAM) and its application to eLearning.

Key predistribution scheme using finite fields and reed muller codes

Resource constraint sensors of a Wireless Sensor Network (WSN) cannot afford the use of costly encryption techniques like public key while dealing with sensitive data. So symmetric key encryption techniques are preferred where it is essential to have the same cryptographic key between communicating parties. To this end, keys are preloaded into the nodes before deployment and are to be established once they get deployed in the target area. This entire process is called key predistribution. In this paper we propose one such scheme using unique factorization of polynomials over Finite Fields. To the best of our knowledge such an elegant use of Algebra is being done for the first time in WSN literature. The best part of the scheme is large number of node support with very small and uniform key ring per node. However the resiliency is not good. For this reason we use a special technique based on Reed Muller codes proposed recently by Sarkar, Saha and Chowdhury in 2010. The combined scheme has good resiliency with huge node support using very less keys per node.

Web health portal to enhance patient safety in Australian healthcare systems

The use of a web Health Portal can be employed not only for reducing health costs but also to view patient's latest medical information (e.g. clinical tests, pathology and radiology results, discharge summaries, prescription renewals, referrals, appointments) in real-time and carry out physician messaging to enhance the information exchanged, managed and shared in the Australian healthcare sector. The Health Portal connects all stakeholders (such as patients and their families, health professionals, care providers, and health regulators) to establish coordination, collaboration and a shared care approach between them to improve overall patient care safety. The paper outlines a Health Portal model for designing a real-time health prevention system. An application of the architecture is described in the area of web Health Portal.

Detecting unknown anomalous program behavior using API system calls

This paper presents the detection techniques of anomalous programs based on the analysis of their system call traces. We collect the API calls for the tested executable programs from Microsoft detour system and extract the features for our classification task using the previously established n-gram technique. We propose three different feature extraction approaches in this paper. These are frequency-based, time-based and a hybrid approach which actually combines the first two approaches. We use the well-known classifier algorithms in our experiments using WEKA interface to classify the malicious programs from the benign programs. Our empirical evidence demonstrates that the proposed feature extraction approaches can detect malicious programs over 88% which is quite promising for the contemporary similar research.

Detecting unwanted email using VAT

Spam or unwanted email is one of the potential issues of Internet security and classifying user emails correctly from penetration of spam is an important research issue for anti-spam researchers. In this paper we present an effective and efficient spam classification technique using clustering approach to categorize the features. In our clustering technique we use VAT (Visual Assessment and clustering Tendency) approach into our training model to categorize the extracted features and then pass the information into classification engine. We have used WEKA (www.cs.waikato.ac.nz/ml/weka/) interface to classify the data using different classification algorithms, including tree-based classifiers, nearest neighbor algorithms, statistical algorithms and AdaBoosts. Our empirical performance shows that we can achieve detection rate over 97%.

Optimization and matrix constructions for classification of data

Max-plus algebras and more general semirings have many useful applications and have been actively investigated. On the other hand, structural matrix rings are also well known and have been considered by many authors. The main theorem of this article completely describes all optimal ideals in the more general structural matrix semirings. Originally, our investigation of these ideals was motivated by applications in data mining for the design of centroid-based classification systems, as well as for the design of multiple classification systems combining several individual classifiers.

vPELS : an eLearning social environment for VLSI design with content security using DRM

This paper provides a proposal for personal e-learning system (vPELS) architecture in the context of social network environment for VLSI Design. The main objective of vPELS is to develop individual skills on a specific subject, say, VLSI and share resources with peers. Our system architecture defines organization and management of personal learning environment that aids in creating, verifying and sharing learning artifacts and making money at the same time. We also focus on in our research one of the most interesting arenas in digital content or document management called Digital Right Management (DRAM) and its application to eLearning.