Adeel Akram

16-bit frequency signatured directly printable tag for organic electronics

A compact 16-bit chipless RFID moisture sensor tag with a size of 13.2 x 19.6mm(2) is designed, fabricated and analyzed. The presented moisture sensor tag is realized on a paper substrate with silv ...

Directly Printable Moisture Sensor Tag for Intelligent Packaging

A compact, flexible 24-b dual-polarized chipless radio frequency identification tag with a size of 20.6mm × 19.9mm is realized. The tag structure is optimized and analyzed for Taconic, Kapton TIN and organic substrate. The prototype fabricated on TIP photopaper with silver nanoparticles-based conductive ink is exhibiting a behavior of moisture sensor. The proposed moisture sensor tag has a bandwidth of 13.5GTIz. The direct printability of moisture sensor tag makes it suitable for intelligent packaging and various low-cost applications.

CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET

A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO.

Pseudo-random key generation for secure HMAC-MD5

Cryptographic hash functions had been very significant primitives to the cryptography. They have been utilized widely in cryptographic applications and most important of them is their use in the composition of efficient Message Authentication Codes (MACs). The cryptanalysis of hashing algorithms used in Hash Message Authentication Code(HMAC) like SHA-1 and MD5 have found many attacks against them [5], [6], [7], [8]. But this does not mean that if the underlying hashing algorithms are breakable then HMAC is also breakable. It is infeasible for the attacker to break HMAC because he would not be able to generate message sets offline without predicting the key K. The goal of this paper is to improve the strength of Hash Message Authentication Code (HMAC), so that its resistance increases to the Birthday Attack and Exhaustive key Search Attack. The secret key used in calculation of HMAC is shared among the sender and the recipient. We generated the Secret key with the help of a pseudorandom MD6 hashing function so that it becomes more secure and hard to envisage by forgery.

Cognitive ALE for HF Radios

This paper presents a novel technique for reducing time delay and improving the performance of Automatic Link Establishment (ALE) in High Frequency (HF)radios. The techniques proposed for Listen Before Transmit(LBT) based on cognitive radio sensing techniques such as energy detection, matched filter detection and cyclostationary feature detection. ALE is a de facto standard for HF radios through which communication is to be carried out by automatically selecting the channel. Current LBT techniques for ALE work fine for good quality channels but it performs pitiable when the channel quality becomes worst.

Using Genetic Algorithm to Minimize False Alarms in Insider Threats Detection of Information Misuse in Windows Environment

Insider threats detection problem has always been one of the most difficult challenges for organizations and research community. Effective behavioral categorization of users plays a vital role for the success of any detection mechanisms. It also helps to reduce false alarms in case of insider threats. In order to achieve this, a fuzzy classifier has been implemented along with genetic algorithm (GA) to enhance the efficiency of a fuzzy classifier. It also enhances the functionality of all other modules to achieve better results in terms of false alarms. A scenario driven approach along with mathematical evaluation verifies the effectiveness of the modified framework. It has been tested for the enterprises having critical nature of business. Other organizations can adopt it in accordance with their specific nature of business, need, and operational processes. The results prove that accurate classification and detection of users were achieved by adopting the modified framework which in turn minimizes false alarms.

Hybrid mid-link spectral inverter to compensate for linear and nonlinear distortions for efficient transmission performance in 224 Gbit/s DP-16QAM system

Abstract. The hybrid mid-link spectral inversion (H-MLSI) and digital signal processing techniques to compensate for the optical Kerr effects in 224  Gbit/s DP-16QAM transmission over 640 km of single-mode fiber are numerically evaluated. Digital signal processing methods, i.e., electronic dispersion compensation (EDC) and digital backward propagation (DBP) techniques, are implemented. The system is evaluated for diverse signal input launch powers for both single-channel and multichannel transmission in which five channels are multiplexed with a channel spacing of 100 GHz with central wavelength at 1550 nm. The system performance is enumerated by monitoring the bit error ratio. From the results, it is clear that the nonlinear threshold point is improved by 2 and 3 dBm signal power by using H-MLSI and DBP, respectively, with 20 steps per fiber span as compared to EDC. Furthermore, we have also evaluated the DBP complexity as compared to H-MLSI and the resultant impact on maximum transmission distance. Moreover, the performance penalty coming from the span-offset of H-MLSI can be reduced by employing DBP to compensate for the residual Kerr effects.

Implementation of VANET-based Warning Generation System using Cellular Networks, GPS, and Passive RFID Tags

Vehicular communication systems are a key part of an intelligent transportation system, while vehicle safety communication is a major target of vehicular communication. Other features that augment vehicular ad hoc networks are enhanced driving experience, including but not limited to, active navigation and weather information, real-time traffic information and a plethora of other autonomous and automated systems. However, our focus will be warning generation systems, which can help reduce fatalities if deployed in an efficient and fail-safe manner on motorways and highways. This paper describes a collective information system for collection and delivery of traffic information aimed at supporting fast, efficient and secure travel of people and transport of goods. Based on that information, authorities are able to assess vehicles’ sudden motion and movement changes and can generate warning/alert messages (for emergency/police vehicles) for post-accident scenarios. In this paper, the use of a radio frequency identification (RFID) system for vehicular communication has been proposed and an extended RFID system and infrastructure for vehicle safety communication through emergency phone towers (EPTs) and cell phones is suggested. In order to communicate, vehicles may be equipped with a cellular phone, RFID, and/or a global positioning system (GPS), whereas RFID readers may be mounted on EPTs, which are already installed on motorways. It also provides a demonstration on flow of information within the system; the simulation results are also included.

Relay based clustering with least distance cluster head selection for wireless sensor networks

This paper proposes an enhanced relay based clustering technique well suited for networks with heterogeneous energy distribution. In relay based architecture, previously the Cluster head is chosen on the basis of highest node energy. We have developed a new technique in which the node with highest energy and having minimum distance from the sink will be assigned as cluster head. The simulation results show that the new Relay Based Clustering with Least Distance Head Selection (RBC-LDHS) technique provides longer lifetime and transmit larger amount of messages to the sink than the classical clustering algorithm.

Suitability of Indoor Positioning System for Smart City IoT Applications

Indoor Positioning is a substantial field of research which requires frequent revisions due to continual developments and various applications in the Smart-City environment. It has found its way into various applications because of the consistent requirement of increased positioning accuracy while maintaining the user privacy. This paper presents technological overview and comparison of indoor location systems for their suitability in Smart City applications. These systems are analyzed for their scalability, range, accuracy, storage requirements and privacy. The paper is fixated on indoor positioning systems that have high accuracy. General Terms Smart Cities, Indoor Positioning, Privacy, Scalability, Mobility