Showing papers by "Thapar University published in 2017"

VUzzer: Application-aware Evolutionary Fuzzing.

Abstract: See, stats, and : https : / / www . researchgate . net / publication / 311886374 VUzzer : Application - aware Conference DOI : 10 . 14722 / ndss . 2017 . 23404 CITATIONS 0 READS 17 6 , including : Some : Systems Sanjay Vrije , Amsterdam , Netherlands 38 SEE Ashish International 1 SEE Cristiano VU 51 SEE Herbert VU 163 , 836 SEE All . The . All - text and , letting . Abstract—Fuzzing is an effective software testing technique to find bugs . Given the size and complexity of real - world applications , modern fuzzers tend to be either scalable , but not effective in exploring bugs that lie deeper in the execution , or capable of penetrating deeper in the application , but not scalable . In this paper , we present an application - aware evolutionary fuzzing strategy that does not require any prior knowledge of the application or input format . In order to maximize coverage and explore deeper paths , we leverage control - and data - flow features based on static and dynamic analysis to infer fundamental prop - erties of the application . This enables much faster generation of interesting inputs compared to an application - agnostic approach . We implement our fuzzing strategy in VUzzer and evaluate it on three different datasets : DARPA Grand Challenge binaries (CGC) , a set of real - world applications (binary input parsers) , and the recently released LAVA dataset . On all of these datasets , VUzzer yields significantly better results than state - of - the - art fuzzers , by quickly finding several existing and new bugs .

Anonymous Authentication for Wireless Body Area Networks With Provable Security

Abstract: Advances in wireless communications, embedded systems, and integrated circuit technologies have enabled the wireless body area network (WBAN) to become a promising networking paradigm. Over the last decade, as an important part of the Internet of Things, we have witnessed WBANs playing an increasing role in modern medical systems because of its capabilities to collect real-time biomedical data through intelligent medical sensors in or around the patients’ body and send the collected data to remote medical personnel for clinical diagnostics. WBANs not only bring us conveniences but also bring along the challenge of keeping data’s confidentiality and preserving patients’ privacy. In the past few years, several anonymous authentication (AA) schemes for WBANs were proposed to enhance security by protecting patients’ identities and by encrypting medical data. However, many of these schemes are not secure enough. First, we review the most recent AA scheme for WBANs and point out that it is not secure for medical applications by proposing an impersonation attack. After that, we propose a new AA scheme for WBANs and prove that it is provably secure. Our detailed analysis results demonstrate that our proposed AA scheme not only overcomes the security weaknesses in previous schemes but also has the same computation costs at a client side.

Secure Signature-Based Authenticated Key Establishment Scheme for Future IoT Applications

Abstract: Internet of Things (IoT) is a network of all devices that can be accessed through the Internet. These devices can be remotely accessed and controlled using existing network infrastructure, thus allowing a direct integration of computing systems with the physical world. This also reduces human involvement along with improving accuracy and efficiency, resulting in economic benefit. The devices in IoT facilitate the day-to-day life of people. However, the IoT has an enormous threat to security and privacy due to its heterogeneous and dynamic nature. Authentication is one of the most challenging security requirements in the IoT environment, where a user (external party) can directly access information from the devices, provided the mutual authentication between user and devices happens. In this paper, we present a new signature-based authenticated key establishment scheme for the IoT environment. The proposed scheme is tested for security with the help of the widely used Burrows-Abadi–Needham logic, informal security analysis, and also the formal security verification using the broadly accepted automated validation of Internet security protocols and applications tool. The proposed scheme is also implemented using the widely accepted NS2 simulator, and the simulation results demonstrate the practicability of the scheme. Finally, the proposed scheme provides more functionality features, and its computational and communication costs are also comparable with other existing approaches.

Generalized Pythagorean Fuzzy Geometric Aggregation Operators Using Einstein t-Norm and t-Conorm for Multicriteria Decision-Making Process

Abstract: The objective of this paper is to present some series of geometric-aggregated operators under Pythagorean fuzzy environment by relaxing the condition that the sum of the degree of membership functions is less than one with the square sum of the degree of membership functions is less than one. Under these environments, aggregator operators, namely, Pythagorean fuzzy Einstein weighted geometric, Pythagorean fuzzy Einstein ordered weighted geometric, generalized Pythagorean fuzzy Einstein weighted geometric, and generalized Pythagorean fuzzy Einstein ordered weighted geometric operators, are proposed in this paper. Some of its properties have also been investigated in details. Finally, an illustrative example for multicriteria decision-making problems of alternatives is taken to demonstrate the effectiveness of the approach.

Some Picture Fuzzy Aggregation Operators and Their Applications to Multicriteria Decision-Making

Abstract: The objective of the work is to present some series of the aggregation operators for the picture fuzzy sets (PFSs). As PFSs have been an extended version of the intuitionistic fuzzy set theory which not only considers the degree of acceptance or rejection but also taken into the account the degree of refusal during the analysis. Thus, by considering all these degrees, some aggregation operators, namely picture fuzzy weighted average, picture fuzzy ordered weighted average, and picture fuzzy hybrid average aggregation operators, have been proposed along with their desirable properties. A decision-making approach based on these operators has also been presented. Finally, an illustrative example has been given for demonstrating the approach.

Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing

Abstract: Fog computing has emerged as a promising solution for accommodating the surge of mobile traffic and reducing latency, both known to be inherent problems of cloud computing. Fog services, including computation, storage, and networking, are hosted in the vicinity of end users (edge of the network), and, as a result, reliable access is provisioned to delay-sensitive mobile applications. However, in some cases, the fog computing capacity is overwhelmed by the growing number of demands from patrons, particularly during peak hours, and this can subsequently result in acute performance degradation. In this article, we address this problem by proposing a new concept called fog vehicular computing (FVC) to augment the computation and storage power of fog computing. We also design a comprehensive architecture for FVC and present a number of salient applications. The result of implementation clearly shows the effectiveness of the proposed architecture. Finally, some open issues and envisioned directions are discussed for future research in the context of FVC.

Container-as-a-Service at the Edge: Trade-off between Energy Efficiency and Service Availability at Fog Nano Data Centers

Abstract: In the last few years, we have witnessed the huge popularity of one of the most promising technologies of the modern era: the Internet of Things. In IoT, various smart objects (smart sensors, embedded devices, PDAs, and smartphones) share their data with one another irrespective of their geographical locations using the Internet. The amount of data generated by these connected smart objects will be on the order of zettabytes in the coming years. This huge amount of data creates challenges with respect to storage and analytics given the resource constraints of these smart devices. Additionally, to process the large volume of information generated, the traditional cloud-based infrastructure may lead to long response time and higher bandwidth consumption. To cope up with these challenges, a new powerful technology, edge computing, promises to support data processing and service availability to end users at the edge of the network. However, the integration of IoT and edge computing is still in its infancy. Task scheduling will play a pivotal role in this integrated architecture. To handle all the above mentioned issues, we present a novel architecture for task selection and scheduling at the edge of the network using container-as-a-service (CoaaS). We solve the problem of task selection and scheduling by using cooperative game theory. For this purpose, we developed a multi-objective function in order to reduce the energy consumption and makespan by considering different constraints such as memory, CPU, and the user's budget. We also present a real-time internal and external container migration technique for minimizing the energy consumption. For task selection and scheduling, we have used lightweight containers instead of the conventional virtual machines to reduce the overhead and response time as well as the overall energy consumption of fog devices, that is, nano data centers (nDCs). Our empirical results demonstrate that the proposed scheme reduces the energy consumption and the average number of SLA violations by 21.75 and 11.82 percent, respectively.

Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process

Abstract: Pythagorean fuzzy set, an extension of the intuitionistic fuzzy set which relax the condition of sum of their membership function to square sum of its membership functions is less than one. Under these environment and by incorporating the idea of the confidence levels of each Pythagorean fuzzy number, the present study investigated a new averaging and geometric operators namely confidence Pythagorean fuzzy weighted and ordered weighted operators along with their some desired properties. Based on its, a multi criteria decision-making method has been proposed and illustrated with an example for showing the validity and effectiveness of it. A computed results are compared with the aid of existing results.

Efficient and Privacy-Preserving Data Aggregation Scheme for Smart Grid Against Internal Adversaries

Abstract: Privacy-preserving data aggregation (P2DA) is an important basic building block that can protect consumer’s privacy in the smart grid environment because it could be used to prevent the extraction of the electricity consumption information of a specific consumer. Due to this important function, the P2DA scheme for the smart grid has attracted a lot of attention from both academic and industry researchers who have proposed many P2DA schemes for the smart grid in recent years. However, most of these P2DA schemes are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter’s side. To address the deficiencies of previous schemes, we propose a new P2DA scheme against internal attackers using Boneh–Goh–Nissim public key cryptography. The proposed P2DA scheme does not use bilinear pairing or hash-to-point operation making it be more computationally efficient than previous P2DA schemes. We also show that the proposed P2DA scheme is provably secure and can meet various security requirements.

Electrocatalytic CO2 Reduction by Imidazolium-Functionalized Molecular Catalysts

Abstract: We present the first examples of CO2 electro-reduction catalysts that feature charged imidazolium groups in the secondary coordination sphere. The functionalized Lehn-type catalysts display significant differences in their redox properties and improved catalytic activities as compared to the conventional reference catalyst. Our results suggest that the incorporated imidazolium moieties do not solely function as a charged tag but also alter mechanistic aspects of catalysis.

Microbial healing of cracks in concrete: a review.

Abstract: Concrete is the most widely used construction material of the world and maintaining concrete structures from premature deterioration is proving to be a great challenge. Early age formation of micro-cracking in concrete structure severely affects the serviceability leading to high cost of maintenance. Apart from conventional methods of repairing cracks with sealants or treating the concrete with adhesive chemicals to prevent the cracks from widening, a microbial crack-healing approach has shown promising results. The unique feature of the microbial system is that it enables self-healing of concrete. The effectiveness of microbially induced calcium carbonate precipitation (MICCP) in improving durability of cementitious building materials, restoration of stone monuments and soil bioclogging is discussed. Main emphasis has been laid on the potential of bacteria-based crack repair in concrete structure and the applications of different bacterial treatments to self-healing cracks. Furthermore, recommendations to employ the MICCP technology at commercial scale and reduction in the cost of application are provided in this review.

A Novel Improved Accuracy Function for Interval Valued Pythagorean Fuzzy Sets and Its Applications in the Decision-Making Process

Abstract: The objective of this work is to present an improved accuracy function for the ranking order of interval-valued Pythagorean fuzzy sets (IVPFSs). Shortcomings of the existing score and accuracy functions in interval-valued Pythagorean environment have been overcome by the proposed accuracy function. In the proposed function, degree of hesitation between the element of IVPFS has been taken into account during the analysis. Based on it, multicriteria decision-making method has been proposed for finding the desirable alternative(s). Finally, an illustrative example for solving the decision-making problem has been presented to demonstrate application of the proposed approach.

An advanced Internet of Thing based Security Alert System for Smart Home

Abstract: Before inception of Internet of Things (IoT), personal computers and laptop were used to handle daily tasks of individuals like mail surfing, access to bank portal, observing current temperature, among others. Nowadays, IoT-enabled smart devices like smart mobile phones, PDAs, and tablets are being used by them for such tasks due to rapid growth in IoT. Smart homes have been widely accepted by individuals and organizations world wide due to their many advantages. Home security systems can be defined as monitoring of complete home/some portion of home from a remotely located or centralized location. It allows the user to watch all activities inside the home from a remote location that ultimately gives satisfaction to the owner of the home. Many home security systems exist, but they have some challenging issues like: delay, non-web enabled and difficult to handle during transfer of alerts to user in situation where any unusual event occurred inside the home. If any unusual event encountered inside the home, where security systems deployed, then system must be capable enough to send alert to the user without any delay by phone, text, or email. Cameras and other latest network technologies have enabled us to remotely monitor the home more effectively and efficiently from our smart phone. Hence, considering the above mentioned facts, in this paper, we have proposed an advanced Internet of Thing based Security Alert System for Smart Home in order to detect an intruder or any unusual event at home, when nobody is available there. This low-cost home security system utilizes a small pyroelectric Infrared (PIR) module and raspberry pi for minimizing the delay during process of e-mail alert. This paper also confirms the advantage of Raspberry Pi flexibility and broad probability of its usage. Preliminary analyses have shown encouraging results.

Chemical vapor treatment of ABS parts built by FDM: Analysis of surface finish and mechanical strength

Abstract: The present study investigates the simultaneous effect of part building orientation (along the X, Y, and Z axis) and raster angle (0°, 30°, 60°, and 90°) on surface roughness, tensile strength, flexural strength, consumption of model, support material, and building time of acrylonitrile butadiene styrene (ABS) test specimens fabricated by fused deposition modeling (FDM) process. Mechanical properties and surface roughness show a strong anisotropic behavior for the parts. For parts built with the X or Y orientations and 30° or 60° raster angle, pulling of fiber and a small amount of necking along with tearing are observed, which are responsible for higher strength. Post-built treatment of the parts with cold vapors of dimethyl ketone resulted in an immense improvement in surface finish. Exposing the parts in cold vapors turns the surfaces to a soft/mushy-like state due to the weakening of the secondary bonds, and the minor flow of polymer layers fills the cavity region between the adjacent layers and helps in improving the surface finish after the treatment.

A stable energy efficient clustering protocol for wireless sensor networks

Abstract: Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.

Data Offloading in 5G-Enabled Software-Defined Vehicular Networks: A Stackelberg-Game-Based Approach

Abstract: Data offloading using vehicles is one of the most challenging tasks to perform due to the high mobility of vehicles. There are many solutions available for this purpose, but due to the inefficient management of data along with the control decisions, these solutions are not adequate to provide data offloading by making use of the available networks. Moreover, with the advent of 5G and related technologies, there is a need to cope with high speed and traffic congestion in the existing infrastructure used for data offloading. Hence, to make intelligent decisions for data offloading, an SDN-based scheme is presented in this article. In the proposed scheme, an SDNbased controller is designed that makes decisions for data offloading by using the priority manager and load balancer. Using these two managers in SDN-based controllers, traffic routing is managed efficiently even with an increase in the size of the network. Moreover, a single-leader multi-follower Stackelberg game for network selection is also used for data offloading. The proposed scheme is evaluated with respect to several parameters where its performance was found to be superior in comparison to the existing schemes.

Secure Three-Factor User Authentication Scheme for Renewable-Energy-Based Smart Grid Environment

Abstract: Smart grid (SG) technology has recently received significant attention due to its usage in maintaining demand response management in power transmission systems. In SG, charging of electric vehicles becomes one of the emerging applications. However, authentication between a vehicle user and a smart meter is required so that both of them can securely communicate for managing demand response during peak hours. To address the above mentioned issues, in this paper, we propose a new efficient three-factor user authentication scheme for a renewable energy-based smart grid environment (TUAS-RESG), which uses the lightweight cryptographic computations such as one-way hash functions, bitwise XOR operations, and elliptic curve cryptography. The detailed security analysis shows the robustness of TUAS-RESG against various well-known attacks. Moreover, TUAS-RESG provides superior security with additional features, such as dynamic smart meter addition, flexibility for password and biometric update, user and smart meter anonymity, and untraceability as compared to other related existing schemes. The practical demonstration of TUAS-RESG is also proved using the widely accepted NS2 simulation.

Data Aggregation in Wireless Sensor Networks: Previous Research, Current Status and Future Directions

Abstract: Wireless sensor networks (WSNs) consist of large number of small sized sensor nodes, whose main task is to sense the desired phenomena in a particular region of interest. These networks have large number of applications such as habitat monitoring, disaster management, security and military etc. Sensor nodes are very small in size and have limited processing capability as these nodes have very low battery power. WSNs are also prone to failure, due to low battery power constraint. Data aggregation is an energy efficient technique in WSNs. Due to high node density in sensor networks same data is sensed by many nodes, which results in redundancy. This redundancy can be eliminated by using data aggregation approach while routing packets from source nodes to base station. Researchers still face trouble to select an efficient and appropriate data aggregation technique from the existing literature of WSNs. This research work depicts a broad methodical literature analysis of data aggregation in the area of WSNs in specific. In this survey, standard methodical literature analysis technique is used based on a complete collection of 123 research papers out of large collection of 932 research papers published in 20 foremost workshops, symposiums, conferences and 17 prominent journals. The current status of data aggregation in WSNs is distributed into various categories. Methodical analysis of data aggregation in WSNs is presented which includes techniques, tools, methodology and challenges in data aggregation. The literature covered fifteen types of data aggregation techniques in WSNs. Detailed analysis of this research work will help researchers to find the important characteristics of data aggregation techniques and will also help to select the most suitable technique for data aggregation. Research issues and future research directions have also been suggested in this research literature.

Network Service Chaining in Fog and Cloud Computing for the 5G Environment: Data Management and Security Challenges

Abstract: In the last few years, we have seen an exponential increase in the number of Internet-enabled devices, which has resulted in popularity of fog and cloud computing among end users. End users expect high data rates coupled with secure data access for various applications executed either at the edge (fog computing) or in the core network (cloud computing). However, the bidirectional data flow between the end users and the devices located at either the edge or core may cause congestion at the cloud data centers, which are used mainly for data storage and data analytics. The high mobility of devices (e.g., vehicles) may also pose additional challenges with respect to data availability and processing at the core data centers. Hence, there is a need to have most of the resources available at the edge of the network to ensure the smooth execution of end-user applications. Considering the challenges of future user demands, we present an architecture that integrates cloud and fog computing in the 5G environment that works in collaboration with the advanced technologies such as SDN and NFV with the NSC model. The NSC service model helps to automate the virtual resources by chaining in a series for fast computing in both computing technologies. The proposed architecture also supports data analytics and management with respect to device mobility. Moreover, we also compare the core and edge computing with respect to the type of hypervisors, virtualization, security, and node heterogeneity. By focusing on nodes' heterogeneity at the edge or core in the 5G environment, we also present security challenges and possible types of attacks on the data shared between different devices in the 5G environment.