Visible to the public Biblio

Found 670 results

Filters: First Letter Of Last Name is G  [Clear All Filters]
A B C D E F [G] H I J K L M N O P Q R S T U V W X Y Z   [Show ALL]
G H, Samyama Gunjal, Swamy, Samarth C.  2020.  A Security Approach to Build a Trustworthy Ubiquitous Learning System. 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC). :1–6.
Modern learning systems, say a tutoring platform, has many characteristics like digital data presentation with interactivity, mobility, which provides information about the study-content as per the learners understanding levels, intelligent learners behavior, etc. A sophisticated ubiquitous learner system maintains security and monitors the mischievous behavior of the learner, and authenticates and authorizes every learner, which is quintessential. Some of the existing security schemes aim only at single entry-point authentication, which may not suit to ubiquitous tutor platform. We propose a secured authentication scheme which is based on the information utility of the learner. Whenever a learner moves into a tutor platform, which has ubiquitous learner system technology, the system at first-begins with learners' identity authentication, and then it initiates trust evaluation after the successful authentication of the learner. Periodic credential verification of the learner will be carried out, which intensifies the authentication scheme of the system proposed. BAN logic has been used to prove the authentication in this system. The proposed authentication scheme has been simulated and analyzed for the indoor tutor platform environment.
G, Emayashri, R, Harini, V, Abirami S, M, Benedict Tephila.  2022.  Electricity-Theft Detection in Smart Grids Using Wireless Sensor Networks. 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS). 1:2033—2036.
Satisfying the growing demand for electricity is a huge challenge for electricity providers without a robust and good infrastructure. For effective electricity management, the infrastructure has to be strengthened from the generation stage to the transmission and distribution stages. In the current electrical infrastructure, the evolution of smart grids provides a significant solution to the problems that exist in the conventional system. Enhanced management visibility and better monitoring and control are achieved by the integration of wireless sensor network technology in communication systems. However, to implement these solutions in the existing grids, the infrastructural constraints impose a major challenge. Along with the choice of technology, it is also crucial to avoid exorbitant implementation costs. This paper presents a self-stabilizing hierarchical algorithm for the existing electrical network. Neighborhood Area Networks (NAN) and Home Area Networks (HAN) layers are used in the proposed architecture. The Home Node (HN), Simple Node (SN) and Cluster Head (CH) are the three types of nodes used in the model. Fraudulent users in the system are identified efficiently using the proposed model based on the observations made through simulation on OMNeT++ simulator.
G. DAngelo, S. Rampone, F. Palmieri.  2015.  "An Artificial Intelligence-Based Trust Model for Pervasive Computing". 2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC). :701-706.

Pervasive Computing is one of the latest and more advanced paradigms currently available in the computers arena. Its ability to provide the distribution of computational services within environments where people live, work or socialize leads to make issues such as privacy, trust and identity more challenging compared to traditional computing environments. In this work we review these general issues and propose a Pervasive Computing architecture based on a simple but effective trust model that is better able to cope with them. The proposed architecture combines some Artificial Intelligence techniques to achieve close resemblance with human-like decision making. Accordingly, Apriori algorithm is first used in order to extract the behavioral patterns adopted from the users during their network interactions. Naïve Bayes classifier is then used for final decision making expressed in term of probability of user trustworthiness. To validate our approach we applied it to some typical ubiquitous computing scenarios. The obtained results demonstrated the usefulness of such approach and the competitiveness against other existing ones.

G. G. Granadillo, J. Garcia-Alfaro, H. Debar, C. Ponchel, L. R. Martin.  2015.  "Considering technical and financial impact in the selection of security countermeasures against Advanced Persistent Threats (APTs)". 2015 7th International Conference on New Technologies, Mobility and Security (NTMS). :1-6.

This paper presents a model to evaluate and select security countermeasures from a pool of candidates. The model performs industrial evaluation and simulations of the financial and technical impact associated to security countermeasures. The financial impact approach uses the Return On Response Investment (RORI) index to compare the expected impact of the attack when no response is enacted against the impact after applying security countermeasures. The technical impact approach evaluates the protection level against a threat, in terms of confidentiality, integrity, and availability. We provide a use case on malware attacks that shows the applicability of our model in selecting the best countermeasure against an Advanced Persistent Threat.

G. Kejela, C. Rong.  2015.  "Cross-Device Consumer Identification". 2015 IEEE International Conference on Data Mining Workshop (ICDMW). :1687-1689.

Nowadays, a typical household owns multiple digital devices that can be connected to the Internet. Advertising companies always want to seamlessly reach consumers behind devices instead of the device itself. However, the identity of consumers becomes fragmented as they switch from one device to another. A naive attempt is to use deterministic features such as user name, telephone number and email address. However consumers might refrain from giving away their personal information because of privacy and security reasons. The challenge in ICDM2015 contest is to develop an accurate probabilistic model for predicting cross-device consumer identity without using the deterministic user information. In this paper we present an accurate and scalable cross-device solution using an ensemble of Gradient Boosting Decision Trees (GBDT) and Random Forest. Our final solution ranks 9th both on the public and private LB with F0.5 score of 0.855.

G., Sowmya Padukone, H., Uma Devi.  2020.  Optical Signal Confinement in an optical Sensor for Efficient Biological Analysis by HQF Achievement. 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184). :7—12.
In this paper, a closely packed Biosensor construction by using a two-dimensional structure is described. This structure uses air-holes slab constructed on silicon material. By removing certain air holes in the slab, waveguides are constructed. By carrying out simulation, it is proved that the harmonic guided wave changes to lengthier wavelengths with reagents, pesticides, proteins & DNA capturing. A Biosensor is constructed with an improved Quality factor & wavelength. This gives high Quality Factor (HQF) resolution Biosensor. The approach used for Simulation purpose is Finite Difference Time Domain(FDTD).
G.A, Senthil, Prabha, R., Pomalar, A., Jancy, P. Leela, Rinthya, M..  2021.  Convergence of Cloud and Fog Computing for Security Enhancement. 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :1—6.
Cloud computing is a modern type of service that provides each consumer with a large-scale computing tool. Different cyber-attacks can potentially target cloud computing systems, as most cloud computing systems offer services to so many people who are not known to be trustworthy. Therefore, to protect that Virtual Machine from threats, a cloud computing system must incorporate some security monitoring framework. There is a tradeoff between the security level of the security system and the performance of the system in this scenario. If a strong security is required then a stronger security service using more rules or patterns should be incorporated and then in proportion to the strength of security, it needs much more computing resources. So the amount of resources allocated to customers is decreasing so this research work will introduce a new way of security system in cloud environments to the VM in this research. The main point of Fog computing is to part of the cloud server's work in the ongoing study tells the step-by-step cloud server to change gigantic information measurement because the endeavor apps are relocated to the cloud to keep the framework cost. So the cloud server is devouring and changing huge measures of information step by step so it is rented to keep up the problem and additionally get terrible reactions in a horrible device environment. Cloud computing and Fog computing approaches were combined in this paper to review data movement and safe information about MDHC.
Gaber, C., Vilchez, J. S., Gür, G., Chopin, M., Perrot, N., Grimault, J.-L., Wary, J.-P..  2020.  Liability-Aware Security Management for 5G. 2020 IEEE 3rd 5G World Forum (5GWF). :133—138.

Multi-party and multi-layer nature of 5G networks implies the inherent distribution of management and orchestration decisions across multiple entities. Therefore, responsibility for management decisions concerning end-to-end services become blurred if no efficient liability and accountability mechanism is used. In this paper, we present the design, building blocks and challenges of a Liability-Aware Security Management (LASM) system for 5G. We describe how existing security concepts such as manifests and Security-by-Contract, root cause analysis, remote attestation, proof of transit, and trust and reputation models can be composed and enhanced to take risk and responsibilities into account for security and liability management.

Gabsi, Souhir, Kortli, Yassin, Beroulle, Vincent, Kieffer, Yann, Belgacem, Hamdi.  2022.  Adoption of a Secure ECC-based RFID Authentication Protocol. 2022 IEEE 9th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT). :69–74.
A single RFID (Radio Frequency Identification) is a technology for the remote identification of objects or people. It integrates a reader that receives the information contained in an RFID tag through an RFID authentication protocol. RFID provides several security services to protect the data transmitted between the tag and the reader. However, these advantages do not prevent an attacker to access this communication and remaining various security and privacy issues in these systems. Furthermore, with the rapid growth of IoT, there is an urgent need of security authentication and confidential data protection. Authentication protocols based on elliptic curve cryptographic (ECC) were widely investigated and implemented to guarantee protection against the various attacks that can suffer an RFID system. In this paper, we are going to focus on a comparative study between the most efficient ECC-based RFID authentication protocols that are already published, and study their security against the different wireless attacks.
Gaddam, Venkateswarlu, Das, Dipjyoti, Jeon, Sanghun.  2020.  Ferroelectricity Enhancement in Hf0.5Zr0.5O2 Capacitors by Incorporating Ta2O5 Dielectric Seed Layers. 2020 4th IEEE Electron Devices Technology Manufacturing Conference (EDTM). :1–3.
Recently, dielectric/ferroelectric (DE/FE) bilayer systems have been extensively investigated for achieving high remanent polarization in Hf0.5Zr0.5O2(HZO) based MFM capacitors. Herein, we report significant enhancement in the ferroelectric property of HZO capacitors by incorporating Ta2O5as the dielectric seed layer. Thickness of the Ta2O5layer was incorporated at both top and bottom of the HZO films and the thickness of the seed layer was varied from 10 to 50 Å. When the Ta2O5dielectric films were inserted at the top, the highest remanent polarization 16.83 μC/cm2 was observed in case of 20 Å films as compared to that of 13.21 μC/cm2 of the reference HZO device. Similarly, for bottom Ta2O5dielectric films, the highest remanent polarization 15.24 μC/cm2 was observed in case of 20 Å films. When we compared both the stacks, the best result was observed in case of top Ta2O5. The coercive field (Ec) was also found to be nearly same with the HZO based device despite the incorporation of the dielectric layer. The enhanced ferroelectricity of these devices can be used in memory devices, FeFETs, FTJ and sensors applications.
Gadde, Phani Harsha, Brahma, Sukumar.  2019.  Realistic Microgrid Test Bed for Protection and Resiliency Studies. 2019 North American Power Symposium (NAPS). :1–6.

Momentum towards realization of smart grid will continue to result in high penetration of renewable fed Distributed Energy Resources (DERs) in the Electric Power System (EPS). The drive towards resiliency will enable a modular topology where several microgrids are tied to-gather, operating synchronously to form the future EPS. These microgrids may very well evolve to be fed by 100% Inverter Based Resources (IBRs), and required to operate reliably in both grid-connected and islanded modes. Since microgrids will evolve from existing distribution feeders, they will be unbalanced in terms of load, phases, and feeder-impedances. Protection and control of such microgrids, spanning over grid-connected mode, islanded mode, and transition mode need urgent attention. This paper focuses on the control aspect to facilitate stable operation and power sharing under these modes. A detailed EMTP model of a testbed using the IEEE 13-bus system is created in PSCAD, involving multiple inverters. Control strategy, modes, and implementation of inverter controls are described, and results showing stable operation and power sharing in all modes are presented.

Gadepally, Krishna Chaitanya, Mangalampalli, Sameer.  2021.  Effects of Noise on Machine Learning Algorithms Using Local Differential Privacy Techniques. 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). :1–4.

Noise has been used as a way of protecting privacy of users in public datasets for many decades now. Differential privacy is a new standard to add noise, so that user privacy is protected. When this technique is applied for a single end user data, it's called local differential privacy. In this study, we evaluate the effects of adding noise to generate randomized responses on machine learning models. We generate randomized responses using Gaussian, Laplacian noise on singular end user data as well as correlated end user data. Finally, we provide results that we have observed on a few data sets for various machine learning use cases.

Gadient, P., Ghafari, M., Tarnutzer, M., Nierstrasz, O..  2020.  Web APIs in Android through the Lens of Security. 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER). :13—22.

Web communication has become an indispensable characteristic of mobile apps. However, it is not clear what data the apps transmit, to whom, and what consequences such transmissions have. We analyzed the web communications found in mobile apps from the perspective of security. We first manually studied 160 Android apps to identify the commonly-used communication libraries, and to understand how they are used in these apps. We then developed a tool to statically identify web API URLs used in the apps, and restore the JSON data schemas including the type and value of each parameter. We extracted 9714 distinct web API URLs that were used in 3 376 apps. We found that developers often use the package for network communication, however, third-party libraries like OkHttp are also used in many apps. We discovered that insecure HTTP connections are seven times more prevalent in closed-source than in open-source apps, and that embedded SQL and JavaScript code is used in web communication in more than 500 different apps. This finding is devastating; it leaves billions of users and API service providers vulnerable to attack.

Gaebel, Ethan, Zhang, Ning, Lou, Wenjing, Hou, Y. Thomas.  2016.  Looks Good To Me: Authentication for Augmented Reality. Proceedings of the 6th International Workshop on Trustworthy Embedded Devices. :57–67.

Augmented reality is poised to become a dominant computing paradigm over the next decade. With promises of three-dimensional graphics and interactive interfaces, augmented reality experiences will rival the very best science fiction novels. This breakthrough also brings in unique challenges on how users can authenticate one another to share rich content between augmented reality headsets. Traditional authentication protocols fall short when there is no common central entity or when access to the central authentication server is not available or desirable. Looks Good To Me (LGTM) is an authentication protocol that leverages the unique hardware and context provided with augmented reality headsets to bring innate human trust mechanisms into the digital world to solve authentication in a usable and secure way. LGTM works over point to point wireless communication so users can authenticate one another in a variety of circumstances and is designed with usability at its core, requiring users to perform only two actions: one to initiate and one to confirm. Users intuitively authenticate one another, using seemingly only each other's faces, but under the hood LGTM uses a combination of facial recognition and wireless localization to bootstrap trust from a wireless signal, to a location, to a face, for secure and usable authentication.

Gafencu, L. P., Scripcariu, L., Bogdan, I..  2017.  An overview of security aspects and solutions in VANETs. 2017 International Symposium on Signals, Circuits and Systems (ISSCS). :1–4.

Because of the nature of vehicular communications, security is a crucial aspect, involving the continuous development and analysis of the existing security architectures and punctual theoretical and practical aspects that have been proposed and are in need of continuous updates and integrations with newer technologies. But before an update, a good knowledge of the current aspects is mandatory. Identifying weaknesses and anticipating possible risks of vehicular communication networks through a failure modes and effects analysis (FMEA) represent an important aspect of the security analysis process and a valuable step in finding efficient security solutions for all kind of problems that might occur in these systems.

Gaff, Brian M., Sussman, Heather Egan, Geetter, Jennifer.  2014.  Privacy and Big Data. Computer. 47:7-9.

Big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth. The Web extra at is an audio recording from the Computing and the Law column, in which authors Brian M. Gaff, Heather Egan Sussman, and Jennifer Geetter discuss how big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth.

Gafurov, Davrondzhon, Hurum, Arne Erik.  2020.  Efficiency Metrics and Test Case Design for Test Automation. 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C). :15—23.
In this paper, we present our test automation work applied on national e-health portal for residents in Norway which has over million monthly visits. The focus of the work is threefold: delegating automation tasks and increasing reusability of test artifacts; metrics for estimating efficiency when creating test artifacts and designing robust automated test cases. Delegating (part of) test automation tasks from technical specialist (e.g. programmer - expensive resource) to non-technical specialist (e.g. domain expert, functional tester) is carried out by transforming low level test artifacts into high level test artifacts. Such transformations not only reduce dependency on specialists with coding skills but also enables involving more stakeholders with domain knowledge into test automation. Furthermore, we propose simple metrics which are useful for estimating efficiency during such transformations. Examples of the new metrics are implementation creation efficiency and test creation efficiency. We describe how we design automated test cases in order to reduce the number of false positives and minimize code duplication in the presence of test data challenge (i.e. using same test data both for manual and automated testing). We have been using our test automation solution for over three years. We successfully applied test automation on 2 out of 6 Scrum teams in Helsenorge. In total there are over 120 automated test cases with over 600 iterations (as of today).
Gafurov, Davrondzhon, Hurum, Arne Erik, Markman, Martin.  2018.  Achieving Test Automation with Testers Without Coding Skills: An Industrial Report. Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering. :749–756.
We present a process driven test automation solution which enables delegating (part of) automation tasks from test automation engineer (expensive resource) to test analyst (non-developer, less expensive). In our approach, a test automation engineer implements test steps (or actions) which are executed automatically. Such automated test steps represent user actions in the system under test and specified by a natural language which is understandable by a non-technical person. Then, a test analyst with a domain knowledge organizes automated steps combined with test input to create an automated test case. It should be emphasized that the test analyst does not need to possess programming skills to create, modify or execute automated test cases. We refine benchmark test automation architecture to be better suitable for an effective separation and sharing of responsibilities between the test automation engineer (with coding skills) and test analyst (with a domain knowledge). In addition, we propose a metric to empirically estimate cooperation between test automation engineer and test analyst's works. The proposed automation solution has been defined based on our experience in the development and maintenance of Helsenorg, the national electronic health services in Norway which has had over one million of visits per month past year, and we still use it to automate the execution of regression tests.
Gagliano, Allison, Krawec, Walter O., Iqbal, Hasan.  2019.  From Classical to Semi-Quantum Secure Communication. 2019 IEEE International Symposium on Information Theory (ISIT). :1707—1711.

In this work we introduce a novel QKD protocol capable of smoothly transitioning, via a user-tuneable parameter, from classical to semi-quantum in order to help understand the effect of quantum communication resources on secure key distribution. We perform an information theoretic security analysis of this protocol to determine what level of "quantumness" is sufficient to achieve security, and we discover some rather interesting properties of this protocol along the way.

Gai, K., Qiu, M..  2017.  An Optimal Fully Homomorphic Encryption Scheme. 2017 ieee 3rd international conference on big data security on cloud (bigdatasecurity), ieee international conference on high performance and smart computing (hpsc), and ieee international conference on intelligent data and security (ids). :101–106.

The expeditious expansion of the networking technologies have remarkably driven the usage of the distributedcomputing as well as services, such as task offloading to the cloud. However, security and privacy concerns are restricting the implementations of cloud computing because of the threats from both outsiders and insiders. The primary alternative of protecting users' data is developing a Fully Homomorphic Encryption (FHE) scheme, which can cover both data protections and data processing in the cloud. Despite many previous attempts addressing this approach, none of the proposed work can simultaneously satisfy two requirements that include the non-noise accuracy and an efficiency execution. This paper focuses on the issue of FHE design and proposes a novel FHE scheme, which is called Optimal Fully Homomorphic Encryption (O-FHE). Our approach utilizes the properties of the Kronecker Product (KP) and designs a mechanism of achieving FHE, which consider both accuracy and efficiency. We have assessed our scheme in both theoretical proofing and experimental evaluations with the confirmed and exceptional results.

Gai, Lei, Li, Wendong, Wei, Yu, Yu, Yonghe, Yang, Yang, Zhang, Xinjian, Zhu, Qiming, Wang, Guoyu, Gu, Yongjian.  2021.  Secure underwater optical communications based on quantum technologies. 2021 19th International Conference on Optical Communications and Networks (ICOCN). :1—3.
Underwater wireless optical communications are studied through single photon detection, photon states modulation and quantum key encryption. These studies will promote the development of optical communication applications in underwater vehicles and underwater sensor networks.
Gai, Na, Xue, Kaiping, He, Peixuan, Zhu, Bin, Liu, Jianqing, He, Debiao.  2020.  An Efficient Data Aggregation Scheme with Local Differential Privacy in Smart Grid. 2020 16th International Conference on Mobility, Sensing and Networking (MSN). :73–80.
Smart grid achieves reliable, efficient and flexible grid data processing by integrating traditional power grid with information and communication technology. The control center can evaluate the supply and demand of the power grid through aggregated data of users, and then dynamically adjust the power supply, price of the power, etc. However, since the grid data collected from users may disclose the user's electricity using habits and daily activities, the privacy concern has become a critical issue. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring the trusted third party. In this paper, we propose a privacy-preserving smart grid data aggregation scheme satisfying local differential privacy (LDP) based on randomized response. Our scheme can achieve efficient and practical estimation of the statistics of power supply and demand while preserving any individual participant's privacy. The performance analysis shows that our scheme is efficient in terms of computation and communication overhead.
Gaikwad, Bipin, Prakash, PVBSS, Karmakar, Abhijit.  2021.  Edge-based real-time face logging system for security applications. 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). :1—6.
In this work, we have proposed a state-of-the-art face logging system that detects and logs high quality cropped face images of the people in real-time for security applications. Multiple strategies based on resolution, velocity and symmetry of faces have been applied to obtain best quality face images. The proposed system handles the issue of motion blur in the face images by determining the velocities of the detections. The output of the system is the face database, where four faces for each detected person are stored along with the time stamp and ID number tagged to it. The facial features are extracted by our system, which are used to search the person-of-interest instantly. The proposed system has been implemented in a docker container environment on two edge devices: the powerful NVIDIA Jetson TX2 and the cheaper NVIDIA Jetson N ano. The light and fast face detector (LFFD) used for detection, and ResN et50 used for facial feature extraction are optimized using TensorRT over these edge devices. In our experiments, the proposed system achieves the True Acceptance Rate (TAR) of 0.94 at False Acceptance Rate (FAR) of 0.01 while detecting the faces at 20–30 FPS on NVIDIA Jetson TX2 and about 8–10 FPS on NVIDIA Jetson N ano device. The advantage of our system is that it is easily deployable at multiple locations and also scalable based on application requirement. Thus it provides a realistic solution to face logging application as the query or suspect can be searched instantly, which may not only help in investigation of incidents but also in prevention of untoward incidents.
Gaikwad, Nikhil B., Ugale, Hrishikesh, Keskar, Avinash, Shivaprakash, N. C..  2020.  The Internet-of-Battlefield-Things (IoBT)-Based Enemy Localization Using Soldiers Location and Gunshot Direction. IEEE Internet of Things Journal. 7:11725–11734.
The real-time information of enemy locations is capable to transform the outcome of combat operations. Such information gathered using connected soldiers on the Internet of Battlefield Things (IoBT) is highly beneficial to create situational awareness (SA) and to plan an effective war strategy. This article presents the novel enemy localization method that uses the soldier's own locations and their gunshot direction. The hardware prototype has been developed that uses a triangulation for an enemy localization in two soldiers and a single enemy scenario. 4.24±1.77 m of average localization error and ±4° of gunshot direction error has been observed during this prototype testing. This basic model is further extended using three-stage software simulation for multiple soldiers and multiple enemy scenarios with the necessary assumptions. The effective algorithm has been proposed, which differentiates between the ghost and true predictions by analyzing the groups of subsequent shooting intents (i.e., frames). Four different complex scenarios are tested in the first stage of the simulation, around three to six frames are required for the accurate enemy localization in the relatively simple cases, and nine frames are required for the complex cases. The random error within ±4° in gunshot direction is included in the second stage of the simulation which required almost double the number of frames for similar four cases. As the number of frames increases, the accuracy of the proposed algorithm improves and better ghost point elimination is observed. In the third stage, two conventional clustering algorithms are implemented to validate the presented work. The comparative analysis shows that the proposed algorithm is faster, computationally simple, consistent, and reliable compared with others. Detailed analysis of hardware and software results for various scenarios has been discussed in this article.
Gaikwad, V. S., Gandle, K. S..  2017.  Ideal complexity cryptosystem with high privacy data service for cloud databases. 2017 1st International Conference on Intelligent Systems and Information Management (ICISIM). :267–270.

Data storage in cloud should come along with high safety and confidentiality. It is accountability of cloud service provider to guarantee the availability and security of client data. There exist various alternatives for storage services but confidentiality and complexity solutions for database as a service are still not satisfactory. Proposed system gives alternative solution for database as a service that integrates benefits of different services along with advance encryption techniques. It yields possibility of applying concurrency on encrypted data. This alternative provides supporting facility to connect dispersed clients with elimination of intermediate proxy by which simplicity can acquired. Performance of proposed system evaluated on basis of theoretical analyses.