Secure Cloud Computing

Secure distributed data storage can shift the burden of maintaining a large number of files from the owner to proxy servers. Proxy servers can convert encrypted files for the owner to encrypted files for the receiver without the necessity of knowing the content of the original files. In practice, the original files will be removed by the owner for the sake of space efficiency. Hence, the issues on confidentiality and integrity of the outsourced data must be addressed carefully. In this paper, we propose two identity-based secure distributed data storage (IBSDDS) schemes.

A number of studies on privacy-preserving data mining have been proposed. Most of them assume that they can separate quasi-identifiers (QIDs) from sensitive attributes. For instance, they assume that address, job, and age are QIDs but are not sensitive attributes and that a disease name is a sensitive attribute but is not a QID. However, all of these attributes can have features that are both sensitive attributes and QIDs in practice. In this paper, we refer to these attributes as sensitive QIDs and we propose novel privacy models, namely, (l1, …, lq)-diversity and (t1, …, tq)-closeness, and a method that can treat sensitive QIDs. Our method is composed of two algorithms: an anonymization algorithm and a reconstruction algorithm. The anonymization algorithm, which is conducted by data holders, is simple but effective, whereas the reconstruction algorithm, which is conducted by data analyzers, can be conducted according to each data analyzer's objective. Our proposed method was experimentally evaluated using real data sets.

11 th International Conference on Cryptography and Information Security (CRYPIS 2022) focuses on cutting-edge results in Applied Cryptography and Information security. It aims to bring together scientists, researchers and students to exchange novel ideas and results in all aspects of Cryptography, Coding and Information security. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

International Journal of Wireless Network Security (IJWNS) 
http://flyccs.com/jounals/IJWNS/Home.html
Scope
International Journal of Wireless Network Security (IJWNS) is a open access journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications. ________________________________________
Topics of interest include, but are not limited to, the following

• Cryptographic protocols
• Cryptography and Coding
• Untraceability
• Privacy and authentication
• Key management
• Authentication
• Trust Management
• Quantum cryptography
• Computational Intelligence in Security
• Artificial Immune Systems
• Biological & Evolutionary Computation
• Intelligent Agents and Systems
• Reinforcement & Unsupervised Learning
• Autonomy-Oriented Computing
• Coevolutionary Algorithms
• Fuzzy Systems
• Biometric Security
• Trust models and metrics
• Regulation and Trust Mechanisms
• Data Integrity
• Models for Authentication, Trust and Authorization
• Information Hiding • Information Hiding
• Data & System Integrity
• E- Commerce
• Access Control and Intrusion Detection
• Intrusion Detection and Vulnerability Assessment
• Authentication and Non-repudiation
• Identification and Authentication
• Insider Threats and Countermeasures
• Intrusion Detection & Prevention
• Secure Cloud Computing
• Security Information Systems Architecture and Design and Security Patterns
• Security Management
• Cryptography and Information Security
• Security Requirements (threats, vulnerabilities, risk, formal methods, etc.)
• Sensor and Mobile Ad Hoc Network Security
• Service and Systems Design and QoS Network Security
• Software Security
• Security and Privacy in Mobile Systems
• Security and Privacy in Pervasive/Ubiquitous Computing
• Security and Privacy in Web Sevices
• Security and Privacy Policies
• Security Area Control
• Security Deployment
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For paper format download the template in this page Manuscript Template
Important Dates
• Submission Deadline : August 10, 2018
• Notification :September 10, 2018
• Final Manuscript Due : September 18, 2018
• Publication Date : Determined by the Editor-in-Chief
TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us : jwnsjournal@yahoo.com(or) jwnsjjournal@gmail.com

11 th International Conference on Cryptography and Information Security (CRYPIS 2022) focuses on cutting-edge results in Applied Cryptography and Information security. It aims to bring together scientists, researchers and students to exchange novel ideas and results in all aspects of Cryptography, Coding and Information security. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

10th International Conference on Cryptography and Information Security (CRYPIS 2021)
focuses on cutting-edge results in Applied Cryptography and Information security. It aims to bring
together scientists, researchers and students to exchange novel ideas and results in all aspects of
Cryptography, Coding and Information security.

To buy this project in ONLINE, Contact:
Email: jpinfotechprojects@gmail.com,
Website: https://www.jpinfotech.org

A Hybrid E-learning Recommendation Approach Based on Learners' Influence Propagation

In e-learning recommender systems, interpersonal information between learners is very scarce, which makes it difficult to apply collaborative filtering (CF) techniques. In this study, we propose a hybrid filtering (HF) recommendation approach (SI-IFL) combining learner influence model (LIM), self-organization based (SOB) recommendation strategy and sequential pattern mining (SPM) together for recommending learning objects (LOs) to learners. The method works as follows: (i), LIM is applied to acquire the interpersonal information by computing the influence that a learner exerts on others. LIM consists of learner similarity, knowledge credibility, and learner aggregation. LIM is independent of ratings. Furthermore, to address the uncertainty and fuzzy natures of learners, intuitionistic fuzzy logic (IFL) is applied to optimize the LIM. (ii), a SOB recommendation strategy is applied to recommend the optimal learner cliques for active learners by simulating the influence propagation among learners. Influence propagation means that a learner can move toward active learners, and such behaviors can stimulate the moving behaviors of his neighbors. This SOB recommendation approach achieves a stable structure based on distributed and bottom-up behaviors of individuals. (iii), SPM is applied to decide the final learning objects (LOs) and navigational paths based on the recommended learner cliques. The experimental results demonstrate that SI-IFL can provide personalized and diversified recommendations, and it shows promising efficiency and adaptability in e-learning scenarios. SYSTEM REQUIREMENTS:

Security has been considered as the key concern of adopting cloud computing. This could be ascribed to the customers’ lack of control over their confidential data once in the cloud and to the absence of trust in cloud providers. Unfortunately, the research efforts in the area of cloud security have not yet succeeded to give the required ”peace of mind” to cloud customers. Therefore, in an attempt to figure out the main loopholes in cloud security, this paper questions the  fundamental principles of the security approaches in the cloud. The paper highlights two main drawbacks; the first is due to a potential incompatibility among security measures, while the other is due to the focus on securing the  infrastructure rather than the data itself. Therefore, the paper advocates the need for integrating information-centric security approaches, and hence presents a novel security framework that adopts both infrastructure and
information-centric security services.

The multihop routing in wireless sensor networks (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful or even devastating attacks against the routing protocols, including sinkhole attacks, wormhole attacks, and Sybil attacks. The situation is further aggravated by mobile and harsh network conditions. Traditional cryptographic techniques or efforts at developing trustaware routing protocols do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multihop routing, we have designed and implemented TARF, a robust trust-aware routing framework for dynamic WSNs. Without tight time synchronization or known geographic information, TARF provides trustworthy and energyefficient route. Most importantly, TARF proves effective against those harmful attacks developed out of identity deception; the resilience of TARF is verified through extensive evaluation with both simulation and empirical experiments on large-scale WSNs under various scenarios including mobile and RF-shielding network conditions. Further, we have implemented a low-overhead TARF module in TinyOS; as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. Based on TARF, we also demonstrated a proof-of-concept mobile target detection application that functions well against an antidetection mechanism.

With the expanding interest for constant applications in the Wireless Senor Network (WSN), ongoing discriminating occasions suspect a proficient quality-of-service (QoS) based Routing for information conveyance from the Network foundation. Outlining such QoS based Routing convention to meet the unwavering quality and postponement certification of discriminating occasions while protecting the vitality effectiveness is a testing assignment. Impressive exploration has been centred on creating hearty vitality productive QoS based Routing conventions. In this paper, we tended to a remote crossover arrange that incorporates a mobile wireless ad hoc network (MANET) and a wireless infrastructure network has been turned out to be a finer option for the cutting edge remote Networks. By straight forwardly embracing asset reservation-based QoS Routing for MANETs, half breeds Networks inherit invalid reservation and race condition issues in MANETs. Instructions to ensure the QoS in cross breed Networks remains an open issue. In this paper, we propose QoS-Oriented Distributed routing protocol (QOD) to upgrade the QoS help capacity of hybrid Networks.

Cloud computing is quickly becoming the platform of choice for many web services. Virtualization is the key underlying technology enabling cloud providers to host services for a large number of customers. Unfortunately, virtualization software is large, complex, and has a considerable attack surface. As such, it is prone to bugs and vulnerabilities that a malicious virtual machine (VM) can exploit to attack or obstruct other VMs -a major concern for organizations wishing to move "to the cloud." In contrast to previous work on hardening or minimizing the virtualization software, we eliminate the hypervisor attack surface by enabling the guest VMs to run natively on the underlying hardware while maintaining the ability to run multiple VMs concurrently. Our NoHype system embodies four key ideas: (i) pre-allocation of processor cores and memory resources, (ii) use of virtualized I/O devices, (iii) minor modifications to the guest OS to perform all system discovery during bootup, and (iv) avoiding indirection by bringing the guest virtual machine in more direct contact with the underlying hardware. Hence, no hypervisor is needed to allocate resources dynamically, emulate I/O devices, support system discovery after bootup, or map interrupts and other identifiers. NoHype capitalizes on the unique use model in cloud computing, where customers specify resource requirements ahead of time and providers offer a suite of guest OS kernels. Our system supports multiple tenants and capabilities commonly found in hosted cloud infrastructures. Our prototype utilizes Xen 4.0 to prepare the environment for guest VMs, and a slightly modified version of Linux 2.6 for the guest OS. Our evaluation with both SPEC and Apache benchmarks shows a roughly 1% performance gain when running applications on NoHype compared to running them on top of Xen 4.0. Our security analysis shows that, while there are some minor limitations with current commodity hardware, NoHype is a significant advance in the security of cloud computing.

Security has been considered as the key concern of adopting cloud computing. This could be ascribed to the customers' lack of control over their confidential data once in the cloud and to the absence of trust in cloud providers. Unfortunately, the research efforts in the area of cloud security have not yet succeeded to give the required "peace of mind" to cloud customers. Therefore, in an attempt to figure out the main loopholes in cloud security, this paper questions the fundamental principles of the security approaches in the cloud. The paper highlights two main drawbacks; the first is due to a potential incompatibility among security measures, while the other is due to the focus on securing the infrastructure rather than the data itself. Therefore, the paper advocates the need for integrating information-centric security approaches, and hence presents a novel security framework that adopts both infrastructure and information-centric security services.

Intentional or unintentional leakage of confidential data is undoubtedly one of the most severe security threats that organizations face in the digital era. The threat now extends to our personal lives: a plethora of personal information is available to social networks and smartphone providers and is indirectly transferred to untrustworthy third party and fourth party applications.

Mobile Ad hoc Networks (MANET) have been highly vulnerable to attacks due to the dynamic nature of its network infrastructure. Among these attacks, routing attacks have received considerable attention since it could cause the most devastating damage to MANET. Even though there exist several intrusion response techniques to mitigate such critical attacks, existing solutions typically attempt to isolate malicious nodes based on binary or naı¨ve fuzzy response decisions. However, binary responses may result in the unexpected network partition, causing additional damages to the network infrastructure, and naı¨ve fuzzy responses could lead to uncertainty in countering routing attacks in MANET. In this paper, we propose a risk-aware response mechanism to systematically cope with the identified routing attacks. Our risk-aware approach is based on an extended Dempster-Shafer mathematical theory of evidence introducing a notion of importance factors. In addition, our experiments demonstrate the effectiveness of our approach with the consideration of several performance metrics. EXISTING SYSTEM: Several work addressed the intrusion response actions in MANET by isolating uncooperative nodes based on the node reputation derived from their behaviors. Such a simple response against malicious nodes often neglects possible negative side effects involved with the response actions. In MANET scenario, improper countermeasures may cause the unexpected network partition, bringing additional damages to the network infrastructure. To address the above-mentioned critical issues, more flexible and adaptive response should be investigated. The notion of risk can be adopted to support more adaptive responses to routing attacks in MANET. Subjective

Online social networks gradually integrate financial capabilities by enabling the usage of real and virtual currency. They serve as new platforms to host a variety of business activities such as online promotion events, where users can possibly get virtual currency as rewards by participating such events. Both OSNs and business partners are significantly concerned when attackers instrument a set of accounts to collect virtual currency from these events, which make these events ineffective and result in significant financial loss. It becomes of great importance to proactively detecting these malicious accounts before the online promotion activities and subsequently decrease their priority to be rewarded. In this paper, we propose a novel system, namely ProGuard, to accomplish this objective by systematically integrating features that characterize accounts from three perspectives including their general behaviors, their recharging patterns, and the usage of their currency. We have performed extensive experiments based on data collected from Tencent QQ, a global leading OSN with built-in financial management activities. Experimental results have demonstrated that our system can accomplish a high detection rate of 96.67% at a very low false positive rate of 0.3%. EXISTING SYSTEM:  Lin et al. ranked the importance of fraud factors used in financial statement fraud detection, and investigated the correct classification rates of three algorithms including Logistic Regression, Decision Trees, and Artificial Neural Networks.

Model combination in classification, density estimation and clustering and forecasting has become a promising research area where better results are obtained compared to using single models. Bayesian inference offers two approaches for combining models; Bayesian model averaging (BMA), and Supra-Bayesian classifier combination (SBCC). In this paper we briefly overview the BMA, show its drawbacks, and propose a novel idea of Bayesian data/model averaging. Then, the SBCC technique is explained, and its implementation used in this work is presented. A novel approach is proposed where input space is clustered before applying the SBCC. A 2-dimensional, 2-class, 4-experts problem is used to test the SBCC and SBCC-clustering algorithms, where better results are obtained over 300 runs for the data set, compared to an averaging technique, where the 4 experts’ performance is averaged.

International Journal of Wireless Network Security (IJWNS) 
http://flyccs.com/jounals/IJWNS/Home.html
Scope
International Journal of Wireless Network Security (IJWNS) is a open access journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications. ________________________________________
Topics of interest include, but are not limited to, the following
• Cryptographic protocols
• Cryptography and Coding
• Untraceability
• Privacy and authentication
• Key management
• Authentication
• Trust Management
• Quantum cryptography
• Computational Intelligence in Security
• Artificial Immune Systems
• Biological & Evolutionary Computation
• Intelligent Agents and Systems
• Reinforcement & Unsupervised Learning
• Autonomy-Oriented Computing
• Coevolutionary Algorithms
• Fuzzy Systems
• Biometric Security
• Trust models and metrics
• Regulation and Trust Mechanisms
• Data Integrity
• Models for Authentication, Trust and Authorization
• Information Hiding • Information Hiding
• Data & System Integrity
• E- Commerce
• Access Control and Intrusion Detection
• Intrusion Detection and Vulnerability Assessment
• Authentication and Non-repudiation
• Identification and Authentication
• Insider Threats and Countermeasures
• Intrusion Detection & Prevention
• Secure Cloud Computing
• Security Information Systems Architecture and Design and Security Patterns
• Security Management
• Cryptography and Information Security
• Security Requirements (threats, vulnerabilities, risk, formal methods, etc.)
• Sensor and Mobile Ad Hoc Network Security
• Service and Systems Design and QoS Network Security
• Software Security
• Security and Privacy in Mobile Systems
• Security and Privacy in Pervasive/Ubiquitous Computing
• Security and Privacy in Web Sevices
• Security and Privacy Policies
• Security Area Control
• Security Deployment•
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For paper format download the template in this page Manuscript Template
Important Dates
• Submission Deadline : August 31, 2018
• Notification :September 30, 2018
• Final Manuscript Due : October 06, 2018
• Publication Date : Determined by the Editor-in-Chief
TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us : jwnsjournal@yahoo.com(or) jwnsjjournal@gmail.com

Cloud computing is quickly becoming the platform of choice for many web services. Virtualization is the key underlying technology enabling cloud providers to host services for a large number of customers. Unfortunately, virtualization software is large, complex, and has a considerable attack

An algorithm for anonymous sharing of private data among parties is developed. This technique is used iteratively to assign these nodes ID numbers ranging from 1 to N. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access. The required computations are distributed without using a trusted central authority. Existing and new algorithms for assigning anonymous IDs are examined with respect to trade-offs between communication and computational requirements. The new algorithms are built on top of a secure sum data mining operation using Newton's identities and Sturm's theorem. An algorithm for distributed solution of certain polynomials over finite fields enhances the scalability of the algorithms. Markov chain representations are used to find statistics on the number of iterations required, and computer algebra gives closed form results for the completion rates. EXISTING SYSTEM: A secure computation function widely used in the literature is secure sum that allows parties to compute the sum of their individual inputs without disclosing the inputs to one another. This function is popular in data mining applications and also helps characterize the complexities of the secure multiparty computation.

Cloud security is one of most important issues that have attracted a lot of research and development effort in past few years. Particularly, attackers can explore vulnerabilities of a cloud system and compromise virtual machines to deploy further large-scale Distributed Denial-of-Service (DDoS). DDoS attacks usually involve early stage actions such as multi-step exploitation, low frequency vulnerability scanning, and compromising identified vulnerable virtual machines as zombies, and finally DDoS attacks through the compromised zombies. Within the cloud system, especially the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is extremely difficult. This is because cloud users may install vulnerable applications on their virtual machines. To prevent vulnerable virtual machines from being compromised in the cloud, we propose a multi-phase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph based analytical models and reconfigurable virtual network-based countermeasures. The proposed framework leverages Open Flow network programming APIs to build a monitor and control plane over distributed programmable virtual switches in order to significantly improve attack detection and mitigate attack consequences. The system and security evaluations demonstrate the efficiency and effectiveness of the proposed solution. AIM

Photo sharing is an attractive feature which popularizes Online Social Networks (OSNs). Unfortunately, it may leak users' privacy if they are allowed to post, comment, and tag a photo freely.we attempt to address this issue and study the scenario when a user shares a photo containing individuals other than himself/herself (termed co-photo for short). To prevent possible privacy leakage of a photo, we design a mechanism to enable each individual in a photo be aware of the posting activity and participate in the decision making on the photo posting. For this purpose, we need an efficient facial recognition (FR) system that can recognize everyone in the photo. However, more demanding privacy setting may limit the number of the photos publicly available to train the FR system. To deal with this dilemma, our mechanism attempts to utilize users' private photos to design a personalized FR system specifically trained to differentiate possible photo co-owners without leaking their privacy. We also develop a distributed consensusbased method to reduce the computational complexity and protect the private training set. We show that our system is superior to other possible approaches in terms of recognition ratio and efficiency.

Broadcast encryption (BE) schemes allow a sender to securely broadcast to any subset of members but require a trusted party to distribute decryption keys. Group key agreement (GKA) protocols enable a group of members to negotiate a common encryption key via open networks so that only the group members can decrypt the ciphertexts encrypted under the shared encryption key, but a sender cannot exclude any particular member from decrypting the ciphertexts. In this paper, we bridge these two notions with a hybrid primitive referred to as contributory broadcast encryption (ConBE). In this new primitive, a group of members negotiate a common public encryption key while each member holds a decryption key. A sender seeing the public group encryption key can limit the decryption to a subset of members of his choice.

Understanding the spreading dynamics of computer viruses (worms, attacks) is an important research problem, and has received much attention from the communities of both computer security and statistical physics. However, previous studies have mainly focused on single-virus spreading dynamics. In this paper, we study multi-virus spreading dynamics, where multiple viruses attempt to infect computers while possibly combating against each other because, for example, they are controlled by multiple bot masters. Specifically, we propose and analyze a general model (and its two special cases) of multi-virus spreading dynamics in arbitrary networks (i.e., we do not make any restriction on network topologies), where the viruses may or may not core side on computers. Our model offers analytical results for addressing questions such as: What are the sufficient conditions (also known as epidemic thresholds) under which the multiple viruses will die out? What if some viruses can "rob" others? What characteristics does the multivirus epidemic dynamics exhibit when the viruses are (approximately) equally powerful? The analytical results make a fundamental connection between two types of factors: defense capability and network connectivity. This allows us to draw various insights that can be used to guide security defense.

Model combination in classification, density
estimation and clustering and forecasting has
become a promising research area where better
results are obtained compared to using single
models. Bayesian inference offers two
approaches for combining models; Bayesian
model averaging (BMA), and Supra-Bayesian
classifier combination (SBCC). In this paper
we briefly overview the BMA, show its
drawbacks, and propose a novel idea of
Bayesian data/model averaging. Then, the
SBCC technique is explained, and its
implementation used in this work is presented.
A novel approach is proposed where input
space is clustered before applying the SBCC.
A 2-dimensional, 2-class, 4-experts problem is
used to test the SBCC and SBCC-clustering
algorithms, where better results are obtained
over 300 runs for the data set, compared to an
averaging technique, where the 4 experts’
performance is averaged.

Social network is a group of individuals with diverse social interactions amongst them. The network large scale and distributed due to Quantitative analysis of networks is need of and in turn the society. Clustering helps us to group people with similar characteristics dense social networks. We have considered similarity measures for statistical When a social network is represented as a graph with members as nodes and their relation as edges, graph mining would be suitable for statistical analysis. We have chosen academic social network nodesto simplify network analysis. similaritybetween unstructured data elements extracted from social network.