International Journal of Communication Networks and Information Security (IJCNIS)
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1021 research outputs found
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Muti-stage Key Management Scheme for Cluster based WSN
Secured communication over the Wireless Sensor Network (WSN) is one of the prime concerns nowadays as the wireless communication medium suffers under a wide range of networks. For establishing secured communication over WSN, literature has suggested the key level management protocol, where each transmission is established based on the availability of secured key. This work develops a key management protocol, namely Multi stage key management (MSKM) protocol, for the secured communication over the clustered WSN. The entire protocol is implemented in three stages, such as pre-deployment, key generation, and key authentication and verification. In the first stage, the nodes are provided with the identity, and then, the second stage uses the homomorphic encryption model, for generating the necessary key to the communication. Finally, a mathematical model is developed in this work with several factors, such as a hashing function, homomorphic encryption, dynamic passwords, profile sequence, random number, and EX-OR functions. The proposed MSKM protocol establishes the secured communication over the WSN by authenticating the entities. The entire work is compared with several states of art techniques and evaluated based on several metrics. The proposed MSKM protocol achieved values of 0.122 kb, 0.929, 2.332 kb, and 14.586 joules for the communication overhead, detection accuracy, key memory storage, and energy, respectively
Security based partner selection in Inter-organizational workflow systems
The creation of inter-organizational workflow implies the coalition of partners' efforts and resources in order to achieve a set of common objectives and goals. However, this openness may cause a huge damage to the participating entities due to security breaches. The risk of unsuccessful collaboration should be well studied. Thus, the key for successful collaboration is to select the appropriate collaborators based on specific security criteria for each outsourced task. In this sense, several criteria have to be considered, among them: trust and reputation level, policy similarity level, security level and privacy compliance level. The proposed security based partner selection approach allows us to rank participating entities in the collaboration based on the main security criteria in order to assign each task to the suitable partner with the most appropriate and efficient way
Dexterity for Channel Capacity Enhancement in MU-MIMO by Abrogating Interference
The looming field of Multi user Multiple-input Multiple-output (MU-MIMO) communication system has faced a challenge with precoding techniques for achieving increased channel capacity of their less inhaling of signals, imperfect knowing of channel state information, loss of signals by noise ,time complexity etc. in downlink systems which results in interference to the users. Hence straight forwarding from the issues, the paper newly introduce2LB-FR precoding technique which holds Linde-Lyold’s (LL)algorithm to increase data transmission by consuming large amount of signals with space and the Bernoulli distribution with Bayes decision (BB) to allot the perfect channel state; l information during transmission that eliminates co-interference. Holding Floyd Rasta (FR) algorithm expels the noise if added and takes the shortest required path by acquiring all the possible routes available in single execution which decreases delay. By the overall implementation, the proposed work pomped that in short time ,the capacity of the channel get enhanced with interference cancellation
SecNetworkCloudSim: An Extensible Simulation Tool for Secure Distributed Mobile Applications
Fueled by the wide interest for achieving rich-storage services with the lowest possible cost, cloud computing has emerged into a highly desired service paradigm extending well beyond Virtualization technology. The next generation of mobile cloud services is now manipulated more and more sensitive data on VM-based distributed applications. Therefore, the need to secure sensitive data over mobile cloud computing is more evident than ever. However, despite the widespread release of several cloud simulators, controlling user’s access and protecting data exchanges in distributed mobile applications over the cloud is considered a major challenge. This paper introduces a new NetworkCloudSim extension named SecNetworkCloudSim, a secure mobile simulation tool which is deliberately designed to ensure the preservation of confidential access to data hosted on mobile device and distributed cloud’s servers. Through high-level mobile users’ requests, users connect to an underlying proxy which is considered an important layer in this new simulator, where users perform secure authentication access to cloud services, allocate their tasks in secure VM-based policy, manage automatically the data confidentiality among VMs and derive high efficiency and coverage rates. Most importantly, due to the secure nature of proxy, user’s distributed tasks can be executed without alterations on different underlying proxy’s security policies. We implement a scenario of follow-up healthcare distributed application using the new extension
A Classification of non-Cryptographic Anonymization Techniques Ensuring Privacy in Big Data
Recently, Big Data processing becomes crucial to most enterprise and government applications due to the fast growth of the collected data. However, this data often includes private personal information that arise new security and privacy concerns. Moreover, it is widely agreed that the sheer scale of big data makes many privacy preserving techniques unavailing. Therefore, in order to ensure privacy in big data, anonymization is suggested as one of the most efficient approaches. In this paper, we will provide a new detailed classification of the most used non-cryptographic anonymization techniques related to big data including generalization and randomization approaches. Besides, the paper evaluates the presented techniques through integrity, confidentiality and credibility criteria. In addition, three relevant anonymization techniques including k-anonymity, l-diversity and t-closeness are tested on an extract of a huge real data set
The Impact of selfishness Attack on Mobile Ad Hoc Network
Mobile Ad-Hoc Network (MANET) is an infrastructure-less network that has the ability to configure itself without any centralized management. The topology of MANET changes dynamically which makes it open for new nodes to join it easily. The openness area of MANET makes it very vulnerable to different types of attacks. One of the most dangerous attacks is selfishness attack. In this type of attack, each node tries to save its resources, behave selfishly or non-cooperatively by not forwarding packets that are generated by other nodes. Routing in MANET is susceptible to selfishness attack and this is a crucial issue which deserves to be studied and solved. Therefore, the main objective of this paper is to study the impact of selfishness attack on two routing protocols namely, Ad hoc On-Demand Distance Vector (AODV) and Destination Sequenced Distance Vector (DSDV), as a try to find the most resistant routing protocol to such attack. The contribution of this paper is a new Selfishness Attack Model (SAM) which applies selfishness attack on the two chosen routing protocols in the NS-2 simulator. According to the conducted simulation results, AODV shows higher performance than DSDV under the effect of selfishness attack
Cyber Security Concerns in Social Networking Service
Today’s world is unimaginable without online social networks. Nowadays, millions of people connect with their friends and families by sharing their personal information with the help of different forms of social media. Sometimes, individuals face different types of issues while maintaining the multimedia contents like, audios, videos, photos because it is difficult to maintain the security and privacy of these multimedia contents uploaded on a daily basis. In fact, sometimes personal or sensitive information could get viral if that leaks out even unintentionally. Any leaked out content can be shared and made a topic of popular talk all over the world within few seconds with the help of the social networking sites. In the setting of Internet of Things (IoT) that would connect millions of devices, such contents could be shared from anywhere anytime. Considering such a setting, in this work, we investigate the key security and privacy concerns faced by individuals who use different social networking sites differently for different reasons. We also discuss the current state-of-the-art defense mechanisms that can bring somewhat long-term solutions to tackling these threats
Symmetric Encryption Algorithms: Review and Evaluation Study
The increased exchange of data over the Internet in the past two decades has brought data security and confidentiality to the fore front. Information security can be achieved by implementing encryption and decryption algorithms to ensure data remains secure and confidential, especially when transmitted over an insecure communication channel. Encryption is the method of coding information to prevent unauthorized access and ensure data integrity and confidentiality, whereas the reverse process is known as decryption. All encryption algorithms aim to secure data, however, their performance varies according to several factors such as file size, type, complexity, and platform used. Furthermore, while some encryption algorithms outperform others, they have been proven to be vulnerable against certain attacks. In this paper, we present a general overview of common encryption algorithms and explain their inner workings. Additionally, we select ten different symmetric encryption algorithms and conduct a simulation in Java to test their performance. The algorithms we compare are: AES, BLOWFISH, RC2, RC4, RC6, DES, DESede, SEED, XTEA, and IDEA. We present the results of our simulation in terms of encryption speed, throughput, and CPU utilization rate for various file sizes ranging from 1MB to 1GB. We further analyze our results for all measures that have been tested, taking into account the level of security they provide
EVHS - Elastic Virtual Honeypot System for SDNFV-Based Networks
The SDNFV-based network has leveraged the advantages of software-defined networking (SDN) and network-function virtualization (NFV) to become the most prominent network architecture. However, with the advancement of the SDNFV-based network, more attack types have emerged. This research focuses on one of the methods (use of the honeypot system) of preventing these attacks on the SDNFV-based network. We introduce an SDNFV-based elastic virtual honeypot system (EVHS), which not only resolves problems of other current honeypot systems but also employs a new approach to efficiently manage and control honeypots. It uses a network-intrusion-detection system (NIDS) at the border of the network to detect attacks, leverages the advantages of SDN and NFV to flexibly generate honeypots, and connects attackers to these honeypots by using a moving-target defense mechanism. Furthermore, we optimize the system to efficiently reuse the available honeypots after the attacks are handled. Experimental results validate that the proposed system is a flexible and efficient approach to manage and provide virtual honeypots in the SDNFV-based network; the system can also resolve the problems encountered by current honeypot systems
Mobile Malware Behaviour through Opcode Analysis
As the popularity of mobile devices are on the rise, millions of users are now exposed to mobile malware threats. Malware is known for its ability in causing damage to mobile devices. Attackers often use it as a way to use the resources available and for other cybercriminal benefits such stealing users’ data, credentials and credit card number. Various detection techniques have been introduced in mitigating mobile malware, yet the malware author has its own method to overcome the detection method. This paper presents mobile malware analysis approaches through opcode analysis. Opcode analysis on mobile malware reveals the behaviour of malicious application in the binary level. The comparison made between the numbers of opcode occurrence from a malicious application and benign shows a significance traits. These differences can be used in classifying the malicious and benign mobile application