Technology known as the Industrial Internet of Things (IIoT) is becoming more important to businesses as a means of boosting productivity and making more educated decisions about their operations. Despite the fact that connected environments provide significant advantages to companies, users of IIoT are especially susceptible to incursions on account of a few key characteristics. To begin, there will be an increase in the number of entry points into industrial systems when there are more linked endpoints. There is also the problem of functioning equipment being modified for applications it was never intended for, communication methods that are vulnerable, and software-hardware configurations that considerably vary across businesses and industries. The most current research in the area of Internet of Things (IIoT) cybersecurity is thoroughly reviewed in this article. Data protection through encryption techniques, using deep learning and machine learning approaches to detect attacks on the IIoT network, and implementing honeypot designs as a preventative measure to safeguard against data loss during potential cyberattacks are the main areas of focus for the research.

The industrial internet of things (IIoT) refers to a system of interconnected equipment, sensors, and devices deployed within industrial environments whose primary function is to collect and facilitate the exchange of data. IIoT has gained significant traction in several domains, encompassing remote monitoring, equipment management, and condition tracking. The utilization of IIoT in different environments gives rise to apprehensions regarding the security of data. As a result of this, it is imperative to ensure that rigorous safety measures are in place to safeguard the confidentiality of the sensitive information being transmitted. The utilization of elliptic curve cryptography (ECC) and quantum key exchange (QKE) in IIoT networks holds promise for achieving robust and predictable security measures. ECC is a widely adopted type of public-key cryptography due to its efficiency and security. It has gained significant popularity in contemporary systems. QKE is an innovative methodology that originates from the fundamental principles of quantum physics. The system has the ability to generate a secret key that is impervious to hacking attempts, as it leverages natural principles instead of conventional mathematical procedures. Due to this characteristic, quantum key distribution (QKD) is widely recognized as one of the most reliable methods for key exchange. The combination has led to the creation of a novel cryptographic model that integrates elliptic curve cryptography (ECC) and quantum key exchange (QKE) techniques for the generation and distribution of cryptographic keys. The model leads to an increase in the base probability of the Bennett–Brassard protocol (BB84) from 0.5 to 1. Subsequently, the keys that are produced are employed for the encryption of data through a streamlined and adapted variant of the Advanced Encryption Standard (AES), thereby expediting the secure exchange of data while upholding its level of safeguarding.

There have been many developments in recent years based on the Internet of Things (IoT), particularly for managing data pertaining to healthcare as it is now known as the Internet of Health Things (IoHT). As those healthcare data ensure improved accuracy, security with enhanced integrity, and better quality data, some these data must be provisioned to such smart healthcare, which is a time-consuming problem in this organization. To improve data provisioning, data must be more secure and privacy protected, as enabled by federated learning and privacy policies. If the data is private, it is possible to learn about it with the owner’s consent. With recent advancements, data process flow related to IoHT is associated with various IoT devices as edge nodes. As there is a problem with a partial level of trained nodes, learning at the nodes is much more difficult as it requires a fully decentralized environment, improved and trained datasets, data provisioning, and security. In this paper, a Hy-FL-based Blockchain approach is suggested because it can manage trust and trained data based on federated learning with better authentication thanks to blockchain technology. This proposed approach enables the encryption of trained data on federated nodes and aggregated data. In the analysis, IoHT-based data manageability is handled safely in terms of energy use, data accuracy, predicated value, etc.

The widespread use of networks in industrial control systems has led to a number of problems, one of the most pressing being cyber security, or the protection of information with the goal of preventing cyberattacks. This work provides a model that mixes fault tree analysis, decision theory, plus fuzzy theory helps to identify the current reasons of cyberattack prevention failures and (ii) assess the vulnerability of a cybersecurity system. The Fuzzy-based Modified MCDM-TOPSIS Model was used to analyse the cybersecurity risks associated with assaulting websites, e-commerce platforms, and enterprise resource planning (ERP), as well as the potential effects of such assaults. We evaluate these effects, which include data dissemination, data alteration, data loss or destruction, and service disruption, in terms of criteria linked to monetary losses and time for restoration. The model application's findings show how effective it is and how much more susceptible e-commerce is to cybersecurity threats than websites or ERP, in part because of frequent operator access, credit transactions, and user authentication issues that are exclusive to e-commerce.

In a cloud environment, ciphertext-policy attribute-based encryption (CP-ABE) plays an important role in attaining fine-grained data access control and confidentiality. In CP-ABE, since each attribute can be shared by a number of users and each user can maintain multiple attributes, the attribute will not be deleted for other users with the same attribute in practice, which may affect other users. Thus, how to revoke attributes is a significant and complex issue with CP-ABE schemes. To solve these issues, we present a novel CP-ABE with an efficient user or attribute revocation model. In this approach, the attribute revocation problem is effectively solved using the attribute group concept. The attribute controller (AC) in the proposed model updates the non-revoked user’s secret key if a user or attribute is revoked from the group. Besides, the proposed revocation model enhances security against cooperation between revoked and non-revoked users. Simulation results depict that the proposed revocation model attained better key update time, ciphertext update time, encryption time and decryption time.

Due to the mobility of users in an organization, inclusion of dynamic attributes such as time and location becomes the major challenge in Ciphertext-Policy Attribute-Based Encryption (CP-ABE). By considering this challenge; we focus to present dynamic time and location information in CP-ABE with multi-authorization. At first, along with the set of attributes of the users, their corresponding location is also embedded. Geohash is used to encode the latitude and longitude of the user’s position. Then, decrypt time period and access time period of users are defined using the new time tree (NTT) structure. The NTT sets the encrypted duration of the encrypted data and the valid access time of the private key on the data user’s private key. Besides, single authorization of attribute authority (AA) is extended as multi authorization for enhancing the effectiveness of key generation. Simulation results depict that the proposed CP-ABE achieves better encryption time, decryption time, security level and memory usage. Namely, encryption time and decryption time of the proposed CP-ABE are reduced to 19% and 16% than that of existing CP-ABE scheme.

The cloud allows clients to store and share data. Depending on the user's needs, it is imperative to design an effective access control plan to share the information only with approved users. The user loses control of their data when the data is outsourced to the cloud. Therefore, access control mechanisms will become a significant challenging problem. The Ciphertext-Policy Attribute- Based Encryption (CP-ABE) is an essential solution in which the user can control data access. CP-ABE encrypts the data under a limited access policy after the user sets some access policies. The user can decrypt the data if they satisfy the limited access policy. Although CP-ABE is an effective access control program, the privacy of the policy might be compromised by the attackers. Namely, the attackers can gather important information from plain text policy. To address this issue, the SHA-512 algorithm is presented to create a hash code for the user's attributes in this paper. Depending on the created hash codes, an access policy will be formed. It leads to protecting the access policy against attacks. The effectiveness of the proposed scheme is assessed based on decryption time, private key generation time, ciphertext generation time, and data verification time.

MANET (Mobile Ad hoc Network) is a collection of self-organizing mobile nodes that operate independently of centralized administration or existing infrastructure. MANETs are particularly vulnerable to a range of security risks as a result of this feature. Furthermore, most MANET routing methods are built on the assumption that the network contains no hostile nodes. As a result, various efforts and studies have gone into developing ad hoc networks, and a safe and reliable routing mechanism. Adaptive cuckoo search optimization and entropy-based signature authentication were proposed in this research for safe routing in MANETs. The network's nodes are first clustered using energy sigmoid-based fuzzy c-means clustering. The nodes in the cluster are then given an entropy-based signature. After that, the link lifetime and path distance are estimated to determine the node's future location. Adaptive cuckoo search optimization is then used to find further optimized routes. Finally, entropy-based signature verification is used to ensure secure routing. The experimental results show that the suggested secure routing technique surpasses existing techniques in terms of performance.

Ciphertext attribute-based encryption is a proven mechanism for providing the privacy and security for the shared resources in the cloud. However, the issues that are concerned with the sharing mechanisms such as master key and access policies were exploited by the malicious users. Moreover, the access control mechanisms are developed by using the large universe of attributes of the shared resource in the cloud. More number of attributes results into increase in computation time while computing the master and secret keys as well as for encryption and decryption processes. The observations over the participating attributes play vital role to prepare a machine learning model in terms of better accountability. In this paper we have proposed specific attribute-based encryption to provide the better security and better cloud access control mechanism. Inclusion of dynamic attributes while performing the encryption at data owner, cloud server would serve a better performance to avoid key exposure. This performance is elevated while generating the secret key at the proxy server. The performance has been found to be satisfactorily encouraging by reducing the computation time to almost half of the existing schemes and the observations are in accordance to the required accountability.

Flying Ad-hoc Network (FANET) is a type of Ad-hoc network on backbone of Unmanned Aerial Vehicle (UAV). These networks are used for providing communication services in case of natural disasters. Dynamic changes in link quality and mobility distort the Quality of Service (QoS) for routing in FANETs. This work proposed a Multi Criteria QoS Optimal Routing (MCQOR) guided by prediction of link quality and three-dimensional (3D) movement of FANET nodes. The network is clustered based on prediction of movement of nodes. Over the clustered topology, routing path is selected in reactive manner with joint optimization of packet delivery ratio, delay, and network overhead. In addition, cross layer feedback is used to reduce the packet generation rate and congestion in network. Through simulation analysis, the proposed routing protocol is found to have 3.8% higher packet delivery ratio, 26% lower delay and 14% lower network overhead compared to existing works.

Smartphone-based biometrics assumes a significant job in advanced mobile phones to protect the personal data, which are kept in the smart devices. The verification pattern such as pattern and password is broadly utilised in the mobile devices. But, these verification ways may not be more secured. Thus, the gait based pattern verification process is presented to confirm the genuine user. A novel kernel compactness African buffalo adaptive boosting (KCAB-AdaBoost) model is proposed to distinguish the authenticated user. To examine this current work model, the unauthenticated user's movement is also trained and tests simultaneously with the authenticated user's movement. Moreover, if the movement is coordinated, then the mobile device will be unlocked consequently or else it cannot be unlocked. Lastly, the adequacy of the proposed model is established by achieving better exactness and less error rate.

Most of the self-driving vehicles are suspect of the of the different types attacks due to its communication pattern and changing network topology characteristics, these types of vehicles are dependent on external communication sources of VANET, which is a vehicular network, It has attracted great interest of industry and academia, but it is having a number of issues like security, traffic congestion, road safety which are not addressed properly in recent years. To address these issues it’s required to build secure framework for the communication system in VANET and to detect different types of attack are the most important needs of the network security, which has been studied adequately by many researchers. However to improve the performance and to adapt the scenario of VANET, here in this paper we proposed a novel Hybrid KSVM scheme which is based on KNN and SVM algorithm to build a secure framework to detect Distributed Daniel of Service attack which is the part of Machine Learning approach. The experimental results shows that this approach gives the better results as compared to different Machine Learning based Algorithms to detect Distributed Daniel of Service attack.

Wireless sensor network with mobility is rapidly evolving and increasing in the recent decade. The cluster and hierarchical routing strategy demonstrates major changes in the lifespan of the network and the scalability. The latency, average energy consumption, packet distribution ratio is highly impacted due to a lack of coordination between cluster head and extreme mobile network nodes. Overall efficiency of highly mobile wireless sensor network is reduced by current techniques such as mobility-conscious media access control, sleep/wakeup scheduling and transmission of real-time services in wireless sensor network. This paper proposes a novel Priority-Mobility Aware Clustering Routing algorithm (p-MACRON) for high delivery of packets by assigning fair weightage to each and every packet of node. To automatically decide the scheduling policy, reinforcement learning approach is integrated. The mixed approach of priority and self-learning results into better utilization of energy. The experimental result shows comparisons of slotted sense multiple access protocol, AODV, MEMAC and P-MACRON, in which proposed algorithm delivered better results in terms of interval, packet size and simulation time.

Wireless sensor network is growing rapidly in recent era. The scalability and mobility impose remarkable challenges and degrade overall lifetime of network. The versatile topology with evolving parameters such as location and coverage needs to be modified for extensively dynamic network. The flat sensor network degrades the network’s total lifespan, because it absorbs a lot of resources. Clustering with one-hop distance in sensor network is the best way to elongate network lifespan. Clustering along with adaptive sleep scheduling using reinforcement algorithm produces better results by eliminating the issue of idle listening. The proposed mobility-aware clustering routing algorithm (MACRON) along with self-healing scheduling for extensively dynamic network to handle network communication with one-hop distance and probability distribution function will give better results as compared to RI-MAC, A-TDMA, AODV and MEMAC. The experimental analysis shows that MACRON gives better results in terms of throughput, delay, packet delivery, hop and mean deviation.

Fall off boundary problem (FOBP) arises in many steganography schemes that use the concept of differencing between two pixel values. This chapter presents a new steganography scheme using add-sub based quotient value differencing (ASQVD) and side match (SM) to address the FOBP. It performs two stages of embedding on 3×3 size disjoint pixel blocks. In stage 1, it performs ASQVD and remainder substitution on the central pixel and its left, right, lower, and upper neighbor pixels. Based on new values of these five pixels, in stage 2, it performs SM embedding approach on four corner neighbors. From experimental observations it has been derived that this scheme hides relatively larger amounts of data. The principles of differencing and substitution have been used in this scheme, so pixel difference histogram (PDH) and regular-singular (RS) tests have been utilized to verify the security of this new scheme. Fortunately, these two tests fail to detect this steganography technique. The average hiding capacity is 3.55 BPB. It is greater than in the existing techniques.

Authentication of appropriate users for accessing the liable gadgets exists as one among the prime theme in security models. Illegal access of gadgets such as smart phones, laptops comes with an uninvited consequences, such as data theft, privacy breakage and a lot more. Straight forward approaches like pattern based security, password and pin based security are quite expensive in terms of memory where the user has to keep remembering the passwords and in case of any security issue risen then the password has to be changed and once again keep remembering the recent one. To avoid these issues, in this paper an effective GAIT based model is proposed with the hybridization of Artificial Neural Network model namely Feedforward Neural Network Model with Swarm based algorithm namely Krill Herd optimization algorithm (KH). The task of KH is to optimize the weight factor of FNN which leads to the convergence of optimal solution at the end of the run. The proposed model is examined with 6 different performance measures and compared with four different existing classification model. The performance analysis shows the significance of proposed model when compared with the existing algorithms.

Along with number of problems associated with WSNs, one of the major issue we chose to study is their clustering topology and energy utilization techniques. Both these parameters are very much responsible in determining the life of nodes, quality of service, delay in data transmission, etc. So, it is very important to examine the cluster-based routing protocols and energy optimization protocols. The cluster routing is based on the selection of cluster head nodes for data transmission, and the parameters which are used for the making of an optimized network mainly depend on number of nodes, position of base station, and the network size. So, a well-settled cluster is tried to be designed with the study of various algorithms early proposed. And for energy optimization of network, we studied “sleep/wake-up” algorithm, which makes the nodes sleep during its ideal mode and wake it up when data transmission is to be done. With this sleep/wake-up algorithm important point to be kept an eye is the delay during this shifting between sleep and wake up or making sure that the selected path should not be engaged as well as it must be shortest path from base station. So, based on these two protocols, various papers are studied, and the comparative result of this protocol in various scenarios is carried out.

The genuine user of the smartphone is identified and information theft is prevented by continuous authentication, which is one of the most emerging features in biometrics application. A person is recognized by analysing the physiological or behavioural attributes is defined as biometrics. The physiological qualities include iris acknowledgment, impression of finger, palm and face geometry are used in the biometric validation frameworks. In the existing entry-point authentication techniques, a confidential information is lost because of internal attacks, while identifying the genuine user of the smartphone. Therefore, a biometric validation framework is designed in this research study to differentiate an authorized user by recognizing the gait. In order to identify the unauthorized smartphone access, a human gait recognition is carried out by implementing a Residual Convolutional Neural Network (RCNN) approach. A personal information of end user in smartphone is secured and presented a better solution from unauthorized access by proposed architecture. The performance of RCNN method is compared with the existing Deep Neural Network (DNN) in terms of classification accuracy. The simulation results showed that the RCNN method achieved 98.15% accuracy, where DNN achieved 95.67% accuracy on OU-ISIR dataset.

-The multiplier is one of the msost important key hardware blocks in most digital and high-performance systems, such as digital signal processors and microprocessors. Wallace Tree Multiplier provides a power-efficient approach for high-speed multiplication. Now, we using a novel (15,4) Binary counter using Symmetric Stacking for the reduces the Counter based Wallace Tree (CBT) Multiplier can be improve the multiplier speed. A novel 15:4 binary counter is proposed by using (7,3) counter and proposed Full Adder based circuit.

There are persistent cyber security attacks which leads unauthorized access to internal corporate networks and other critical confidential information. It is essential to build security solutions by adopting a Security Framework for any organization to find solutions for majority of vulnerabilities and flaws. The proposed work provides a platform to study methodical, controlled and repeatable approach to assess an organization’s cyber security posture especially for asset management. The study helps organization's owners to assess their operational and information system’s cybersecurity practices by querying a set of comprehensive questions about cyber security assets like Authentication, Authorization, Access controls, Database, Email security, Removable media, Backup &, Firewalls, Incident management etc. The proposed model improves the cyber security posture of the organization and escalate the chances of mitigating cyber security risks.

There are persistent cyber security attacks which leads unauthorized access to internal corporate networks and other critical confidential information. It is essential to build security solutions by adopting a Security Framework for any organization to find solutions for majority of vulnerabilities and flaws. The proposed work provides a platform to study methodical, controlled and repeatable approach to assess an organization’s cyber security posture especially for asset management. The study helps organization's owners to assess their operational and information system’s cybersecurity practices by querying a set of comprehensive questions about cyber security assets like Authentication, Authorization, Access controls, Database, Email security, Removable media, Backup &, Firewalls, Incident management etc. The proposed model improves the cyber security posture of the organization and escalate the chances of mitigating cyber security risks.

As VANET is one of the subset of MANET, it has been emerging since the inception of AI based Self Driving cars and have been increasing till date. The main objective of Vanet can be referred as safety concerns and internet driven Applications. On board units(OBU) and street side gadgets(RSU)are the fundamental aspect of vanet, it speak over open wi-fi network therefore making system at risk of attacks and which can also cause privatenesscompromisation, tracking and so on. in phrases of routing in VANET’s conventional routing can face a few critical trouble as in community. In conversation while the vacation spot node is unknown it is able to causes the packet loss it can cause degradation of QoS and developing in energy intake. As immoderate mobility is one of the critical part of VANET. VANET can be seen as an instance of hybrid developing networks. right here in this paper we are that specialize in essential troubles and routing techniques in Vanet.

In wireless sensor network energy consumption is the recent research trend. Sleep scheduling and clustering of nodes in mobile environment are two different approaches adopted to elongate the life of network. In this paper Mobility Aware Clustering routing algorithm (MACRON) is proposed by integrating two challenging approaches. In the sleep scheduling approach, the node takes the decision for their states independently in decentralized manner. Using this reward based approach; the node decides its own current state (sleep, wake, idle) and it also predict the state of neighbors without communicating with neighbors. The performance improvement of sleep scheduling algorithm is significant but, to enhance performance it should be integrated with clustering approaches. To support the mobility in wireless sensor network various MAC protocol has been proposed, but they consume huge energy for data transmission. The proposed MACRON algorithm works efficiently in both mobile and stationary network. The performance of proposed algorithm gives decent outcome in varying size of nodes ranging from 10 to 40 in ns-2.

Micro Electromechanical System also popularly known as MEMS is a technique of combining both mechanical and electrical components to produce a miniature device. The functionality of MEMS devices are mechanical and electrical functions. MEMS has number of micro components integrated on one single chip it is done in such a way to sense and control the environment at the same time. The integration of these chips is done by using micro fabrication technologies. There are few parameters Low Actuation is achieved by using electrostatic mechanism. The proposed RF MEMS switch works at a low pull in voltage at 17V is achieved by electromechanical analysis. The Proposed switch has a capacitance ratio of 159. Electromagnetic analysis is analyzed, and RF performance of the switch is discussed.

Block chain is a trust which can be best understood by the state machine replication, It is decentralized distributed ledger which is along all peers in the network connected through nodes over Internet. Every Node in the chain have equal stake and also the main factor is every node which have greater CPU cycles has a chance to operate node by spending those CPU cycles and also show Proof Of Work. Hence when the block chain is used in Business Models it loses its Private transactions and Confidential Contracts.

To protect from pixel difference histogram (PDH) analysis and RS analysis, two hybrid image steganography techniques by appropriate combination of LSB substitution, pixel value differencing (PVD), and exploiting modification directions (EMD) have been proposed in this paper. The cover image is traversed in raster scan order and partitioned into blocks. The first technique operates on 2 × 2 pixel blocks and the second technique operates on 3 × 3 pixel blocks. For each block, the average pixel value difference, d, is calculated. If d value is greater than 15, the block is in an edge area, so a combination of LSB substitution and PVD is applied. If d value is less than or equal to 15, the block is in a smooth area, so a combination of LSB substitution and EMD is applied. Each of these two techniques exists in two variants (Type 1 and Type 2) with respect to two different range tables. The hiding capacities and PSNR of both the techniques are found to be improved. The results from experiments prove that PDH analysis and RS analysis cannot detect these proposed techniques.

Blockchain Technology is helping to build robust applications in all sectors. Blockchain is trending, advancing and adopted depending on the requirement because of data integrity, privacy and encryption. The appearance of suspicious logs are visible and noticeable by malicious activity through either malware or an intrusion in the network as identified by IDS or any other preventive systems. The generation of false alarms is the output of any IDS, Firewall and other similar secure preventive systems in the organization. Blockchain technology with its decentralized behaviour can be visualized through an application for monitoring and controlling the logs which can be similar to IDS and other similar systems. In this work we propose a framework to confirm the visualization of Blockchain application to monitor and control the logs in huge number that spread across the organization's network. The framework is well supported by the description of each and every component of Blockchain application and its environment.

Current digitized world has surpassed the days of mere existence of internet. Furnishing the services through web has become the most often element to be implemented by almost every sector. These ever-changing technologies has also brought about, devastating evading techniques compromising the fragility of the web application. Assessing the existing vulnerabilities of a web application and testing all possible penetrations would be tedious if the tools used are bearing a cost factor. This paper suggests an integrated approach of assessing the vulnerabilities in any web application using free and open source tools where the reports are generated with respect to vulnerabilities and their categories and level of severity. The tools are integrated and correlated for producing the accurate results in better manner similar to the results produced by the commercial ones. The analysis has been done by considering the reports released by OWASP, OSSTMM, ISSAF, CVE, Exploit Database and Microsoft Vulnerability Research. The report produced after vulnerability assessment has been taken for testing different penetrations for a single application. The identified vulnerabilities are therefore exploited for testing the penetrations of a web application. The report will be generated finally stating all possible exploitable vulnerabilities that are encountered in a web application. The final report generated would help the developers to fix the vulnerable issues.

For the most part there are unbounded quantities of routes in number framework. In any case, machines include them two's though humans include them tens. It is as of now demonstrated that for the base number of calculations to be accessible for a number, a base-e number framework is picked. As the whole number estimation of e is nearest to 3, we take a shot at the number system with base 3. As a rule there exists a framework which can change over a ternary number into parallel and afterward double to polynomial shape and after that send the scrambled information to the authority of information. In this paper, we examine an approach which can change over a ternary number specifically into polynomial shape, skirting the progression of transformation to transitional parallel frame. We actualize AES calculation utilizing the proposed ternary framework as a swap for GF(2n).

The traditional pixel value differencing (PVD) steganographical schemes are easily detected by pixel difference histogram (PDH) analysis. This problem could be addressed by adding two tricks: (i) utilizing horizontal, vertical, and diagonal edges and (ii) using adaptive quantization ranges. This paper presents an adaptive PVD technique using 6-pixel blocks. There are two variants. The proposed adaptive PVD for 2×3-pixel blocks is known as variant 1, and the proposed adaptive PVD for 3×2-pixel blocks is known as variant 2. For every block in variant 1, the four corner pixels are used to hide data bits using the middle column pixels for detecting the horizontal and diagonal edges. Similarly, for every block in variant 2, the four corner pixels are used to hide data bits using the middle row pixels for detecting the vertical and diagonal edges.The quantization ranges are adaptive and are calculated using the correlation of the two middle column/row pixels with the four corner pixels. The technique performs better as compared to the existing adaptive PVD techniques by possessing higher hiding capacity and lesser distortion. Furthermore, it has been proven that the PDH steganalysis and RS steganalysis cannot detect this proposed technique.

Mobile ad-hoc network is an infrastructure-less and self-organizing network, where nodes communicate through wireless links. Because of its dynamic topology, security becomes a vital issue compared to infrastructure networks. MANETs are more vulnerable to various types of security attacks due to the absence of trusted centralized authority. Several routing protocols have been proposed for these networks to establish an end to end link for communication between the nodes. These protocols are prone to attacks by the malicious nodes and there is always a need to detect and prevent the attacks timely before the collapse of network. In this paper the focus lies on current routing attacks, security issues of ad-hoc networks and solutions to mitigate attacks against the routing protocols based on cooperation between nodes in network.

In all industries in trade in these days, desktops and IT sectors are a giant and indulging infrastructure. Employees in all divisions from HR to program progress expect a computing device and/or network connector as a way to do their jobs effortlessly. Still people in the field are needed to hold a desktop or several form of the hand held the device to broadcast information. This approach to the arena has introduced a quantity of recent protection associated subject to the work drive. One of the crucial matter includes the manufacturer's proper to keep manage over InfoTech and educational institutes belongings which furnish staff with an opportunity to silently execute private events. There are over hundred's entirely unexpected stock realistic now a days that might let organizations notice what their clients act at job on their desktops, of their e-mail and on cyberspace. However what do such statistics fairly represent? What do organization keep an eye on of user/employee electronic message, web and PC utilization truly look like? In this study, we provide a survey results conducted on both students and staff in our college and explanation of why you need to monitor your employees, concept of key loggers and the client server based interception of keyloggers. The key logging project captures all strokes of keys along with the title of the appliance where in the keystrokes had been pressed. Using this, we seizing all knowledge in textual content and photo type.

Background/Objectives: This paper presents a method by calculating the pixel value differences along seven directions using nine-pixel blocks. Methods/Statistical Analysis: The centrally located pixel in nine-pixel block is used to form seven pairs with its seven neighboring pixels. The eighth neighbor pixel is used as the indicator to identify whether a block suffers with Fall Off Boundary Problem (FOBP) or not. Findings: Seven pixel value differences are calculated and based on these differences embedding is done. After embedding, the central pixel value is normalized to have a single value for all the seven pairs by suitable adjustments. After adjustments if any pixel value in the block falls off boundary, then the entire block is exempted from embedding. This is noted at the eighth neighbor pixel, so that it can also be exempted during extraction. Furthermore, to increase the capacity and peak signal-to-noise ratio, the nine-pixel blocks which suffer with FOBP are embedded using Wu and Tsai's PVD method. The extraction process is very simple and the secret message can be extracted from the stego-image without using the original cover image. Application/ Improvements: Without compromising the security and imperceptibility the hiding capacity is almost 50% increased as compared to Wu and Tsai's Pixel Value Differencing (PVD) method.

This paper illustrates the various performance evaluation parameters of image steganography techniques. The performance of a steganographic technique can be rated by three parameters; (i) hiding capacity, (ii) distortion measure and (iii) security. The hiding capacity means the maximum amount of information that can be hidden in an image. It can also be represented as the number of bits per pixel. The distortion is measured by using various metrics like mean square error, root mean square error, PSNR, quality index, correlation, structural similarity index etc. Each of these metrics can be represented mathematically. The security can be evaluated by testing the steganography technique with the steganalysis schemes like pixel difference histogram analysis, RS analysis etc. All these metrics are illustrated with mathematical equations. Finally, some future directions are also highlighted at the end of the paper.

This article proposes a hybrid steganographic approach using LSB replacement and PVD. The main goal is to increase capacity of data hiding and decrease the distortion. The input image is fragmented into blocks. Every block is comprised of of six pixels drawn from two consecutive rows and three consecutive columns without any overlapping. In the uppermiddle pixel of a block k data bits are hidden using LSB replacement. Using the modified value of it, five difference values are calculated with regard to its five neighbors in the block. These differences are used to hide secret data bits. The vertical. diagonal and horizontal edges are exploited for data hiding. Two variants of this approach are proposed. The first one, Type1, possesses higher PSNR i.e. lower distortion. The second one, Type2 possesses higher hiding capacity.

In recent the espousal of Wireless Sensor Networks has been broadly augmented in numerous divisions. Battery operated Sensor nodes in the wireless network accomplish main task of capturing and responding to the surroundings. The lifetime of the network depends on the energy consumption of the sensor nodes. This paper contributes the survey on how the energy consumption should be managed for maximizing the life time of network and how to improve the efficiency of Network by using Cross layer architecture. The traditional MAC Layer, Network Layer & Transport for WLAN having their own downsides just by modifying those we can achieve the network life time maximization goal. This paper represents analytical study for Energy efficiency by modifying Scheduling algorithm, by modifying traditional AODV routing algorithm for efficient packet transmission and by effectively using TCP for End to End Delivery of Data.

The Computational Performance of implementing cryptographic block ciphers can be improved by exploiting parallel execution in Lab View (Laboratory Virtual Instrument Engineering Workbench). In this paper, we present a parallel processing method for block cipher algorithm: Data Encryption Standard (DES) based on software implementation in lab view. Test of common Lab view Program show on average, a 20 to 35 percent improvement in execution time in most Lab view code. Optimizing a Lab view program for a multicore computing is the best way to ensure the maximum speed up when running code on the multicore computing systems. The proposed approach can be implemented by using String To Byte Array Function, U8 To TF Array, Split 1D Array Function, Index Array Function, Array Subset Function, Build Array Function. In this we will give a file input which contains large amount of plane text which is divided each 8byte in table like manner with same key, when this file is given as input several 8byte of plaintext will be executed parallel.

Data Encryption Standard (DES) is an encryption algorithm which is primarily used in applications where block cipher mode of operation is required. It is further modified as Double DES (2DES), Triple DES (3DES) in order to provide added security due to extra key length. DES is susceptible to brute force attack and 2DES for meet in middle attack. In this paper we implement a modified DES algorithm in Cipher Block Chaining mode of operation in which key generation procedure differs by using a 112 bit key and the plain text is encoded using a modified playfair technique as input to DES encryption function. Variations in the avalanche affect are observed in the results. Experimental results exhibit a higher avalanche effect in 60% of the cases using the modified DES algorithm.

Attack pattern system exhibits a unique property of pattern sequential cascading nature applied during the design phase of an application system. In this paper a mathematical framework based on predicate and propositional logic is applied to verify and check the mentioned property with the help of design specification. The framework also defines few predicate operators to construct the results in terms of propositions that each pattern displays during the design in the context of security scenario. Finally the results are presented against number of patterns along with number of propositions, operators, other resources where pattern consumes during the implementation scenario. Templates are proposed to present the pattern data to derive the desired security metric. © 2012 IEEE.