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Sarathy, N., Alsawwaf, M., Chaczko, Z..  2020.  Investigation of an Innovative Approach for Identifying Human Face-Profile Using Explainable Artificial Intelligence. 2020 IEEE 18th International Symposium on Intelligent Systems and Informatics (SISY). :155–160.
Human identification is a well-researched topic that keeps evolving. Advancement in technology has made it easy to train models or use ones that have been already created to detect several features of the human face. When it comes to identifying a human face from the side, there are many opportunities to advance the biometric identification research further. This paper investigates the human face identification based on their side profile by extracting the facial features and diagnosing the feature sets with geometric ratio expressions. These geometric ratio expressions are computed into feature vectors. The last stage involves the use of weighted means to measure similarity. This research addresses the problem of using an eXplainable Artificial Intelligence (XAI) approach. Findings from this research, based on a small data-set, conclude that the used approach offers encouraging results. Further investigation could have a significant impact on how face profiles can be identified. Performance of the proposed system is validated using metrics such as Precision, False Acceptance Rate, False Rejection Rate and True Positive Rate. Multiple simulations indicate an Equal Error Rate of 0.89.
Saravanan, S., Sabari, A., Geetha, M., priyanka, Q..  2015.  Code based community network for identifying low risk community. 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO). :1–6.

The modern day approach in boulevard network centers on efficient factor in safe routing. The safe routing must follow up the low risk cities. The troubles in routing are a perennial one confronting people day in and day out. The common goal of everyone using a boulevard seems to be reaching the desired point through the fastest manner which involves the balancing conundrum of multiple expected and unexpected influencing factors such as time, distance, security and cost. It is universal knowledge that travelling is an almost inherent aspect in everyone's daily routine. With the gigantic and complex road network of a modern city or country, finding a low risk community for traversing the distance is not easy to achieve. This paper follows the code based community for detecting the boulevard network and fuzzy technique for identifying low risk community.

Sardana, Noel, Cohen, Robin.  2014.  Modeling Agent Trustworthiness with Credibility for Message Recommendation in Social Networks. Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems. :1423–1424.

This paper presents a framework for multiagent systems trust modeling that reasons about both user credibility and user similarity. Through simulation, we are able to show that our approach works well in social networking environments by presenting messages to users with high predicted benefit.

Sardar, Muhammad Usama, Quoc, Do Le, Fetzer, Christof.  2020.  Towards Formalization of Enhanced Privacy ID (EPID)-based Remote Attestation in Intel SGX. 2020 23rd Euromicro Conference on Digital System Design (DSD). :604—607.

Vulnerabilities in privileged software layers have been exploited with severe consequences. Recently, Trusted Execution Environments (TEEs) based technologies have emerged as a promising approach since they claim strong confidentiality and integrity guarantees regardless of the trustworthiness of the underlying system software. In this paper, we consider one of the most prominent TEE technologies, referred to as Intel Software Guard Extensions (SGX). Despite many formal approaches, there is still a lack of formal proof of some critical processes of Intel SGX, such as remote attestation. To fill this gap, we propose a fully automated, rigorous, and sound formal approach to specify and verify the Enhanced Privacy ID (EPID)-based remote attestation in Intel SGX under the assumption that there are no side-channel attacks and no vulnerabilities inside the enclave. The evaluation indicates that the confidentiality of attestation keys is preserved against a Dolev-Yao adversary in this technology. We also present a few of the many inconsistencies found in the existing literature on Intel SGX attestation during formal specification.

Saridou, Betty, Shiaeles, Stavros, Papadopoulos, Basil.  2019.  DDoS Attack Mitigation through Root-DNS Server: A Case Study. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:60—65.

Load balancing and IP anycast are traffic routing algorithms used to speed up delivery of the Domain Name System. In case of a DDoS attack or an overload condition, the value of these protocols is critical, as they can provide intrinsic DDoS mitigation with the failover alternatives. In this paper, we present a methodology for predicting the next DNS response in the light of a potential redirection to less busy servers, in order to mitigate the size of the attack. Our experiments were conducted using data from the Nov. 2015 attack of the Root DNS servers and Logistic Regression, k-Nearest Neighbors, Support Vector Machines and Random Forest as our primary classifiers. The models were able to successfully predict up to 83% of responses for Root Letters that operated on a small number of sites and consequently suffered the most during the attacks. On the other hand, regarding DNS requests coming from more distributed Root servers, the models demonstrated lower accuracy. Our analysis showed a correlation between the True Positive Rate metric and the number of sites, as well as a clear need for intelligent management of traffic in load balancing practices.

Sarikaya, Y., Ercetin, O., Koksal, C.E..  2014.  Confidentiality-Preserving Control of Uplink Cellular Wireless Networks Using Hybrid ARQ. Networking, IEEE/ACM Transactions on. PP:1-1.

We consider the problem of cross-layer resource allocation with information-theoretic secrecy for uplink transmissions in time-varying cellular wireless networks. Particularly, each node in an uplink cellular network injects two types of traffic, confidential and open at rates chosen in order to maximize a global utility function while keeping the data queues stable and meeting a constraint on the secrecy outage probability. The transmitting node only knows the distribution of channel gains. Our scheme is based on Hybrid Automatic Repeat Request (HARQ) transmission with incremental redundancy. We prove that our scheme achieves a utility, arbitrarily close to the maximum achievable. Numerical experiments are performed to verify the analytical results and to show the efficacy of the dynamic control algorithm.
 

Sarkar, M. Z. I., Ratnarajah, T..  2010.  Information-theoretic security in wireless multicasting. International Conference on Electrical Computer Engineering (ICECE 2010). :53–56.
In this paper, a wireless multicast scenario is considered in which the transmitter sends a common message to a group of client receivers through quasi-static Rayleigh fading channel in the presence of an eavesdropper. The communication between transmitter and each client receiver is said to be secured if the eavesdropper is unable to decode any information. On the basis of an information-theoretic formulation of the confidential communications between transmitter and a group of client receivers, we define the expected secrecy sum-mutual information in terms of secure outage probability and provide a complete characterization of maximum transmission rate at which the eavesdropper is unable to decode any information. Moreover, we find the probability of non-zero secrecy mutual information and present an analytical expression for ergodic secrecy multicast mutual information of the proposed model.
Sarkisyan, A., Debbiny, R., Nahapetian, A..  2015.  WristSnoop: Smartphone PINs prediction using smartwatch motion sensors. 2015 IEEE International Workshop on Information Forensics and Security (WIFS). :1–6.

Smartwatches, with motion sensors, are becoming a common utility for users. With the increasing popularity of practical wearable computers, and in particular smartwatches, the security risks linked with sensors on board these devices have yet to be fully explored. Recent research literature has demonstrated the capability of using a smartphone's own accelerometer and gyroscope to infer tap locations; this paper expands on this work to demonstrate a method for inferring smartphone PINs through the analysis of smartwatch motion sensors. This study determines the feasibility and accuracy of inferring user keystrokes on a smartphone through a smartwatch worn by the user. Specifically, we show that with malware accessing only the smartwatch's motion sensors, it is possible to recognize user activity and specific numeric keypad entries. In a controlled scenario, we achieve results no less than 41% and up to 92% accurate for PIN prediction within 5 guesses.

Sarma, K.J., Sharma, R., Das, R..  2014.  A survey of Black hole attack detection in Manet. Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on. :202-205.

MANET is an infrastructure less, dynamic, decentralised network. Any node can join the network and leave the network at any point of time. Due to its simplicity and flexibility, it is widely used in military communication, emergency communication, academic purpose and mobile conferencing. In MANET there no infrastructure hence each node acts as a host and router. They are connected to each other by Peer-to-peer network. Decentralised means there is nothing like client and server. Each and every node is acted like a client and a server. Due to the dynamic nature of mobile Ad-HOC network it is more vulnerable to attack. Since any node can join or leave the network without any permission the security issues are more challenging than other type of network. One of the major security problems in ad hoc networks called the black hole problem. It occurs when a malicious node referred as black hole joins the network. The black hole conducts its malicious behavior during the process of route discovery. For any received RREQ, the black hole claims having route and propagates a faked RREP. The source node responds to these faked RREPs and sends its data through the received routes once the data is received by the black hole; it is dropped instead of being sent to the desired destination. This paper discusses some of the techniques put forwarded by researchers to detect and prevent Black hole attack in MANET using AODV protocol and based on their flaws a new methodology also have been proposed.

Sarma, M. S., Srinivas, Y., Abhiram, M., Ullala, L., Prasanthi, M. S., Rao, J. R..  2017.  Insider Threat Detection with Face Recognition and KNN User Classification. 2017 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM). :39—44.
Information Security in cloud storage is a key trepidation with regards to Degree of Trust and Cloud Penetration. Cloud user community needs to ascertain performance and security via QoS. Numerous models have been proposed [2] [3] [6][7] to deal with security concerns. Detection and prevention of insider threats are concerns that also need to be tackled. Since the attacker is aware of sensitive information, threats due to cloud insider is a grave concern. In this paper, we have proposed an authentication mechanism, which performs authentication based on verifying facial features of the cloud user, in addition to username and password, thereby acting as two factor authentication. New QoS has been proposed which is capable of monitoring and detection of insider threats using Machine Learning Techniques. KNN Classification Algorithm has been used to classify users into legitimate, possibly legitimate, possibly not legitimate and not legitimate groups to verify image authenticity to conclude, whether there is any possible insider threat. A threat detection model has also been proposed for insider threats, which utilizes Facial recognition and Monitoring models. Security Method put forth in [6] [7] is honed to include threat detection QoS to earn higher degree of trust from cloud user community. As a recommendation, Threat detection module should be harnessed in private cloud deployments like Defense and Pharma applications. Experimentation has been conducted using open source Machine Learning libraries and results have been attached in this paper.
Sarma, Subramonian Krishna.  2019.  Optimized Activation Function on Deep Belief Network for Attack Detection in IoT. 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :702–708.
This paper mainly focuses on presenting a novel attack detection system to thread out the risk issues in IoT. The presented attack detection system links the interconnection of DevOps as it creates the correlation between development and IT operations. Further, the presented attack detection model ensures the operational security of different applications. In view of this, the implemented system incorporates two main stages named Proposed Feature Extraction process and Classification. The data from every application is processed with the initial stage of feature extraction, which concatenates the statistical and higher-order statistical features. After that, these extracted features are supplied to classification process, where determines the presence of attacks. For this classification purpose, this paper aims to deploy the optimized Deep Belief Network (DBN), where the activation function is tuned optimally. Furthermore, the optimal tuning is done by a renowned meta-heuristic algorithm called Lion Algorithm (LA). Finally, the performance of proposed work is compared and proved over other conventional methods.
Sarochar, J., Acharya, I., Riggs, H., Sundararajan, A., Wei, L., Olowu, T., Sarwat, A. I..  2019.  Synthesizing Energy Consumption Data Using a Mixture Density Network Integrated with Long Short Term Memory. 2019 IEEE Green Technologies Conference(GreenTech). :1—4.
Smart cities comprise multiple critical infrastructures, two of which are the power grid and communication networks, backed by centralized data analytics and storage. To effectively model the interdependencies between these infrastructures and enable a greater understanding of how communities respond to and impact them, large amounts of varied, real-world data on residential and commercial consumer energy consumption, load patterns, and associated human behavioral impacts are required. The dissemination of such data to the research communities is, however, largely restricted because of security and privacy concerns. This paper creates an opportunity for the development and dissemination of synthetic energy consumption data which is inherently anonymous but holds similarities to the properties of real data. This paper explores a framework using mixture density network (MDN) model integrated with a multi-layered Long Short-Term Memory (LSTM) network which shows promise in this area of research. The model is trained using an initial sample recorded from residential smart meters in the state of Florida, and is used to generate fully synthetic energy consumption data. The synthesized data will be made publicly available for interested users.
Saroliya, A., Mondal, J., Agrawal, M..  2020.  A Solution for Secured Content Transferring in between Multiple Hosts within P2P Enabled Intranet. 2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3). :1—3.
Peer to peer file transferring is always a better approach for sharing the contents among multiple nodes when they are in same logical network. Sometimes when a peer leaves the network and its resources key is handed-over to other neighbors (may be adjacent peer) there is always high risk for transferring of related content. In this paper a solution has been implemented through which peers can share files with another peer in a secure manner over P2P enabled intra-network. The data of Peers are located in two different folders namely- PUBLIC and PRIVATE. For a PRIVATE file, the permission from the owner will be desired to retrieve the file at the receiving-end peer. This enables users to restrict the outflow of files. The main advantage of this application is that there is no need of global network (internetwork) and a centralized server.
Sarrab, Mohamed, Alnaeli, Saleh M..  2018.  Critical Aspects Pertaining Security of IoT Application Level Software Systems. 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). :960–964.
With the prevalence of Internet of Things (IoT) devices and systems, touching almost every single aspect of our modern life, one core factor that will determine whether this technology will succeed, and gain people trust, or fail is security. This technology aimed to facilitate and improve the quality of our life; however, it is hysterical and fast growth makes it an attractive and prime target for a whole variety of hackers posing a significant risk to our technology and IT infrastructures at both enterprise and individual levels. This paper discusses and identifies some critical aspects from software security perspective that need to be addressed and considered when designing IoT applications. This paper mainly concerned with potential security issues of the applications running on IoT devices including insecure interfaces, insecure software, constrained application protocol and middleware security. This effort is part of a funded research project that investigates internet of things (IoT) security and privacy issues related to architecture, connectivity and data collection.
Sasa, K., Kikuchi, H..  2018.  Impact Assessment of Password Reset PRMitM Attack with Two-Factor Authentication. 2018 IEEE Conference on Dependable and Secure Computing (DSC). :1-8.

In 2017, Gelernter et al. identified the ``password-reset man-in-the-middle'' attack, which can take over a user's account during two-factor authentication. In this attack, a password reset request is sent via an SMS message instead of an expected authentication request, and the user enters a reset code at the malicious man-in-the-middle website without recognizing that the code resets the password. Following this publication, most vulnerable websites attempted to remove the vulnerability. However, it is still not clear whether these attempts were sufficient to prevent careless users from being attacked. In this paper, we describe the results of an investigation involving domestic major websites that were vulnerable to this type of attack. To clarify the causes of vulnerability, we conducted experiments with 180 subjects. The SMS-message parameters were ``with/without warning'', ``numeric/alphanumeric code'', and ``one/two messages'', and subjects were tested to see if they input the reset code into the fake website. According to the result of the experiment, we found that the PRMitM risk odds were increased 4.6, 1.86, and 11.59 times higher in a no-warning case, a numeric-only reset code, and a behavior that change passwords very frequently, respectively.

Sasan, Avesta, Zu, Qi, Wamg, Yanzhi, Seo, Jae-sun, Mohsenin, Tinoosh.  2018.  Low Power and Trusted Machine Learning. Proceedings of the 2018 on Great Lakes Symposium on VLSI. :515–515.

In this special discussion session on machine learning, the panel members discuss various issues related to building secure and low power neuromorphic systems. The security of neuromorphic systems may be discussed in term of the reliability of the model, trust in the model, and security of the underlying hardware. The low power aspect of neuromorphic computing systems may be discussed in terms of adaptation of new devices and technologies, the adaptation of new computational models, development of heterogeneous computing frameworks, or dedicated engines for processing neuromorphic models. This session may include discussion on the design space of such supporting hardware, exploring tradeoffs between power/energy, security, scalability, hardware area, performance, and accuracy.

Sasidharan, B., Kumar, P.V., Shah, N.B., Rashmi, K.V., Ramachandran, K..  2014.  Optimality of the product-matrix construction for secure MSR regenerating codes. Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on. :10-14.

In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of ℓ1 nodes as well as all the repair traffic entering a second disjoint set of ℓ2 nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever ℓ2 ≤ d - k + 1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al.

Sasidharan, B., Kumar, P.V., Shah, N.B., Rashmi, K.V., Ramachandran, K..  2014.  Optimality of the product-matrix construction for secure MSR regenerating codes. Communications, Control and Signal Processing (ISCCSP), 2014 6th International Symposium on. :10-14.

In this paper, we consider the security of exact-repair regenerating codes operating at the minimum-storage-regenerating (MSR) point. The security requirement (introduced in Shah et. al.) is that no information about the stored data file must be leaked in the presence of an eavesdropper who has access to the contents of ℓ1 nodes as well as all the repair traffic entering a second disjoint set of ℓ2 nodes. We derive an upper bound on the size of a data file that can be securely stored that holds whenever ℓ2 ≤ d - k + 1. This upper bound proves the optimality of the product-matrix-based construction of secure MSR regenerating codes by Shah et. al.

Sasirekha, D., Radha, N..  2017.  Secure and attack aware routing in mobile ad hoc networks against wormhole and sinkhole attacks. 2017 2nd International Conference on Communication and Electronics Systems (ICCES). :505–510.

The inherent characteristics of Mobile Ad hoc network (MANET) such as dynamic topology, limited bandwidth, limited power supply, infrastructure less network make themselves attractive for a wide spectrum of applications and vulnerable to security attacks. Sinkhole attack is the most disruptive routing layer attack. Sinkhole nodes attract all the traffic towards them to setup further active attacks such as Black hole, Gray hole and wormhole attacks. Sinkhole nodes need to be isolated from the MANET as early as possible. In this paper, an effective mechanism is proposed to prevent and detect sinkhole and wormhole attacks in MANET. The proposed work detects and punishes the attacker nodes using different techniques such as node collusion technique, which classifies a node as an attacker node only with the agreement with the neighboring nodes. When the node suspects the existence of attacker or sinkhole node in the path, it joins together with neighboring nodes to determine the sinkhole node. In the prevention of routing attacks, the proposed system introduces a route reserve method; new routes learnt are updated in the routing table of the node only after ensuring that the route does not contain the attacker nodes. The proposed system effectively modifies Ad hoc on demand Distance Vector (AODV) with the ability to detect and prevent the sinkhole and wormhole attack, so the modified protocol is named as Attack Aware Alert (A3AODV). The experiments are carried out in NS2 simulator, and the result shows the efficiency in terms of packet delivery ratio and routing overhead.

Sassani Sarrafpour, Bahman A., Del Pilar Soria Choque, Rosario, Mitchell Paul, Blake, Mehdipour, Farhad.  2019.  Commercial Security Scanning: Point-on-Sale (POS) Vulnerability and Mitigation Techniques. 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :493–498.
Point of Sale (POS) systems has become the technology of choice for most businesses and offering number of advantages over traditional cash registers. They manage staffs, customers, transaction, inventory, sale and labor reporting, price adjustment, as well as keeping track of cash flow, expense management, reducing human errors and more. Whether traditional on-premise POS, or Cloud-Bases POS, they help businesses to run more efficiently. However, despite all these advantages, POS systems are becoming targets of a number of cyber-attacks. Security of a POS system is a key requirement of the Payment Card Industry Data Security Standard (PCI DSS). This paper undertakes research into the PCI DSS and its accompanying standards, in an attempt to break or bypass security measures using varying degrees of vulnerability and penetration attacks in a methodological format. The resounding goal of this experimentation is to achieve a basis from which attacks can be made against a realistic networking environment from whence an intruder can bypass security measures thus exposing a vulnerability in the PCI DSS and potentially exposing confidential customer payment information.
Sassatelli, Lucile, Médard, Muriel.  2017.  Thwarting Pollution Attacks in Network Coding for Delay Tolerant Mobile Social Networks. Proceedings of the Second International Conference on Internet of Things, Data and Cloud Computing. :63:1–63:7.

We consider Delay Tolerant Mobile Social Networks (DTMSNs), made of wireless nodes with intermittent connections and clustered into social communities. The lack of infrastructure and its reliance on nodes' mobility make routing a challenge. Network Coding (NC) is a generalization of routing and has been shown to bring a number of advantages over routing. We consider the problem of pollution attacks in these networks, that are a very important issue both for NC and for DTMSNs. Our first contribution is to propose a protocol which allows controlling adversary's capacity by combining cryptographic hash dissemination and error-correction to ensure message recovery at the receiver. Our second contribution is the modeling of the performance of such a protection scheme. To do so, we adapt an inter-session NC model based on a fluid approximation of the dissemination process. We provide a numerical validation of the model. We are eventually able to provide a workflow to set the correct parameters and counteract the attacks. We conclude by highlighting how these contributions can help secure a real-world DTMSN application (e.g., a smart-phone app.).

Sasubilli, S. M., Dubey, A. K., Kumar, A..  2020.  Hybrid security analysis based on intelligent adaptive learning in Big Data. 2020 International Conference on Advances in Computing and Communication Engineering (ICACCE). :1—5.

Big data provides a way to handle and analyze large amount of data or complex set. It provides a systematic extraction also. In this paper a hybrid security analysis based on intelligent adaptive learning in big data has been discussed with the current trends. This paper also explores the possibility of cloud computing collaboration with big data. The advantages along with the impact for the overall platform evaluation has been discussed with the traditional trends. It has been useful in the analysis and the exploration of future research. This discussion also covers the computational variability and the connotation in terms of data reliability, availability and management in big data with data security aspects.

Satav, Pravin R, Jawandhiya, Pradeep M., Thakare, Vilas M..  2018.  Secure Route Selection Mechanism in the Presence of Black Hole Attack with AOMDV Routing Algorithm. 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). :1–6.
The research in MANET has been carried out for the development of various techniques which will increase the competency of the network only. A plenty number of proposed routing protocols are magnificent in terms of efficiency. However, proposed protocols were generally fulfilling the set of trusted network and not considered for adversarial network setting, hence there is no security mechanism has been considered. MANET is widely used in sensitive fields like battlefield, police rescue operation and many more in such type of sensitive field an attacker may try to gather information about the conversation starting from the origin node to the terminal node. Secure route selection approach for route selection in adverse environment is discussed in this article. The results shows that proposed algorithm, will resolve the single & collaborative attack by increasing the computational & storage overhead and by improving the significant PDR, achieves a noticeable enhancement in the end to end delay.
Sathiaseelan, Arjuna, Selimi, Mennan, Molina, Carlos, Lertsinsrubtavee, Adisorn, Navarro, Leandro, Freitag, Felix, Ramos, Fernando, Baig, Roger.  2017.  Towards Decentralised Resilient Community Clouds. Proceedings of the 2Nd Workshop on Middleware for Edge Clouds & Cloudlets. :4:1–4:6.
Recent years have seen a trend towards decentralisation - from initiatives on decentralized web to decentralized network infrastructures. In this position paper, we present an architectural vision for decentralising cloud service infrastructures. Our vision is on community cloud infrastructures on top of decentralised access infrastructures i.e. community networks, using resources pooled from the community. Our architectural vision considers some fundamental challenges of integrating the current state of the art virtualisation technologies such as Software Defined Networking (SDN) into community infrastructures which are highly unreliable. Our proposed design goal is to include lightweight network and processing virtualization with fault tolerance mechanisms to ensure sufficient level of reliability to support local services.
Sathiyamurthi, P, Ramakrishnan, S, Shobika, S, Subashri, N, Prakavi, M.  2018.  Speech and Audio Cryptography System using Chaotic Mapping and Modified Euler's System. 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT). :606–611.
Security often requires that the data must be kept safe from unauthorized access. And the best line of speech communication is security. However, most computers are interconnected with each other openly, thereby exposing them and the communication channels that person uses. Speech cryptography secures information by protecting its confidentiality. It can also be used to protect information about the integrity and authenticity of data. Stronger cryptographic techniques are needed to ensure the integrity of data stored on a machine that may be infected or under attack. So far speech cryptography is used in many forms but using it with Audio file is another stronger technique. The process of cryptography happens with audio file for transferring more secure sensitive data. The audio file is encrypted and decrypted by using Lorenz 3D mapping and then 3D mapping function is converted into 2D mapping function by using euler's numerical resolution and strong algorithm provided by using henon mapping and then decrypted by using reverse of encryption. By implementing this, the resultant audio file will be in secured form.