Smart E-Voting System

The advancement within the mobile devices, wireless and internet technologies given rise to the new application which will create the pick method terribly simple and economical. The e-voting promising the chance of convenient, simple and safe thanks to capture and count the votes in an election. This subject provides the specification and necessities for E-Voting victimisation an android platform. The e-voting suggests that the pick method in election by victimisation device. During this topic it's described however the android mobile phones area unit economical and may be used for pick. The robot platform is employed to develop an application. Afterward the user opens the appliance. The face authentication is finished so the OTP (One Time Password) is send to the user's mail address if the user is valid user. Victimisation OTP user opens the pick type he casts his vote so click on submits button so logout. On the server aspect we are able to check the results. The GCM is that sends notification to user's android phone. The sqlite is that the native information of the user's phone. Within the ancient system there was a necessity to travel on the booth and forged a vote. Individuals from distinct places who didn't have their pick cards cannot forge their votes. Additionally authentication of the user wasn't sensible and acceptable. There was lots of labor that was terribly time intense. The results required to be calculated manually that was terribly time intense method. Thus the planned system is developed to get rid of the efforts required within the ancient pick method. The planned system has an application developed on robot phone via that the user will forged his vote from anyplace on the face of the world. The user registers by giving his personal details and therefore the image of his face that gets hold on within the information at the server aspect. a replacement method of pick cracks the limitation of ancient pick and focuses on the protection and performability of the pick, so it will reach to every an

A Proof of Work: Securing Majority-Attack in Blockchain Using Machine Learning and Algorithmic Game Theory

Blockchain's vast applications in different industries have drawn several researchers to pursue extensive research in securing blockchain technologies. In recent times we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority attack from taking place

Security Hazards when Law is Code.

As software continues to eat the world, there is an increasing pressure to automate every aspect of society, from self-driving cars, to algorithmic trading on the stock market. As this pressure manifests into software implementations of everything, there are security concerns to be addressed across many areas. But are there some domains and fields that are distinctly susceptible to attacks, making them difficult to secure? My dissertation argues that one domain in particular—public policy and law— is inherently difficult to automate securely using computers. This is in large part because law and policy are written in a manner that expects them to be flexibly interpreted to be fair or just. Traditionally, this interpreting is done by judges and regulators who are capable of understanding the intent of the laws they are enforcing. However, when these laws are instead written in code, and interpreted by a machine, this capability to understand goes away. Because they blindly fol- low written rules, computers can be tricked to perform actions counter to their intended behavior. This dissertation covers three case studies of law and policy being implemented in code and security vulnerabilities that they introduce in practice. The first study analyzes the security of a previously deployed Internet voting system, showing how attackers could change the outcome of elections carried out online. The second study looks at airport security, investigating how full-body scanners can be defeated in practice, allowing attackers to conceal contraband such as weapons or high explosives past airport checkpoints. Finally, this dissertation also studies how an Internet censorship system such as China’s Great Firewall can be circumvented by techniques that exploit the methods employed by the censors themselves. To address these concerns of securing software implementations of law, a hybrid human-computer approach can be used. In addition, systems should be designed to allow for attacks or mistakes to be retroactively undone or inspected by human auditors. By combining the strengths of computers (speed and cost) and humans (ability to interpret and understand), systems can be made more secure and more efficient than a method employing either alone.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120795/1/ewust_1.pd

Big Data Security (Volume 3)

After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology

Security and Privacy in Unified Communication

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The use of unified communication; video conferencing, audio conferencing, and instant messaging has skyrocketed during the COVID-19 pandemic. However, security and privacy considerations have often been neglected. This paper provides a comprehensive survey of security and privacy in Unified Communication (UC). We systematically analyze security and privacy threats and mitigations in a generic UC scenario. Based on this, we analyze security and privacy features of the major UC market leaders and we draw conclusions on the overall UC landscape. While confidentiality in communication channels is generally well protected through encryption, other privacy properties are mostly lacking on UC platforms

Persistent Homology Tools for Image Analysis

Topological Data Analysis (TDA) is a new field of mathematics emerged rapidly since the first decade of the century from various works of algebraic topology and geometry. The goal of TDA and its main tool of persistent homology (PH) is to provide topological insight into complex and high dimensional datasets. We take this premise onboard to get more topological insight from digital image analysis and quantify tiny low-level distortion that are undetectable except possibly by highly trained persons. Such image distortion could be caused intentionally (e.g. by morphing and steganography) or naturally in abnormal human tissue/organ scan images as a result of onset of cancer or other diseases. The main objective of this thesis is to design new image analysis tools based on persistent homological invariants representing simplicial complexes on sets of pixel landmarks over a sequence of distance resolutions. We first start by proposing innovative automatic techniques to select image pixel landmarks to build a variety of simplicial topologies from a single image. Effectiveness of each image landmark selection demonstrated by testing on different image tampering problems such as morphed face detection, steganalysis and breast tumour detection. Vietoris-Rips simplicial complexes constructed based on the image landmarks at an increasing distance threshold and topological (homological) features computed at each threshold and summarized in a form known as persistent barcodes. We vectorise the space of persistent barcodes using a technique known as persistent binning where we demonstrated the strength of it for various image analysis purposes. Different machine learning approaches are adopted to develop automatic detection of tiny texture distortion in many image analysis applications. Homological invariants used in this thesis are the 0 and 1 dimensional Betti numbers. We developed an innovative approach to design persistent homology (PH) based algorithms for automatic detection of the above described types of image distortion. In particular, we developed the first PH-detector of morphing attacks on passport face biometric images. We shall demonstrate significant accuracy of 2 such morph detection algorithms with 4 types of automatically extracted image landmarks: Local Binary patterns (LBP), 8-neighbour super-pixels (8NSP), Radial-LBP (R-LBP) and centre-symmetric LBP (CS-LBP). Using any of these techniques yields several persistent barcodes that summarise persistent topological features that help gaining insights into complex hidden structures not amenable by other image analysis methods. We shall also demonstrate significant success of a similarly developed PH-based universal steganalysis tool capable for the detection of secret messages hidden inside digital images. We also argue through a pilot study that building PH records from digital images can differentiate breast malignant tumours from benign tumours using digital mammographic images. The research presented in this thesis creates new opportunities to build real applications based on TDA and demonstrate many research challenges in a variety of image processing/analysis tasks. For example, we describe a TDA-based exemplar image inpainting technique (TEBI), superior to existing exemplar algorithm, for the reconstruction of missing image regions

A framework for comparing the security of voting schemes

We present a new framework to evaluate the security of voting schemes. We utilize the framework to compare a wide range of voting schemes, including practical schemes in realworld use and academic schemes with interesting theoretical properties. In the end we present our results in a neat comparison table. We strive to be unambiguous: we specify our threat model, assumptions and scope, we give definitions to the terms that we use, we explain every conclusion that we draw, and we make an effort to describe complex ideas in as simple terms as possible. We attempt to consolidate all important security properties from literature into a coherent framework. These properties are intended to curtail vote-buying and coercion, promote verifiability and dispute resolution, and prevent denial-of-service attacks. Our framework may be considered novel in that trust assumptions are an output of the framework, not an input. This means that our framework answers questions such as ”how many authorities have to collude in order to violate ballot secrecy in the Finnish paper voting scheme?

Kleptography and steganography in blockchains

Despite its vast proliferation, the blockchain technology is still evolving, and witnesses continuous technical innovations to address its numerous unresolved issues. An example of these issues is the excessive electrical power consumed by some consensus protocols. Besides, although various media reports have highlighted the existence of objectionable content in blockchains, this topic has not received sufficient research. Hence, this work investigates the threat and deterrence of arbitrary-content insertion in public blockchains, which poses a legal, moral, and technical challenge. In particular, the overall aim of this work is to thoroughly study the risk of manipulating the implementation of randomized cryptographic primitives in public blockchains to mount kleptographic attacks, establish steganographic communication, and store arbitrary content. As part of our study, we present three new kleptographic attacks on two of the most commonly used digital signatures: ring signature and ECDSA. We also demonstrate our kleptographic attacks on two real cryptocurrencies: Bytecoin and Monero. Moreover, we illustrate the plausibility of hijacking public blockchains to establish steganographic channels. Particularly, we design, implement, and evaluate the first blockchain-based broadcast communication tool on top of a real-world cryptocurrency. Furthermore, we explain the detrimental consequences of kleptography and steganography on the users and the future of the blockchain technology. Namely, we show that kleptography can be used to surreptitiously steal the users' secret signing keys, which are the most valuable and guarded secret in public blockchains. After losing their keys, users of cryptocurrencies will inevitably lose their funds. In addition, we clarify that steganography can be used to establish subliminal communication and secretly store arbitrary content in public blockchains, which turns them into cheap cyberlockers. Consequently, the participation in such blockchains, which are known to store unethical content, can be criminalized, hindering the future adoption of blockchains. After discussing the adverse effects of kleptographic and steganographic attacks on blockchains, we survey all of the existing techniques that can defend against these attacks. Finally, due to the shortcomings of the available techniques, we propose four countermeasures that ensure kleptography and steganography-resistant public blockchains. Our countermeasures include two new cryptographic primitives and a generic steganographyresistant blockchain framework (SRBF). This framework presents a universal solution that deters steganography and practically achieves the right to be forgotten (RtbF) in blockchains, which represents a regulatory challenge for current immutable blockchains