Detecting the Risk of Online Harms on People With Social Orientation Impairments

This chapter proposes automated screening of internet and multimedia communications through a combination of neuroeconomics to measure neuro-response plasticity through forensic phonetics, EEG monitoring, and EigenFaces. These measure neuro-response plasticity through facial differences, including through the eyes, differences in EEG pattern, and prosody in the form of tone of voice. Through describing the ‘Distress in the Mind Test', a computer program is proposed that can be implemented on any device with a camera and microphone and can therefore also be used to diagnose social orientation impariments, such as autism and social phobia. Further development would prevent people with social orientation impairments or whom are otherwise at risk from online harms being exposed to them through automated content filtering.

User Authentication Into Electronic Health Record Based on Reliable Lightweight Algorithms

Supporting a mechanism to authenticate members in electronic health record (EHR) is a fundamental procedure to prevent different threats from penetrating patients' identities/data. Existing authentication schemes still suffer from security drawbacks. Exchanging medical-related information/data between clients and the servers leaves them compromised to breakthrough by intruders as they can transmit over an unreliable environment. To guarantee the protection of patient records, this chapter proposes a new scheme that provides authentication of patients/providers in EHR depending on the legitimate member identities and the device information. The scheme utilizes an elliptic curve cryptography and lightweight hash function to accomplish robust security with satisfying performance. Moreover, it depends on a set of techniques such as multi-pseudonyms to authenticate legitimate members. Additionally, concentrated theoretical and experimental analysis proves that the proposed provides elevated performance and security compared to existing research.

Statistical Methods for Conducting the Ontology and Classifications of Fake News on Social Media

Fake news and its impacts are serious threats to social media in recent time. Studies on the ontology of these problems reveal that serious cybercrimes such as character assassination, misinformation, and blackmailing that some people intentionally perpetrate through social networks significantly correlate with fake news. Consequently, some classical studies on social anthropology have profiled the problems and motives of perpetrators of fake news on political, rivalry, and religious issues in contemporary society. However, this classification is restrictive and statistically defective in dealing with cyber security, forensic problems, and investigation of social dynamics on social media. This chapter exhaustively discusses the above issues and identifies solutions to challenges confronting research community in the above domain. Thematic analysis of responses of certain respondents reveal three new classifications of fake news that people propagate on social media on the basis of mode of propagation, motives of perpetrators, and impacts on victims.

Preserving Information Security Using Fractal-Based Cryptosystem

The chapter intends to propose a hybrid cryptosystem based on a chaotic map and a fractal function. The sequential order of process execution provides a computationally less expensive and simple approach that still designed a secure cryptosystem. A one-dimensional Ricker map and its modified form are employed to initially shuffle the image pixels twice, and also a pseudo-random sequence is generated using both maps. The algorithm implemented a sequence of pixel confusion-diffusion steps using the image rotation and a transcendental anti-Mandelbrot fractal function (TAMFF) and its Mann-iterated fractal function (Sup-TAMFF). Finally, the pixel value of an image obtained in the last step and the recent two pixels of the encrypted image is XORed with the corresponding pseudo-random matrix value to get the cipher image. Subsequently, various performance tests are conducted to verify the suitability of the given method to be used in real-world information transmission.

Prediction, Detection, and Mitigation of DDoS Attacks Using HPCs

Web service interruptions caused by DDoS (distributed denial of service) attacks have increased considerably over the years, and intrusion detection systems (IDS) are not enough to detect threats on the network, even when used together with intrusion prevention systems (IPS), taking into account the increase of assets in the traffic path, where it creates unique points of failure in the system, and also taking into account the use of data that contains information about normal traffic situations and attacks, where this comparison and analysis can cost a significant amount of host resources, to try to guarantee the prediction, detection, and mitigation of attacks in real-time or in time between detection and mitigation, being crucial in harm reduction. This chapter presents an adaptive architecture that combines techniques, methods, and tools from different segments to improve detection accuracy as well as the prediction and mitigation of these threats and to show that it is capable of implementing a powerful architecture against this type of threat, DDoS attacks.

Learning With Differential Privacy

The leakage of data might have an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint protection, intrusion detection systems are prone to leakage. Differential privacy comes to the rescue with a proper promise of protection against leakage, as it uses a randomized response technique at the time of collection of the data which promises strong privacy with better utility. Differential privacy allows one to access the forest of data by describing their pattern of groups without disclosing any individual trees. The current adaption of differential privacy by leading tech companies and academia encourages authors to explore the topic in detail. The different aspects of differential privacy, its application in privacy protection and leakage of information, a comparative discussion on the current research approaches in this field, its utility in the real world as well as the trade-offs will be discussed.

The Intersection of Cybercrime and the Blockchain

The immutability of blockchains and the transparency of their transaction records would appear to limit the benefit of exploiting them for criminal activity. However, blockchains also offer a high degree of anonymity, similar to fiat paper currency; the technology was intended to facilitate trustless transactions. Coupled with a global, borderless reach, blockchains have become an enabler of cybercrime. They are a new class of assets that, like all other assets, possess security risks and become potential targets of attack. In particular, cryptocurrencies, which depend on blockchain technology, provide significant incentives for attack because of their value. The goals of this chapter are to identify and classify blockchain-based cybercrimes and to explore the avenues for protecting against them at individual, organizational, and policy levels.

Self-Driving Robotic Cars

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

Oblivion Is Full of Memory

The right to informational self-determination has raised bitter debate over the last decade as to the opportunity and possible scope of the right to demand withdrawal from the internet of personal information which, while true, might represent a detriment that there is no legal duty to put up with. The leading case in this topic is that of Mario Costeja, Judgment of the EU Court of Justice, May 13, 2014. The interest of recent European jurisprudence lies not so much in the recognition of such a right but in the appreciation of certain limits to its implementation, assisting data protection authorities in balancing the rights at stake in each case. Reflection on the current status of the issue considers rights and duties imposed in the matter by Regulation (EU) 2016/679, of 27 April, known as the new General Data Protection Regulation.

Implementing Information Security Using Multimodal Biometrics

With the exponential growth of smart devices and dependency on the internet and wireless networks, the security of information is a major challenge in the recent years. Biometrics have been widely used for information security. It plays a crucial role in minimizing the probability of inappropriate access. Human biometrics are characterized into physical and behavioral features. In this chapter, the authors propose to use fingerprint and online signature for information security. Though biometric provides more security and integrity, it is also threatened by various attacks. Digital watermarking is the answer to the above problems. Initially, the features of the human biometric images are extracted and act as watermarks for other biometric image. It is assumed that fingerprints act as a host and a signature as watermark. This chapter presents a survey of various biometric and watermarking techniques. The chapter also reviewed the work done by different researchers in the area, algorithms employed by them with their literature to utilize them for biometric protection.