Blockchain Technology Is a Boost to Cyber Security

The information in any real-time application is needed to be digitalized across the world. Since digitalization of data happens, there comes the role of privacy. Blockchain could address the security challenge that happens in the any real sector. There are a few more challenges that prevail in the industry such as integrity in data, traceability of stored records, and interoperability among organizations that share information. This chapter says what blockchain is and applications in which blockchain technology could solve the existing challenges where they lack security, privacy, integrity, and interoperability.

Security Framework for Smart Visual Sensor Networks

Due to the significance of image data over the scalar data, the camera-integrated wireless sensor networks have attained the focus of researchers in the field of smart visual sensor networks. These networks are inexpensive and found wide application in surveillance and monitoring systems. The challenge is that these systems are resource deprived systems. The visual sensor node is typically an embedded system made up of a light weight processor, low memory, low bandwidth transceiver, and low-cost image sensor unit. As these networks carry sensitive information of the surveillance region, security and privacy protection are critical needs of the VSN. Due to resource limited nature of the VSN, the image encryption is crooked into an optimally lower issue, and many findings of image security in VSN are based on selective or partial encryption systems. The secure transmission of images is more trivial. Thus, in this chapter, a security frame work of smart visual sensor network built using energy-efficient image encryption and coding systems designed for VSN is presented.

Network Intrusion Detection and Prevention Systems for Attacks in IoT Systems

Internet of things (IoT) has transformed greatly the improved way of business through machine-to-machine (M2M) communications. This vast network and its associated technologies have opened the doors to an increasing number of security threats which are dangerous to IoT and 5G wireless networks. The first part of this chapter presents instruction detection system (IDS) which detect the various attacks in 6LoWPAN layer. An IDS is to detect and analyze both inbound and outbound network traffic for abnormal activities. An IPS complements an IDS configuration by proactively inspecting a system's incoming traffic to weed out malicious requests. A typical IPS configuration uses web application firewalls and traffic filtering solutions to secure applications. An IPS prevents attacks by dropping malicious packets, blocking offending IPs and alerting security personnel to potential threats. Machine learning (ML)-based instruction detection and prevention system (IDPS) is proposed and implemented in Contiki simulation environment.

Techniques for Analysis of Mobile Malware

The rapid rise in the number of mobile devices has resulted in an alarming increase in mobile software and applications. The mobile application markets/stores too have created a fundamental shift in the way mobile applications are delivered to users, with apps being added and updated in thousands every day. Even though research progresses have been achieved towards detection and mitigation of mobile security, open challenges still remain and also keep evolving in this area. Several studies reveal that mobile application markets/stores do harbor applications that are either vulnerable or malicious in nature, leading to compromises of millions of devices. This chapter (1) captures the attack surface of mobile devices, (2) lists the various mobile malware analysis techniques, and (3) lays the ground for research on mobile malware by providing mobile malware dataset resources, tools for malware analysis, patent landscaping for mobile malware detection, and a few open challenges in malware analysis.

The Role of Artificial Intelligence in Cyber Security

Cyber security has become a major concern in the digital era. Data breaches, ID theft, cracking the captcha, and other such stories abound, affecting millions of individuals as well as organizations. The challenges have always been endless in inventing right controls and procedures and implementing them with acute perfection for tackling with cyber attacks and crimes. The ever-increasing risk of cyber attacks and crimes grew exponentially with recent advancements in artificial intelligence. It has been applied in almost every field of sciences and engineering. From healthcare to robotics, AI has created a revolution. This ball of fire couldn't be kept away from cyber criminals, and thus, the “usual” cyber attacks have now become “intelligent” cyber attacks. In this chapter, the authors discuss specific techniques in artificial intelligence that are promising. They cover the applications of those techniques in cyber security. They end the discussion talking about the future scope of artificial intelligence and cyber security.

Study on Query-Based Information Extraction in IoT-Integrated Wireless Sensor Networks

The internet of things-integrated sensor nodes (IoT-WSN) is widely adopted in variety of applications such as fire detection, gas leakage detection in industry, earthquake detection, vibrating locations on flyover, weather monitoring, and many more wherein highest value is required in time to serve the abnormal areas with highest priority. The query-based information extraction has increased attention of many researchers working on increasing the network lifetime of the IoT-WSN. In resource-constraint IoT-WSN, executing the requests (in the form of queries) in time with minimum energy consumption is the main requirement and focus. The query processing at sink node in collaboration with neighboring nodes and then finding the top-k values for data aggregation is the most challenging job in IoT-WSN. This chapter investigates the various query-based approaches and improvements in the query data availability. The chapter also presents a comparative analysis that gives an idea of different aspects and applications of query-based schemes.

The Fundamentals of Digital Forensics and Cyber Law

This chapter provides prerequisites associated with cyber crimes, cyber forensics, and law enforcement. It consists of a brief introduction to the definition of cyber crimes, its classification, challenges associated with it and how it evolved with time, impact on the society, cyber terrorism, and the extent of problem scalability along with focusing on law enforcement aspects associated with the tracking and the prevention from such type crimes. The aspects discussed here include various cyber laws and law enforcement techniques introduced by various countries throughout the world which helps them to fight against cyber crimes. The cyber laws discussed include Australian, Canadian, United States, United Kingdom, and Indian law. This chapter also deals with the digital/cyber forensics, what does digital/cyber forensics mean, its types, and laws/rules revolving around them, like how to collect evidence, jurisdictions, and e-discovery.

Secured Information Exchange Using Haptic Codes

This chapter discloses an invention related to methods and systems to provide secure and custom information exchange code for the users of haptic or kinesthetic communication devices in a variety of applications. The proposed information exchange codes are named as “haptic codes,” where it maps several touch interactive locations into a single information exchange code. Thus, the proposed haptic code facilitates the representation of different notions to unique information exchange character/digit/symbol. A method has been invented to design eight such codes from the intuitive touch gestures (ITG) of user, each of which uses double-touch on arbitrary location within the touch pad/screen without shifting hand position on every touch. Hand position may or may not be the same after the generation of every ITG. Haptic codes are made secure by incorporating a new cryptographic system, which employs polar graph for encoding and decoding such locations using polar curves as shareable keys. Therefore, haptic codes can be exchanged for secure communication and read by devices that supports to touch.

Intelligent Malware Detection Using Deep Dilated Residual Networks for Cyber Security

Malware is the most serious security threat, which possibly targets billions of devices like personal computers, smartphones, etc. across the world. Malware classification and detection is a challenging task due to the targeted, zero-day, and stealthy nature of advanced and new malwares. The traditional signature detection methods like antivirus software were effective for detecting known malwares. At present, there are various solutions for detection of such unknown malwares employing feature-based machine learning algorithms. Machine learning techniques detect known malwares effectively but are not optimal and show a low accuracy rate for unknown malwares. This chapter explores a novel deep learning model called deep dilated residual network model for malware image classification. The proposed model showed a higher accuracy of 98.50% and 99.14% on Kaggle Malimg and BIG 2015 datasets, respectively. The new malwares can be handled in real-time with minimal human interaction using the proposed deep residual model.

An Indian and Global Perspective on Cybercrime

Cybercrime is defined as a crime in which a computer is the object of the crime (hacking, phishing, spamming) or is used as a tool to commit an offense (child pornography, hate crimes). The advancement of technology has made us dependent on internet for all our needs. Internet has given us easy access to everything without moving from our place. Social networking, online shopping, storing data, gaming, online studying, online jobs, every possible thing that man can think of can be done through the medium of internet. However, with the development of the internet and its related benefits, the concept of cybercrimes arose. Cybercrimes are committed in different forms. In a report published by the National Crime Records Bureau, the incidence of cybercrimes under the IT Act has increased by 85.4% in the year 2011 as compared to 2010 in India, whereas the increase in incidence of the crime under IPC is by 18.5% as compared to the year 2010.