Analysis of adversarial attacks against CNN-based image forgery detectors

With the ubiquitous diffusion of social networks, images are becoming a dominant and powerful communication channel. Not surprisingly, they are also increasingly subject to manipulations aimed at distorting information and spreading fake news. In recent years, the scientific community has devoted major efforts to contrast this menace, and many image forgery detectors have been proposed. Currently, due to the success of deep learning in many multimedia processing tasks, there is high interest towards CNN-based detectors, and early results are already very promising. Recent studies in computer vision, however, have shown CNNs to be highly vulnerable to adversarial attacks, small perturbations of the input data which drive the network towards erroneous classification. In this paper we analyze the vulnerability of CNN-based image forensics methods to adversarial attacks, considering several detectors and several types of attack, and testing performance on a wide range of common manipulations, both easily and hardly detectable

Beginner's Guide for Cybercrime Investigators

In the real world there are people who enter the homes and steal everything they find valuable. In the virtual world there are individuals who penetrate computer systems and "steal" all your valuable data. Just as in the real world, there are uninvited guests and people feel happy when they steal or destroy someone else's property, the computer world could not be deprived of this unfortunate phenomenon. It is truly detestable the perfidy of these attacks. For if it can be observed immediately the apparent lack of box jewelry, penetration of an accounting server can be detected after a few months when all clients have given up the company services because of the stolen data came to competition and have helped it to make best deals. Cybercrime is a phenomenon of our time, often reflected in the media. Forensic investigation of computer systems has a number of features that differentiate it fundamentally from other types of investigations. The computer itself is the main source of information for the investigator. CONTENTS: Computing systems and storage media - Computing devices - - Peripheral devices - - External drives for media storage - Typology of data stored on specific supports – File systems - - Program that allows working with ” inactive” space - Information that can be obtained from the computing system environment Computer networks - Copper wire in computer networks - Optical fibers - Wireless LAN - Internet and Intranet Software and services - Client/server architecture - Protocols and Standards - Internet Services - - e-Mail - - - Spam - - HTTP - - Web address - URL - - Web browsers - - - Browser cookies - - Working with web pages - - - Choosing your favorite web pages - - - Keeping track of visited web pages - - - Saving web pages - - Proxy servers - - Privacy on the Internet - FTP - Instant Messaging - Peer-to-peer networks Vulnerabilities - The first attacks on the Internet - Cybercrime - - Typologies of cyber attackers - - - Classification of cyber attackers according to their skills and objectives - Classification of risks and incidents in cyberworld - - Classification as a list of terms - - List of categories - - Categories of results - - Empirical lists - Events, attacks and incidents - Online security events, actions, and targets - - Actions - - Targets - Attacks - - Tools - - Vulnerabilities - - Unauthorized results Cybercrime laws - The concept of "cybercrime" Investigations - Computer forensic investigations - Digital evidence - Digital sampling during investigations - The suspect - Witnesses in cybercrime - Transporting of samples in laboratory - Analysis of samples - Preparing team members - Computer tools Convention on Cybercrime - Preamble - Chapter I – Use of terms - Chapter II – Measures to be taken at the national level - - Section 1 – Substantive criminal law - - - Title 1 – Offences against the confidentiality, integrity and availability of computer data and systems - - - Title 2 – Computer-related offences - - - Title 3 – Content-related offences - - - Title 4 – Offences related to infringements of copyright and related rights - - - Title 5 – Ancillary liability and sanctions - - Section 2 – Procedural law - - - Title 1 – Common provisions - - - Title 2 – Expedited preservation of stored computer data - - - Title 3 – Production order - - - Title 4 – Search and seizure of stored computer data - - - Title 5 – Real-time collection of computer data - - Section 3 – Jurisdiction - Chapter III – International co-operation - - Section 1 – General principles - - - Title 1 – General principles relating to international co-operation - - - Title 2 – Principles relating to extradition - - - Title 3 – General principles relating to mutual assistance - - - Title 4 – Procedures pertaining to mutual assistance requests in the absence of applicable international agreements - - Section 2 – Specific provisions - - - Title 1 – Mutual assistance regarding provisional measures - - - Title 2 – Mutual assistance regarding investigative powers - - - Title 3 – 24/7 Network - Chapter IV – Final provisions Recommendation No. R (95) 13 - Appendix to Recommendation No. R (95) 13 - - I. Search and seizure - - II. Technical surveillance - - III. Obligations to co-operate with the investigating authorities - - IV. Electronic evidence - - V. Use of encryption - - VI. Research, statistics and training - - VII. International co-operation Rules for obtaining digital evidence by police officers Standards in the field of digital forensics Principles in digital evidence Procedures model for the forensic examination - Hard disk examination Code of Ethics Sources and references About - Nicolae Sfetcu - - By the same author - - Contact Publishing House - MultiMedia Publishin

A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Copyright Protection for Surveillance System Multimedia Stream with Cellular Automata Watermarking

Intelligent Surveillance Systems are attracting extraordinary attention from research and industry. Security and privacy protection are critical issues for public acceptance of security camera networks. Existing approaches, however, only address isolated aspects without considering the integration with established security technologies and the underlying platform. Easy availability of internet, together with relatively inexpensive digital recording and storage peripherals has created an era where duplication, unauthorized use and misdistribution of digital content has become easier. The ease of availability made digital video popular over analog media like film or tape. At the same time it demands a sharp attention regarding the ownership issue. The ownership and integrity can easily be violated using different audio and video editing softwares. To prevent unauthorized use, misappropriation, misrepresentation; authentication of multimedia contents achieved a broad attention in recent days and to achieve secure copyright protection we embedded some information in audio and videos and that audio or video is called copyright protected. Digital watermarking is a technology to embed additional information into the host signal to ensure security and protection of multimedia data. The embedded information can’t be detected by human but some attacks and operations can tamper that information to breach protection. So in order to find a secure technique of copyright protection, we have analyzed different techniques. After having a good understanding of these techniques we have proposed a novel algorithm that generates results with high effectiveness, additionally we can use self-extracted watermark technique to increase the security and automate the process of watermarking. Forensic digital watermarking is a promising tool in the fight against piracy of copyrighted motion imagery content, but to be effective it must be (1) imperceptibly embedded in high-definition motion picture source, (2) reliably retrieved, even from degraded copies as might result from camcorder capture and subsequent very-low-bitrate compression and distribution on the Internet, and (3) secure against unauthorized removal. Audio and video watermarking enables the copyright protection with owner or customer authentication and the detection of media manipulations. The available watermarking technology concentrates on single media like audio or video. But the typical multimedia stream consists of both video and audio data. Our goal is to provide a solution with robust and fragile aspects to guarantee authentication and integrity by using watermarks in combination with content information. We show two solutions for the protection of audio and video data with a combined robust and fragile watermarking approach. The first solution is to insert a time code into the data: We embed a signal as a watermark to detect gaps or changes in the flow of time. The second solution is more complex: We use watermarks to embed information in each media about the content of the other media. In our paper we present the problem of copyright protection and integrity checks for combined video and audio data. Both the solutions depend upon cellular automata, cellular automata are a powerful computation model that provides a simple way to simulate and solve many difficult problems in different fields. The most widely known example of Cellular Automata is the Game-of-Life. Cellular automaton growth is controlled by predefined rule or programs .The rule describes how the cell will interact with its neighborhood. Once the automaton is started it will work on its own according to the rule specified.

Information Forensics and Security: A quarter-century-long journey

Information forensics and security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to facilitate the gathering of solid evidence to hold perpetrators accountable. For over a quarter century, since the 1990s, the IFS research area has grown tremendously to address the societal needs of the digital information era. The IEEE Signal Processing Society (SPS) has emerged as an important hub and leader in this area, and this article celebrates some landmark technical contributions. In particular, we highlight the major technological advances by the research community in some selected focus areas in the field during the past 25 years and present future trends

An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones

Drone susceptibility to jamming or spoofing attacks of GPS, RF, Wi-Fi, and operator signals presents a danger to future medical delivery systems. A detection framework capable of sensing attacks on drones could provide the capability for active responses. The identification of interference attacks has applicability in medical delivery, disaster zone relief, and FAA enforcement against illegal jamming activities. A gap exists in the literature for solo or swarm-based drones to identify radio frequency spectrum attacks. Any non-delivery specific function, such as attack sensing, added to a drone involves a weight increase and additional complexity; therefore, the value must exceed the disadvantages. Medical delivery, high-value cargo, and disaster zone applications could present a value proposition which overcomes the additional costs. The paper examines types of attacks against drones and describes a framework for designing an attack detection system with active response capabilities for improving the reliability of delivery and other medical applications.Comment: 7 pages, 1 figures, 5 table