the natural hierarchical relationships between users due to social and geographic circumstances. We proposed an eﬃ- cient and simple scheme for fingerprint design, and proposed a multistage colluder identification scheme by exploiting the hierarchical nature of the group-oriented system where the basic idea is to successively narrow down the size of the suspi- cious set. Performance criteria were analyzed to guide the pa- rameter settings during the design process. We demonstrated performance improvement of the proposed scheme over the orthogonal scheme via examples. Furthermore, we derived an upper bound on the expected computational burden of the proposed approach and showed that one additional ad- vantage of the tree-structure-based fingerprinting system is its computational e ﬃ ciency. We also evaluated the perfor- mance on real images and noted that the experimental results match the analysis. Overall, by exploiting knowledge of the dynamics between groups of colluders, our proposed scheme illustrates a promising mechanism for enhancing the collu- sion resistance performance of a multimedia fingerprinting system.
This class of techniques aims at disclosing statistical correlations introduced by compres- sion schemes. The JPEG compression is well known to be a lossy scheme, i.e. some information is lost during the process. In particular, a quantization step taken on the DCT coefficient is mainly responsible for such loss. The full quantization is based on a table of 192 values, associated with each frequency on a 8 × 8 block-basis and may vary depending on the quality setting. In  it has been demonstrated that such table can be estimated and extracted from the content. Inconsistencies of it all over the image, or video, can be taken as evidence of tampering [82, 21]. Moreover, it has been shown that JPEG compressing the data twice, some specific artifacts are introduced in an image [99, 128], as well as in a video . Lately, also JPEG2000 traces have been studied as proof of alteration  and also for double compression . Block artifacts introduced by a JPEG compression at the border of neighboring pixels are studied in  for forensics purposes supposing that manipulations are likely to alter such artifacts. Assuming that, when creating a composite, it is unlikely to match the same level of quantization of the two spliced parts,  analyzes the quantization coefficients to prove tampering.
As a result, the trustworthiness of media contents is strongly compromised, with effects that span in many practical scenarios. Considering also the more intuitive and immedi- ate impact of visual data with respect to textual documents, the potential diffusion of distorted or completely fake multimedia content on websites, information media, adver- tisement and legal proceedings seriously represents an issue to be addressed. It appears evident that the authenticity of multimedia data can no longer be taken from granted, and their fidelity to reality should be called into question. In other words, the develop- ment of media-related technologies has to be combined with effective techniques for their protection and verification. This would help in avoiding an illegitimate exploitation, be it malicious or not, of the semantic message they may convey. Indeed, the role of visual con- tent manipulation is currently under debate, questioning how manipulated images impact users’ perceptions and opinions on topics and people [37, 143].
Rahman, 2001) encrypts raw data or compressed data with traditional cipher or improved cipher directly. These algorithms are secure, but often cost much time and change data format. Therefore, they are more suitable for data storage than data transmission. Partial encryption method (Ahn, Shim, Jeon, & Choi, 2004; Lian, Liu, Ren, & Wang, 2005c; Shi, King, & Salama, 2006; To- sum & Feng, 2000; Zeng & Lei, 2003) encrypts only parts of multimedia data with traditional ciphers. These algorithms aim to obtain higher HI¿FLHQF\EDVHGRQWKHVDFUL¿FHRIVHFXULW\)RU a secure algorithm, the selection of the part to be encrypted should satisfy some principles (Lian, Sun, Zhang, & Wang, 2004a). Compared with di- rection encryption algorithms, partial encryption algorithms are more suitable for secure multimedia transmission. Compression-combined encryption method (Kankanhalli & Guan, 2002; Lian, Sun, & Wang, 2004b; Wu & Kuo, 2000) incorporates encryption operation into compression and real- izes compression and encryption simultaneously. 7KHVH DOJRULWKPV DUH RIWHQ RI KLJK HI¿FLHQF\ while the compression ratio and security are re- duced more or less. Thus, these algorithms can be a choice for lightweight media encryption in wireless or mobile network.
The development of computer graphics technologies has been bringing realism to computer generated multimedia data, e.g., scenes, human char- acters and other objects, making them achieve a very high quality level. However, these synthetic objects may be used to create situations which may not be present in real world, hence raising the demand of having ad- vance tools for differentiating between real and artificial data. Indeed, since 2005 the research community on multimediaforensics has started to develop methods to identify computer generated multimedia data, focusing mainly on images. However, most of them do not achieved very good performances on the problem of identifying CG characters.
The Professional Project course should be a research project which requires the application of the knowledge, techniques, methodology, and skills learned from other digital forensics courses. Topics could be either from academia or from industry. The survey result indicates that multimedia forensic analysis has been conducted by digital forensics practitioners, which requires the use of a suite of tools including VideoFOCUS, dTective, ClearID DAC, dVeleloper and Magnifi Spotlight. Several research issues on multimediaforensics exists which need to be undertaken to improve the efficiency and accuracy of the results. Another important topic is the deployment of a honeypot which has been recently used for cyber security protection and network forensic investigation (Spitzner, 2003), due to its cost effectiveness and usefulness for security and forensic education and research. Other important topics include malware forensics analysis, social computing forensics (for example, forensics investigation on Facebook, MySpace, Twitter, Blogosphere, etc.), accounting and financial fraud detection and investigation. Furthermore, evidence should be presented in a in a clear, concise, professional way so that audiences in a courtroom, such as a jury, judge, and attorneys, can easily understand it. The Courtroom Experience course is an application of the knowledge, skills, and methodology learned from all the courses in the education program, including forensic law, criminal justice, communication, digital forensics investigation, and other computer courses. In a mock courtroom, judges and attorneys from industry and law enforcement can participate, and the cases may be a simulation of real world scenarios. In a mock trial course, the students can apply what they have learned and gain real world experiences.
Computer Forensics is the science of identifying, extracting preserving, and presenting the digital evidence stored in digital devices that can be legally admissible in court for any cybercrime or fraudulent . In other words, finding out facts, records, and digital trails can be legally admissible in the court for criminal prosecution . Digital information is fragile in that it can be easily modified, duplicated, or destroyed etc. In the course of the investigation it should be assured that digital evidence is not modified without appropriate authorization . Computer forensics has had major impact in detecting and preventing frauds as well as potential business losses that can deface an organization of its reputation. The basic process of computer forensics is based on the following steps:
This development serves the community but also has threats such as eavesdropping and illegal use of information [1-10]. A new term that protects the user has appeared which forensic science is. Forensic science has many branches and one of them is digital forensics. Digital forensics involves investigation and retrieval of items found in digital devices; oftentimes digital forensics is a relation to computer crime also called cyber forensics. Computer forensic includes stratifying techniques of computer investigation and analysis to fix criminality and supply evidence to support status. It is identifying, analyzing, presenting and preserving the digital evidence process. Cyber forensic tools are very easily used and play an important role to gather the evidence[11, 12, 38]. Cyber-crimes are in general classified into three categories, based on its impact on those affected. Cyber-crimes are hostile to persons, property, and the government. All categories of cyber-crimes impact us in many ways. Each category can use a different process and the process could be used differently from one criminal to another one. In cyber- crimes against persons: This form of cyber-crime can be in the form of cyberstalking deal or trade in something illegal, such as sharing pornography, trafficking, and grooming. Recently, law enforcement agencies deal with this category of cyber-crime very industriously and join forces around the world to reach the perpetrators and arrest them. In cyber- crimes against property: Just as in the actual world where a felon can rob and steal, a felon in the cyber domain resorts to theft and robbing. Currently, cyber felons can steal a person’s information like bank details and the wrong use the credit card to make several purchases online. Although crimes against a government are not as common as the previous two categories, crimes against a government are still considered a crime. Crimes in this category occur when
Ownership protection. In this application, a watermark signal is secretly selected by the copyright holder to represent his/her ownership, and is imperceptibly em- bedded in the multimedia source. As pirates are highly motivated to remove the copyright watermark, the embedding should survive common processing and re- sist intentional attacks so that the owner can demonstrate the presence of this wa- termark in case of dispute to verify his/her ownership. The detection should have as little ambiguity and false alarm as possible. In most scenarios, the total number of bits that can be embedded and extracted reliably does not have to be high. Authentication or tampering detection. In this application, we embed a set of sec- ondary data in the multimedia source beforehand, and later use it to determine whether the host media is tampered or not. The robustness against removing the watermark or making it undetectable is not a major concern as this clearly sig- nals the occurrence of tampering and there is no strong incentive to do so from an attacker’s point of view. The main threat is the forging of a valid authentica- tion watermark in an unauthorized or tampered multimedia signal, which must be prevented. In many practical applications, it is also desirable to locate the tam- pered regions and distinguish some noncontent changes (such as those incurred by moderate lossy compression) from other changes (such as content tampering). In general, the embedding payload should be suﬃciently high to accommodate these needs. The detection must be performed without using the original unwa- termarked copy, because either this original is unavailable or its integrity has not been established yet. This kind of detection is known as noncoherent detection or blind detection.
What makes operational forensics an entity of its own is the ability to use the time and effort spent in planning for benefits other than prosecuting criminals. The key benefit is in an organization’s ability to learn some- thing from every operational miscue. Countless times, systems stop run- ning because intruders who only partially succeed at gaining access have corrupted the network connections. In most instances, all the informa- tion that could have been used to close access vulnerabilities goes away with the Ctrl-Alt-Delete keys. Systems do not crash without cause. If each cause were evaluated, many of them could be eliminated or their proba- bility of reoccurring significantly reduced.
Computers have become an integral part of our lives. They have changed the way we work. Due to this cyber crimes are steadily increasing. Criminals have become to realize that if they want to keep doing their deeds they have to keep abreast with the times. Hence there is a need to pinpoint exactly what happened. The ability of exposing is called “cyber forensics”. Cyber Penetrators have adopted more sophisticated tools and tactics that endanger the operations of the global phenomena. These attackers are also using anti-forensic techniques to hide evidence of a cyber crime. Cyber forensics tools must increase its toughness and counteract these advanced persistent threats. This review paper focuses on briefing of Cyber forensics, various phases of cyber forensics, handy tools and new research trends in this fascinated area.
Based on the raised mobile security issue in usages of smart phones, the purpose of this study is to acquire the evidence smart phone in opened status, by using the Android forensic tools to examine smart phone digital forensics. This study will refer to the United States National Institute of Standards and Technology tool in the smart phone specification  and smart phone forensics process in order to make legally binding, and the digital evidence will have evidences ability and credibility.
When we first started the TeamViewer Forensics project, there was no prior in-depth research that had been done on the artifacts of TeamViewer. Throughout the course of our research, we came across a website, forensicartifacts.com, which contained an article by Matt Nelson called “TeamViewer 8,” providing a list of all of the artifacts found on a computer (Nelson, 2012). Although this has been done, we want to provide a paper on where the artifacts are stored and how to find them using forensic software from a student’s perspective.
One important element of digital forensics is the credibility of the digital evidence. Digital evidence includes computer evidence, digital audio, digital video, cell phones, digital fax machines etc. The legal settings desire evidence to have integrity , authenticity, reproductivity, non-interference and minimization.
Abstract— Now a days, photographs are considered as very important part in various fields like digital forensics, medical imaging, digital forensics, scientific publications, in the courts as an evidence, etc. From last few years, photographers are also able to create composites of analog pictures. This process requires lots of time and expert knowledge is also required. Today, large number of image modification softwares and corresponding graphics are available. So, modifications of digital image become easy. Hence, we can hardly trust on photographs as evidence. In this paper, we are going to describe a technique for exposing fake images by the method of splicing or compositing the image. Here we used Adaboost algorithm for finding the face area and non-face area. This algorithm divides the whole image into number of parts and Pearson's correlation is for comparing difference between background and foreground color. This technology is very much easy for finding the fake image.
Every technology has some benefits and some limitations. Cloud computing has its own set of them. Cloud computing has various advantages i.e. reliability, cost effective, scalability, fault tolerance, backup. But there are also some security issues in cloud computing because data is stored on worldwide platform. Many attackers can use cloud services to create vulnerability in the cloud system. There are some forensics tools implemented to find information about these attacks in cloud environment. This complete process to find evidence in cloud environment is known as cloud forensics. This paper presents a study about cloud forensics methods, technology used, comparative study to provide awareness of tools, methods, challenges in cloud forensics. This information will help to find new techniques to improve forensics process in cloud forensics.
question the power of the word, image, and sound bite to represent social and environmental injustice. When K-12 students learn to critically read and write with images, sounds, multimedia, and print, they deepen their critical thinking skills and develop their identities as responsible and empowered global citizens. Critical Media Literacy combines theoretical foundations of cultural studies and critical pedagogy with practical classroom applications of new digital media and technology as well as
Plan for a forensic examiner to respond to the search warrant scene in order to perform a computer forensic examination and analysis on the "live" evidence. As many agents have been trained to pull the device's plug before conducting forensics, be aware that, understandably, they may be uncomfortable with the idea of live forensics and counter-encryption procedures. They have been trained that a still-running computer presents forensic difficulties, as the device is not in a static state. However, methods exist to address this situation, and it is better to attempt to develop evidence with the subject's device still running than to power down the subject's computer and
network traffic fully. There are many toolkits for building network traffic analysis and statistical event records. [Io02, FL01, MJ93] After obtaining the network traffic data, forensics analysis is needed. Data mining techniques can be used for mining stream data or email contents [LS98, LSM99]. Utilizing artificial intelligent approaches to identify special features [SA03], IP trace back approaches [St00, HB00] to the attack origin identification and mapping topology approaches for the possible location of the attack origin [Ta02, MP01].