{"title":"Performance analysis of image steganalysis techniques and future research directives","authors":"Sanchita Pathak, Ratnakirti Roy, S. Changder","doi":"10.1504/IJICS.2018.10010646","DOIUrl":"https://doi.org/10.1504/IJICS.2018.10010646","url":null,"abstract":"Steganography is a technique of hiding information imperceptibly inside other medium so that the very fact of communication taking place remains hidden. Recently, the reach of internet has extensively widened through social networking and blogging websites and a high amount of digital media interchange, especially in the form of digital images is being witnessed. This poses a huge threat to security from hackers and terrorists, as this medium can be used for covert communication, thus justifying the need for good steganalysis techniques to detect the existence of hidden messages in digital images. This paper analyses some steganalysis techniques which attack various kinds of spatial domain steganography techniques. Some of them are chi-square attack, triples analysis, sample pair analysis, TPVD steganalysis and analysis of adjacent pixel pair steganalysis. This paper also identifies the current research challenges and discusses possible directions for future research in this field.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121339323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of an efficient classifier using proposed sensitivity-based feature selection technique for intrusion detection system","authors":"H. Hota, Dinesh K. Sharma, A. Shrivas","doi":"10.1504/IJICS.2018.10010649","DOIUrl":"https://doi.org/10.1504/IJICS.2018.10010649","url":null,"abstract":"Intrusion detection system protects an individual computer or network computer from suspicious data and protects the system from unauthorized access. In this paper, we propose a feature selection technique (FST) known as sensitivity based feature selection technique (SBFST) which selects relevant features from intrusion data based on the value of sensitivity. We compare various existing FSTs with the proposed SBFST from three different categories of NSL-KDD data set. Experimental results reveal that C4.5 with SBFST performs better than other existing FSTs and produce a high accuracy of 99.68% with 11 features and 99.95% accuracy with nine features for the multiclass and binary class problems respectively. It has also produced 99.64% accuracy for both multiclass and binary class problems respectively with six and seven features. The performance of proposed SBFST is also verified using the intersection of features, segment by segment with other FSTs and found to be better.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"1 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113978732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modelling a secure support vector machine classifier for private data","authors":"M. Sumana, K. Hareesha","doi":"10.1504/IJICS.2018.10010647","DOIUrl":"https://doi.org/10.1504/IJICS.2018.10010647","url":null,"abstract":"Privacy preserving data mining engrosses in drawing out information from distributed data without disclosing sensitive information to collaborating sites. This paper aims on the construction of a vertically distributed privacy preserving support vector machine classifier. The learning model is build for datasets, where one of the collaborating parties comprises the dependent attribute. Furthermore, the amount of privacy, computation speed and the accuracy of our classifier outperform other benchmark algorithms. Privacy of the perceptive attributes values of the cooperating sites are retained while performing secure computations. Collaborative classification is performed using these attributes. The site with the dependent attribute is the master site that initiates the process of secure computation to identify support vectors. Homomorphic property is used to protectively compute the data matrix on records/tuples available at sites. The recommended nonlinear privacy preserving classifier provides an accuracy equivalent to the non-privacy undistributed SVM classifier which uses all the attributes directly.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130583667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A survey on forensic event reconstruction systems","authors":"A. Dabir, A. Abdou, A. Matrawy","doi":"10.1504/IJICS.2017.10008447","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10008447","url":null,"abstract":"Security related incidents such as unauthorised system access, data tampering and theft have been noticeably rising. Tools such as firewalls, intrusion detection systems and anti-virus software strive to prevent these incidents. Since these tools only prevent an attack, once an illegal intrusion occurs, they cease to provide useful information beyond this point. Consequently, system administrators are interested in identifying the vulnerability in order to: 1) avoid future exploitation; 2) recover corrupted data; 3) present the attacker to law enforcement where possible. As such, forensic event reconstruction systems are used to provide the administrators with possible information. We present a survey on the current approaches towards forensic event reconstruction systems proposed over the past few years. Technical details are discussed, as well as analysis to their effectiveness, advantages and limitations. The presented tools are compared and assessed based on the primary principles that a forensic technique is expected to follow.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130523315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MAM-ISSIDS: multi-agent model-based intelligent and self-sharing intrusion detection system for distributed network","authors":"K. Anusha, E. Sathiyamoorthy","doi":"10.1504/IJICS.2017.10008448","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10008448","url":null,"abstract":"Intrusion detection system (IDS) is essential for protecting the computer networks from various threats and attacks. The autonomous multi-agent model (MAM) architecture is a scalable and smart alternative to leverage the strengths of the host and network based IDS. This paper proposes MAM-based intelligent and self-sharing IDS (MAM-ISSIDS) for distributed network to detect the host, network and web service attacks. Feature selection is performed by using the integrated particle swarm optimisation-genetic algorithm (PSO-GA) approach. The intuitionistic fuzzy rules are used to formulate the rules of the existing attackers for the benchmark dataset. The ontology structure is used to share the rules in network. The MAM is used for detecting the occurrence of abnormal traffic resulting due to the intrusion attacks. The proposed system achieves higher attack detection rate, accuracy and lower false positive rate due to the distributed sharing strategy of the MAM.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131805308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A novel quantum distributed key management protocol for ring-organised group","authors":"Rima Djellab, M. Benmohammed","doi":"10.1504/IJICS.2017.10004329","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10004329","url":null,"abstract":"Key distribution is a core building block for secure communication. In group communication, key distribution is not a simple extension of two-party communication. Many approaches were proposed in the classical field. Nevertheless, they are still based on the assumption that some computational problems are hard. Based on quantum mechanics lows, new field emerges allowing to generate and share a secret and secure key between two, or more, participants. In this paper, we propose new multiparty key distribution protocol in ring-organised communication group based on the well-known quantum key distribution protocol BB84. The security of the proposed solution is based on the unconditional security of the BB84 allowed by the mechanics lows and the mathematical proved secure operation XOR. In our proposed solution, each participant collaborates with a partial key in order to obtain at the end of the protocol the same group key that can be used for encryption aims. We also analyse and verify security properties of the proposed protocol. This is done using a probabilistic symbolic model-checker, the PRISM tool.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125552685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Update enabled multi-keyword searchable encryption scheme for secure data outsourcing","authors":"Vasudha Arora, Shyam Sunder Tyagi","doi":"10.1504/IJICS.2017.10008445","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10008445","url":null,"abstract":"Over the last decade, cloud computing has emerged as a distinct IT environment that is provisioned to provide remote access to a set of decentralised IT resources. Cloud computing enables the data owner to outsource their data and applications so that users could access the data from anywhere and at any time without any concern about local hardware and software management. However, concerns about outsourcing sensitive data cause privacy problems. Encrypting data before outsourcing protects data to some extent but searching on encrypted data may lead to compromised efficiency. Searchable encryption allows the cloud data to be retrieved efficiently based on certain relevance criterion. Our proposed scheme enables the dynamically updating already existing searchable encryption schemes with a high-level accuracy and security so that information leakage can be eliminated.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115985868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data hiding using lifting scheme and genetic algorithm","authors":"Geeta Kasana, Kulbir Singh, S. S. Bhatia","doi":"10.1504/IJICS.2017.10008444","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10008444","url":null,"abstract":"In this paper, data hiding algorithm by using lifting scheme and genetic algorithm (GA) has been proposed. Arnold transform has been used to scramble the secret image to secure the extraction of secret image. Lifting scheme is applied on the cover image to get the wavelet subbands. In this algorithm, scrambled secret image is embedded into significant wavelet coefficients of subbands of cover image. Scaling factor (SF) parameter is used in embedding and extracting process of the proposed algorithm and GA is used to optimise this parameter. This optimisation is used to maximise the value of peak signal to noise ratio (PSNR) of composite image and similarity index modulation (SIM) of extracted secret image. Experimental results reveal that proposed algorithm provides high embedding capacity and better quality of composite images than the existing data hiding techniques. To show the effectiveness of the proposed algorithm, statistical tests have been performed to show that the imperceptibility is maintained.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"13 1-4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120963097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Djoudi Touazi, Mawloud Omar, Abdelhakim Bendib, A. Bouabdallah
{"title":"A trust-based approach for securing data communication in delay tolerant networks","authors":"Djoudi Touazi, Mawloud Omar, Abdelhakim Bendib, A. Bouabdallah","doi":"10.1504/IJICS.2017.10008446","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10008446","url":null,"abstract":"The proliferation of network technologies drives many different network architectures to provide huge variety of services and contents to end clients. This task becomes more difficult when we are in networks with intermittent connections, called delay tolerant networks (DTN) where security is an important issue. In this paper, we propose a trust-based approach to secure data transfer in DTN in the presence of malicious transporters. Our proposal is intended to a DTN architecture which includes several sub-networks geographically dispersed in isolated regions and having an intermittent access to an infrastructure-based network (like internet). Our approach is based on a particular web-of-trust, which is formed based on existing social relationship among clients and transporters. We conducted intensive simulations and the obtained results show that it offers high packet delivery rate and resists against malicious transporter's behaviour.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"9 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128008838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A standardised data acquisition process model for digital forensic investigations","authors":"R. Montasari","doi":"10.1504/IJICS.2017.10005908","DOIUrl":"https://doi.org/10.1504/IJICS.2017.10005908","url":null,"abstract":"Similar to traditional evidence, courts of law do not assume that digital evidence is reliable if there is no evidence of some empirical testing regarding the theories and techniques pertaining to its production. Courts take a careful notice of the way in which digital evidence has been acquired and stored. In contrast with traditional crimes for which there are well-established standards and procedures upon which courts can rely, there are no formal procedures or models for digital data acquisition to which courts of law can refer. A standardised data acquisition process model is needed to enable digital forensic investigators to follow a uniform approach, and to assist courts of law in determining the reliability of digital evidence presented to them. This paper proposes a model that is standardised in that it can enable digital forensic investigators in following a uniform approach, and that is generic in that it can be applied in both law enforcement and corporate investigations. To carry out the research presented in the paper, the design science research process (DSRP) methodology proposed by Peffers et al. (2006) has been followed.","PeriodicalId":164016,"journal":{"name":"Int. J. Inf. Comput. Secur.","volume":"47 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116447857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}